risk/return

Impact: Reshaping Capitalism to Drive Real Change
by Ronald Cohen
Published 1 Jul 2020

Impact-weighted accounts for businesses, which dependably reflect their impact, will be the watershed between the risk–return and risk–return–impact paradigms. Investment returns from risk–return–impact will be at least as good as the returns from risk–return, and most likely better. Risk–return–impact thinking is disrupting entrepreneurship, business, investment, philanthropy and government in just as far-reaching a way as technology. The chain-reaction triggered by risk–return–impact thinking is already under way, driven by young consumers, entrepreneurs and employees. They have influenced the behavior of investors, who have joined them in influencing the behavior of businesses, philanthropists and governments.

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For outcome payers, they represent an outcomes-based contract that delivers better results and provides greater transparency on what works and what doesn’t than a conventional contract that pays for activities. SIBs and DIBs are the purest expression of risk–return– impact at work. They are part of a general shift, which is already under way, to a system whose model of decision-making introduces this new mindset of risk–return–impact, rather than risk–return. They also make us realize that the impact of social interventions can actually be measured. This realization is now spreading to the broader understanding that impact can be measured and compared across companies, transforming all decision-making that relates to them.

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As a result, SIBs reduce the volatility and improve the returns of a portfolio when the stock market takes a nosedive or interest rates soar. Because of the importance of investment flows within our economies, risk– return–impact investing puts us on the road to impact economies SIBs and DIBs also clearly demonstrate the inherent logic of risk–return–impact and that by optimizing this triple helix we can reach a higher ‘efficient frontier’, where for the same level of risk we can achieve higher returns and greater impact. Because of the importance of investment flows within our economies, risk–return–impact investing puts us on the road to impact economies, where impact influences every decision taken in investment and as a consequence, as we will see in the next chapter, in business too.

Investing Demystified: How to Invest Without Speculation and Sleepless Nights
by Lars Kroijer
Published 5 Sep 2013

We can accept the premise that market forces have set a price on individual securities and the aggregate market at a level that is consistent with the risk/return characteristics of that asset class. Because equities are riskier, we get higher expected returns, etc. For other investments left out of the rational portfolio there is typically not a liquid and efficient market to set prices for the individual investments, so someone without an edge is unable to simply buy into the whole asset class and expect to get its overall risk/return. So there is no theoretical inconsistency in being a rational investor – on the contrary. We don’t think we know any better than the market about the risk/return profiles of individual securities or how they move relative to one another.

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The beautiful shortcut – follow the crowd But here is the beautiful thing. If you generally believe in efficient markets, you don’t need to worry about the portfolio theory above or collecting millions of correlations and thousands of risk-return profiles. The market’s ‘invisible hand’ has already done all that for you. We don’t think we are able to reallocate between securities in such a way that we have a higher risk/return profile than what the aggregate knowledge of the market provides. Buying the entire market is essentially like buying the tangency point T. To some people it will seem like too bold an assumption that capital has seamlessly flowed between countries and industries in such a way that world markets are efficiently allocated.

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Investment A in the chart, therefore, consists of many thousands of underlying equities from all over the world in the portfolio (see later). By combining the minimal risk asset and A (world equities) in various proportions we choose various risk/return levels in the most efficient way, from minimal risk to the risk of the world equity markets, or greater than that if we borrow money. Point T is already the tangency point, or optimal portfolio, and we don’t think we can reallocate money between the many securities in such a way that we end up with better risk/return characteristics (see Figure 3.7). Figure 3.7 Combining the minimal risk asset and world equities Later, when we add other government and corporate bonds, we will see that this is akin to when we added the possibility of investment B earlier.

The New Science of Asset Allocation: Risk Management in a Multi-Asset World
by Thomas Schneeweis , Garry B. Crowder and Hossein Kazemi
Published 8 Mar 2010

Similarly, private equity returns and the returns of many hedge fund strategies are model driven. The message sent is clear—beware of past data and doubly beware of bad past data. Today’s market and trading environment is fundamentally different than that of even five years ago. Today, tradable ETFs exist that provide access to a wide range of investment sectors and risk/return scenarios. Tradable forms of private equity, real estate, hedge fund, managed futures, and commodity indices also exist. Moreover, the degree to which these new investment tools are offered and how they are presented to investors is often based on the business model of the firm offering the investment or investment advice.

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A REVIEW OF THE CAPITAL ASSET PRICING MODEL The model developed by Sharpe and others is known as the Capital Asset Pricing Model (CAPM). While the results of this model are based on several unrealistic assumptions, it has dominated the world of finance and asset allocation for the past 40 years. The main foundation of the CAPM is that regardless of their risk-return preference, all investors can create desirable mean-variance efficient portfolios by combining two portfolios/assets: One is a unique, highly diversified, mean-variance efficient portfolio (market portfolio) and the other is the riskless asset. By combining these two investments, investors should be able to create mean-variance efficient portfolios that match their risk preferences.

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The combination of the riskless asset and 5 A Brief History of Asset Allocation the market portfolio (the Capital Market Line [CML] as shown in Exhibit 1.2) provides a solution to the asset allocation problem in a very simple and intuitive manner: Just combine the market portfolio with riskless asset and you will create a portfolio that has optimal risk-return properties. In such a world, the risk of an individual security is then measured by its marginal contribution to the volatility (risk) of the market portfolio. This leads to the so-called CAPM: E ( Ri ) − Rf = [ E ( Rm ) − Rf ] βi βi = Corr ( Ri , Rm ) × σi σm where Rf = Return on the riskless asset E(Rm) and E(Ri) = Expected returns on the market portfolio and a security σm and σi = Standard deviations of the market portfolio and the security Corr(Ri,Rm) = Correlation between the market portfolio and the security CML Expected Return Markowitz Efficient Frontier Market Portfolio Risk-Free Rate Standard Deviation EXHIBIT 1.2 Capital Market Line 6 THE NEW SCIENCE OF ASSET ALLOCATION Expected Return SML Market Portfolio Risk-Free Rate 0 1 2 Beta EXHIBIT 1.3 Security Market Line Thus, in the world of the CAPM all the assets are theoretically located on the same straight line that passes through the point representing the market portfolio with beta equal to 1.

Commodity Trading Advisors: Risk, Performance Analysis, and Selection
by Greg N. Gregoriou , Vassilios Karavas , François-Serge Lhabitant and Fabrice Douglas Rouah
Published 23 Sep 2004

Construction of efficient frontiers with each of the pools. 3. Comparison of the efficient frontiers built with CTAs to those constructed without CTAs and determination if this hedge fund strategy adds value at the portfolio level or not in terms of risk/returns. Recall that, in a risk/return framework, the efficient frontier represents all the risk/return combinations where the risk is minimized for a specific return (or the return is maximized for a specific risk). Each minima (or maxima) is reached thanks to an optimal asset allocation. The process of constructing efficient frontiers through an asset weight optimization is summarized in this definition: For all possible target portfolio returns, find portfolio weights (i.e., asset allocation) such as the portfolio volatility is minimized and the following constraints are respected: no short sale, full investment, and weight limits if any. 316 PROGRAM EVALUATION, SELECTION, AND RETURNS Clearly, the resulting efficient frontier depends on the returns, volatility, and correlations of the considered assets, but it also depends on the constraints (maximum and minimum weight limit, no short selling, and full investment) fixed by the portfolio manager.

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Finally, the last one is made of all traditional assets and hedge funds strategies including CTAs. Whether to consider or not consider CTAs in the pools should affect the generated efficient frontiers and highlight any diversification capacity of CTAs. Concerning the portfolio optimizations, two frameworks are used: a classical two-dimensional risk-return framework and a three-dimensional one (a risk/return/time framework; the time being introduced with rolling statistics). The three-dimensional framework should capture time changes, which are rarely presented in portfolio allocation studies. Portfolio Optimization and Constraints Before being specific about CTAs, it is important to have a brief reminder of portfolio optimization and constraints.

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The range of weight goes from 0 percent (unconstrained portfolio) to 100 percent (portfolio made of a single asset). As a constraint increases, the efficient surface is reduced and tends to a single risk/return combination (100 percent allocation in a single asset). As an example, let us focus on one portfolio optimization (Figures 17.11a and b). These assumptions are applied on the pool of assets IV (15 members): no constraints, full investment, and no short sell. The optimization includes assets having the best risk/return profiles. Hedge funds strategies like global macro or the REIT equities are immediately selected, which is not the case for CTAs. CTAs are not included in any efficient portfolio construction.

The Investopedia Guide to Wall Speak: The Terms You Need to Know to Talk Like Cramer, Think Like Soros, and Buy Like Buffett
by Jack (edited By) Guinan
Published 27 Jul 2009

Related Terms: • Modified Internal Rate of Return • Risk-Return Trade-Off • U.S. Treasury • Return on Investment—ROI • Treasury Bill—T-Bill Risk-Return Trade-Off What Does Risk-Return Trade-Off Mean? The principle that potential return rises with an increase in risk. Low levels of uncertainty (low risk) are associated with low potential returns, whereas high levels of uncertainty (high risk) are associated with high potential returns. According to the risk-return trade-off, invested money can render higher profits only if it is subject to the possibility of being lost. Investopedia explains Risk-Return Trade-Off Because of the risk-return trade-off, investors must recognize their personal risk tolerance when choosing investments.

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Investopedia explains Coefficient of Variation (CV) The coefficient of variation allows investors to determine how much volatility (risk) they are assuming in relation to the amount of expected return from an investment; the lower the ratio of standard deviation to the mean return is, the better the risk-return trade-off is. Note that if the expected return in the denominator of the calculation is negative or zero, the ratio will not make sense. Related Terms: • Beta • Risk-Return Trade-Off • Volatility • Expected Return • Standard Deviation Collateral What Does Collateral Mean? Properties or assets that secure a loan or another debt. Collateral becomes subject to seizure on default.

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The risk inherent to each party to a contract that the counterparty will not live up to its contractual obligations. The Investopedia Guide to Wall Speak 55 Investopedia explains Counterparty Risk In most financial contracts, counterparty risk is known as default risk. Related Terms: • Beta • Risk-Return Trade-Off • Unsystematic Risk • Risk • Systematic Risk Coupon What Does Coupon Mean? The interest rate stated on a bond when it is issued. The coupon typically is paid semiannually. This also is referred to as the coupon rate or coupon percent rate. Investopedia explains Coupon For example, a $1,000 bond with a coupon of 7% will pay $70 a year.

Stocks for the Long Run, 4th Edition: The Definitive Guide to Financial Market Returns & Long Term Investment Strategies
by Jeremy J. Siegel
Published 18 Dec 2007

CHAPTER 2 Risk, Return, and Portfolio Allocation FIGURE 33 2–5 Risk-Return Trade-Offs for Various Holding Periods, 1802 through December 2006 curve means increasing the proportion in stocks and correspondingly reducing the proportion in bonds. As stocks are added to the all-bond portfolio, expected returns increase and risk decreases, a very desirable combination for investors. But after the minimum risk point is reached, increasing stocks will increase the return of the portfolio but only with extra risk. The slope of any point on the efficient frontier indicates the risk-return trade-off for that allocation.

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The historical correlation between the annual returns in U.S. and non-U.S. markets has been about 57 percent, which means that 57 percent of the variation in non-U.S. markets is also seen in U.S. stock returns. Using these historical data allows us to construct Figure 10-2, which shows the risk-return trade-off (called the efficient frontier) for dollar-based investors depending on varying the proportions that are invested in foreign markets (measured by the EAFE Index) and U.S. markets. The minimum risk for this world portfolio occurs when 22.5 percent is allocated to EAFE stocks and thus 77.5 percent to U.S. stocks. But the “best” risk-return portfolio, called the efficient portfolio, is not the one with the lowest risk but the one that optimally balances risk and return.

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For more information about this title, click here C O N T E N T S Foreword xv Preface xvii Acknowledgments xxi PART 1 THE VERDICT OF HISTORY Chapter 1 Stock and Bond Returns Since 1802 3 “Everybody Ought to Be Rich” 3 Financial Market Returns from 1802 5 The Long-Term Performance of Bonds 7 The End of the Gold Standard and Price Stability 9 Total Real Returns 11 Interpretation of Returns 12 Long-Term Returns 12 Short-Term Returns and Volatility 14 Real Returns on Fixed-Income Assets 14 The Fall in Fixed-Income Returns 15 The Equity Premium 16 Worldwide Equity and Bond Returns: Global Stocks for the Long Run 18 Conclusion: Stocks for the Long Run 20 Appendix 1: Stocks from 1802 to 1870 21 Appendix 2: Arithmetic and Geometric Returns 22 v vi Chapter 2 Risk, Return, and Portfolio Allocation: Why Stocks Are Less Risky Than Bonds in the Long Run 23 Measuring Risk and Return 23 Risk and Holding Period 24 Investor Returns from Market Peaks 27 Standard Measures of Risk 28 Varying Correlation between Stock and Bond Returns 30 Efficient Frontiers 32 Recommended Portfolio Allocations 34 Inflation-Indexed Bonds 35 Conclusion 36 Chapter 3 Stock Indexes: Proxies for the Market 37 Market Averages 37 The Dow Jones Averages 38 Computation of the Dow Index 39 Long-Term Trends in the Dow Jones 40 Beware the Use of Trend Lines to Predict Future Returns 41 Value-Weighted Indexes 42 Standard & Poor’s Index 42 Nasdaq Index 43 Other Stock Indexes: The Center for Research in Security Prices (CRSP) 45 Return Biases in Stock Indexes 46 Appendix: What Happened to the Original 12 Dow Industrials?

Mastering Private Equity
by Zeisberger, Claudia,Prahl, Michael,White, Bowen , Michael Prahl and Bowen White
Published 15 Jun 2017

The maturity or stage of the development has of course a distinct impact on the risk−return profile of the underlying investment: a pre-completion project requires a higher risk tolerance but offers the greatest potential for price appreciation, while an investment in mature projects provides exposure to stable, long-term cash flows.5 Leverage is typically employed at all stages of development to enhance returns, with the physical assets themselves serving as collateral. Exhibit 5.4 provides a simple overview of the two project stages (early stage and mature) and the risk−return characteristics of real estate, infrastructure and natural resources projects.

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Used together with the case book Private Equity in Action—Case Studies from Developed and Emerging Markets, which complements the text, this book brings the learning points to life and offers readers a ringside seat to the day-to-day challenges facing partners in PE and venture funds. For novices to the field of PE, our book provides clear insights into the workings of the industry. While the book assumes a sound understanding of basic finance, accounting techniques and risk–return concepts, it offers links to literature and research to ensure clarity for those rusty in the theoretical concepts behind today's financial markets. Graduate and postgraduate students will find the book an invaluable companion for their PE, venture capital and entrepreneurship courses; it will allow them to connect the dots and ensure that an understanding of the dynamics in the industry is maintained as they explore the respective chapters in greater detail.

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The larger number of portfolio companies and the high rate of failure require VCs to make tough decisions and (potentially) write off underperforming investments quickly to focus their time and resources on the most promising companies. Entrepreneurs are well advised to be aware of these dynamics before presenting their business plans to a VC fund. The risk−return dynamics of VC investing are a concern for its investors. While limited partners remain intrigued by the industry’s well-publicized winners and its fabled returns, a landmark report by the Kauffman Foundation published in 20126 raised doubts on the return contributions from venture to an institutional portfolio, implying that the risks may outweigh the strategy’s return and that LPs make decisions based on “seductive narratives like vintage year and quartile performance.”

Capital Ideas Evolving
by Peter L. Bernstein
Published 3 May 2007

Today, as in the past (and in some ways even more so than in the past), only a precious few investors have found strategies to beat the markets with any acceptable degree of consistency. Although Markowitz’s prescription for constructing portfolios requires assumptions we cannot replicate in the real world, the risk/return trade-off is central to all investment choices. Just as essential, Markowitz’s emphasis on the difference between the portfolio as a whole and its individual holdings has gained rather than lost relevance with the passage of time. The beta of the Capital Asset Pricing Model is no longer the single parameter of risk, but investors cannot afford to ignore the distinction between the risk of the expected returns of an asset class and the risk in decisions to bern_a03fpref.qxd xx 3/23/07 8:43 AM Page xx PREFACE outperform that asset class.

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CAPM derives from mean/variance estimates for only one time period; there is only one asset to worry about and value; being in the market is the only risk that is rewarded; the investor takes no risks other than the risk of being in the market; and expected return and risk are always positively correlated. “These are really extreme assumptions,” Sharpe adds. Once unshackled from CAPM’s stylized view of the real world, the investor can employ a more varied and realistic setting when making choices. State-preference theory enables us to price assets and optimize the risk/return trade-off under a wide range of possible outcomes, taking into consideration the probabilities that each outcome may occur. As a consequence, this approach could include situations where the distribution of returns differs from the bell-shaped normal distribution. As Sharpe describes this approach, it also allows investors to consider “at least a limited range of more complex preferences of the sort Danny Kahneman has talked about [or] the implications of a world in which people have disagreements about * A more complete and extended version of Sharpe’s views on these matters appears in Sharpe (2006).

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Although Scholes explicitly excludes considerations of alpha and beta in the management of his hedge fund, and although he claims the search for omega is not a zero-sum game, the roots of his strategies are still deeply imbedded in the basic structures of Capital Ideas. Risk, in all its manifestations, is the central consideration in everything his fund undertakes, and the risk/return trade-off is basic to all decisions. He makes little use of the Capital Asset Pricing Model, but assumptions of market efficiency explain why he insists the investments in his fund are not based on “mispricings” but, rather, on value created by investors seeking to shed risks by making it profitable for others to assume those risks for them.

The Smartest Investment Book You'll Ever Read: The Simple, Stress-Free Way to Reach Your Investment Goals
by Daniel R. Solin
Published 7 Nov 2006

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Reported at: http://finance. yahoo. com/ columnist/ article/ futureinvest/ 6953 Everyone wants to make as big a return as he or she can. But at what risk? The possibility of gaining a few percentage points on the upside may be dwarfed by the increase in downside risk. Take a look at the chart on page 74, which illustrates this point. 74 Your Broker or Advisor Is Keeping You from Being a Smart Im"eStor RISK RETURN COMPARISON (DitlI'Iri8l: 1911-2005) 11m _ • C*dI Yur lois AmgII AuuaJ II!ln • &1M SIKb 141M iIIJlIk ....... "" .,.. "" ... '" "' "" ,"' "" . . As you can see, if you invested in a diversified portfolio consisting of 100% stocks during the period 1977 to 2005, your average rerum would have been 1 1.7%.

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Su financial media Agrawal, Ravi, 158 Al-Sharkas, Add A., 165- 66 American Express house funds, 77, 163 a~tcla~,40, 70-72 asset allocation about ao;set allocation, 40-4 1, 70-72,121- 22 in Four-Stcp Process for Smart Investors, 119, 121-26 perfo rmance and, l I S. 137-38 resarch on, 115, 122, 162--63 website to determine. 124 See also Four-Step Process fo r Sman Investors; investment portfolios Asset Allocation Questionnaire about the questionnaire. 123--24 qucstionnaire, 171-78 Atkinson, Howard)., 127, 148-49 Atkinson, Stanley M., 159 Bachelicr, Louis, 11 1 Bajari, Patrick, 53, 157 bank wrap accounts, 65-66,16 1 Barber, Brad, 154, 157 Barclays Global Investors Canada Ltd., 106, 148 Beck, Peler, 165 Beebowcr, Gilbert L, 12 1, 162 Belsky, Gary, 67 benchmark index, 23-24 Bergstresser, Daniel B., 149- 50 Berkshire Hathaway, 108 Bernstein, William, 142, 182 Bhattacharya, Utpal. 168 Biggs, Barton, 95 Blake, Christopher R., 158 Blirzcr, David M., 105 Bodie, Zvi, 163 Bogle, John c., 48, 89, 129, 147-48,150,159--60,168, 182 Bogk on Mutual Funds (Bogle), 182 bonds abo ut bonds, 13, 7 1 as asser class, 13,40,71, 121, IG2 186 Index risk return comparison (chan), 14,74-76 bond index funds, 19 Set also iShares CON Bond Index Fund (XBS) borrowing on margin, 77-78 Bowen,JohnJ.,84 Brinson, Gary P.. 12 1. 162 brokerage firms. Sf( securities industry Buffett, Warren, 86, 108-9 for index nmds, 147 for management fees, 5, 25, 35,37,62-63,88-90, 147,159--60 for sales and trading, 25, 35- 37, 53, 59-60, 63, 115.119, 128,154 for trading online. 119 for wrap accounts, 65--66 front-load and no-load funds, 60, 63 management expense ratio Cadsby, Ted, 181 Carrick, Rob, 65, 16 1 cash, as asset class, 40, 121 Chalmers, John M.R.• 149-50 C handler, James L. , 162 charitable organi7..ations, as Smart Investors, lOG C hevreau, Jonathan, 44, 77, 93, 146 chimp Story, 3-4. 146 Clements, Jonathan. 26, 29, 93, 152 commissions.

In Pursuit of the Perfect Portfolio: The Stories, Voices, and Key Insights of the Pioneers Who Shaped the Way We Invest
by Andrew W. Lo and Stephen R. Foerster
Published 16 Aug 2021

“De Finetti Scoops Markowitz.” Journal of Investment Management 4: 5–18. ________. 2010. “God, Ants and Thomas Bayes.” American Economist 55, no. 2: 5–9. ________. 2016. Risk-Return Analysis, Vol. 2, The Theory and Practice of Rational Investing. New York: McGraw-Hill. ________. 2020. Risk-Return Analysis, Vol. 3, The Theory and Practice of Rational Investing. New York: McGraw-Hill. Markowitz, Harry M., and Kenneth Blay. 2014. Risk-Return Analysis, Vol. 1, The Theory and Practice of Rational Investing. New York: McGraw-Hill. Marschak, J. 1938. “Money and the Theory of Assets.” Econometrica 6, no. 4: 311–25. ________. 1946.

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In what, in retrospect, can be described as a tremendous understatement, Markowitz noted that “the calculation of efficient surfaces might possibly be of practical use.”45 Once an efficient set of portfolios could be determined, then investors might state the preferred portfolio for their desired risk-return combination. Markowitz was quick to point out that in order to be of practical use, two broad conditions first needed to apply. First, investors had to act “according to the E-V maxim.”46 In other words, investors needed to find higher expected returns more desirable, the “E” of the E-V maxim, while at the same time finding more variance (or variability) less desirable, the “V” of the E-V maxim, and only consider these two factors.

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“The way I see things going in the next sixty years … is for the human-computer division of labor to cover more fully the various aspects of financial planning.”107 To that end, having laid the foundation in his first and second volumes, Markowitz recently completed the third volume of a projected four-volume series titled Risk-Return Analysis: The Theory and Practice of Rational Investing.108 These books expand on the analysis Markowitz first presented in his 1959 book, justifying the use of mean-variance analysis as a rational approach to decision making under uncertainty. According to Markowitz, despite its title, the series is “not about rational investing, it’s about rational decision making for financial planning.”109 Markowitz noted that portfolio selection needs to be considered in a broad context: “Just analyzing the portfolio selection decision in isolation is like trying to decide how bishops should move in a chess game without considering the chess game as a whole.”

Beyond Diversification: What Every Investor Needs to Know About Asset Allocation
by Sebastien Page
Published 4 Nov 2020

To further illustrate the power of diversification between covered call writing and managed volatility, Stefan estimated returns, volatilities, downside risk, and relative performance statistics for the stand-alone and combined strategies. Based on data from January 1996 to December 2015, the risk-return ratio of the S&P 500 is 0.41. When combined with the covered call writing strategy (with gross exposure capped at 125%), the S&P 500’s risk-return ratio increases from 0.41 to 0.49, while downside risk is only marginally reduced. But when we add managed volatility, the risk-return ratio jumps from 0.49 to 0.69 (even though the stand-alone managed volatility strategy had a relatively low risk-return ratio of 0.17), and downside risk is reduced substantially. Takeaways and Q&A To summarize, volatility has been shown to be persistent, and in the short run, it has not been predictive of returns.

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Their betas are all that matter.17 From that perspective, CAPM forecasts are most relevant for long investment horizons, say, over 10 years. They’re useful as inputs for life cycle investing applications, for example. Also, CAPM results can indicate whether valuation spreads, relative to long-term averages or between asset classes, may be transitory or permanent. All else being equal, the further away valuations are from their risk-return “CAPM equilibrium,” the greater the gravitational pull of mean reversion. But there’s another issue I should emphasize: the betas are just statistical estimates produced by a risk model. They’re not very forward-looking. In Table 1.1, non-US small caps have a lower beta than non-US large caps.

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For unhedged international bonds, correlation peaks at 57% at 0.5 duration (here the effect of currency risk muddies the water). Harvey and Stonacek conclude that “current yields are most highly correlated with future returns for higher-quality and hedged bond indexes. As these indexes follow stricter maturity, duration, and quality rules, they present a more stable risk/return profile than unhedged and lower quality indexes.” For equity asset classes, even a 57% correlation between a simple, publicly available indicator and subsequent returns would be remarkable. Yet some of the fiercest debates I’ve witnessed on expected returns have been between bond quants, on how to account for minute details that may or may not improve the forecast.

The Handbook of Personal Wealth Management
by Reuvid, Jonathan.
Published 30 Oct 2011

ឣ 84 REAL ESTATE AND FORESTRY ______________________________________________ Larger-scale investors who are content to place themselves in a limited geography and to move a bit further up the risk–return spectrum can consider a direct forest purchase, managed by an experienced forestry management company. It is essential to obtain good value upon purchase at the outset; efficient sourcing and due diligence on properties are required. Risk–return profiles of forestry investments The typical returns from forestry investments in mature forestry markets, such as the United States or Australasia, have been estimated since the early 2000s to be in a typical range of 6 to 7 per cent per annum after inflation and before tax.

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66 2.2 The overseas property market in the economic downturn James Price, Knight Frank LLP A ‘nice to have’ 69; Markets within the market 69; Which buyers are most active? 73; Outlook 74 2.3 Current opportunities in forestry investment Alan Guy and Alastair Sandels, Fountains Plc Introduction 79; The nature of the forestry asset class 79; Special qualities of forestry investment 80; Types of investment in the forestry asset class 82; Risk–return profiles of forestry investments 84; New revenue sources from forestry 85; Summary 85 2.4 Risks and direct investment in forestry Alan Guy and Alastair Sandels, Fountains Plc Risks in forestry investment 87; Direct investment 89; How UK and US forestry has performed in recent years 91; Tax treatment of forestry in the UK and United States 92; Summary 92 2.5 Timber investments in South-East Asia Guy Conroy, Oxigen Investments An ethical way to watch your money grow 94; Timber outperforms the stock market 96; Sri Lanka: the natural forest 97; Malaysia: ideal for teak 98; The science of trees 99; Agroforestry: a new ethical investment 100; What investors want to know 101; Can the experts all be wrong?

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No matter how complex the concluding-solution set of investment answers is, that set is effectively meaningless to the client if the underlying inputs are questionable. Effective wealth managers appreciate the importance of this. Most ‘optimal’ outputs incorporate a degree of quantitative science. Such approaches typically embed a series of risk, return and correlation assumptions (and may also incorporate a confidence function). By means of a presumed optimization methodology, a mix of asset classes can be identified that matches an investor’s profile and steers him or her on a path to achieving investment objectives. Since the development of modern portfolio theory, analysts have questioned the validity of certain portfolio approaches.

High-Frequency Trading: A Practical Guide to Algorithmic Strategies and Trading Systems
by Irene Aldridge
Published 1 Dec 2009

High-frequency strategies focus on the most liquid securities; a security requiring a holding period of 10 minutes may not be able to find a timely counterparty in illiquid markets. While longer-horizon investors can work with either liquid or illiquid securities, Amihud and Mendelson (1986) show that longer-horizon investors optimally hold less liquid assets. According to these authors, the key issue is the risk/return consideration; longer-term A 37 38 HIGH-FREQUENCY TRADING investors (already impervious to the adverse short-term market moves) will obtain higher average gains by taking on more risk in less liquid investments. According to Bervas (2006), a perfectly liquid market is the one where the quoted bid or ask price can be achieved irrespective of the quantities traded.

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The discipline of portfolio optimization originated from the seminal work of Markowitz (1952). The two dimensions of a portfolio that he reviewed are the average return and risk of the individual securities that compose the portfolio and of the portfolio as a whole. Optimization is conducted by constructing an “efficient frontier,” a set of optimal risk-return portfolio combinations for the various instruments under consideration. In the absence of leveraging opportunities (opportunities to borrow and increase the total capital available as well as opportunities to lend to facilitate leverage of others), the efficient frontier is constructed as follows: 1.

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For every possible combination of security allocations, the risk and return are plotted on a two-dimensional chart, as shown in Figure 14.1. Due to the quadratic nature of the risk function, the resulting chart takes the form of a hyperbola. Return Risk FIGURE 14.1 Graphical representation of the risk-return optimization constructed in the absence of leveraging opportunities. The bold line indicates the efficient frontier. 203 Creating and Managing Portfolios of High-Frequency Strategies 2. The points with the highest level of return for every given level of risk are selected as the efficient frontier.

The Intelligent Asset Allocator: How to Build Your Portfolio to Maximize Returns and Minimize Risk
by William J. Bernstein
Published 12 Oct 2000

Unfortunately, the above examples are no more than useful illustrations of the theoretical benefits of diversified portfolios. In the real world of investing, we must deal with mixes of dozens of asset types, each with a different return and risk. Even worse, the returns of these assets are only rarely completely uncorrelated. Worse still, the risks, returns, and correlations of these assets fluctuate considerably over time. In order to understand real portfolios, we shall require much more complex techniques. Thus far we have dealt with portfolios with only two uncorrelated components. Two uncorrelated assets may be represented with four time periods as in Uncle Fred’s coin toss, three assets with eight periods, four assets with 16 periods, etc.

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A recurring theme in these pages is that you try as hard as you can to identify the diverse strains of current financial wisdom in order that you may ignore them. Now that we’ve ascertained that the popular view of international diversification has been poisoned by the recent poor performance of foreign stocks, what does the “complete” data show? Figure 4-5 is the risk-return plot for the full 30-year period from 1969 to 1998. For this period the returns for the S&P (12.67%) and EAFE (12.39%) were nearly identical. Note also how narrowly spaced the return values on the y axis are, with less than 1% separating all of the portfolio returns. The Behavior of Real-World Portfolios 49 Note how “bulgy” this plot is.

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We are looking at recency again— our tendency to overemphasize recent events. However, no one questions that small stocks are more risky than large stocks. In Figure 4 -7, I’ve plotted various mixes of small and large stocks with the ubiquitous five-year Treasury notes. First, note that the two plots nearly overlap. In other words, the risk-return curves are very Figure 4-7. Large and small stocks/bonds, 1926–1998. 54 The Intelligent Asset Allocator similar, except that the small-stock curve extends out a lot farther to the right than the S&P curve. In the present graph, large stock and bond mixes appear to be slightly more efficient than small stock and bond mixes.

The Four Pillars of Investing: Lessons for Building a Winning Portfolio
by William J. Bernstein
Published 26 Apr 2002

Value of $1.00 invested in stocks, bonds, and bills, 1901–2000 (semilogarithmic scale). (Source: Jeremy Siegel.) Risk—The Second Dimension The study of investment returns is only half of the story. Distilled to its essence, investing is about earning a return in exchange for shouldering risk. Return is by far the easiest half, because it is simple to define and calculate, either as “total returns”—the end values in Figures 1-7 and 1-8, or as “annualized returns”—the hypothetical gain you’d have to earn each year to reach that value. Risk is a much harder thing to define and measure. It comes in two flavors: short-term and long-term.

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But these are the winning lottery tickets in the growth stock sweepstakes. For every growth stock with high returns, there are a dozen that, within a very brief time, disappointed the market with lower-than-expected earnings growth and were consequently taken out and shot. Summing Up: The Historical Record on Risk/Return I’ve previously summarized the returns and risks of the major U.S. stock and bond classes over the twentieth century in Table 1-1. In Figure 1-19, I’ve plotted these data. Figure 1-19 shows a clear-cut relationship between risk and return. Some may object to the magnitude of the risks I’ve shown for stocks.

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That is not to say that your return requirements are immaterial. For example, if you have saved a large amount for retirement and do not plan to leave a large estate for your heirs or to charity, you may require a very low return to meet your ongoing financial needs. In that case, there would be little sense in choosing a high risk/return mix, no matter how great your risk tolerance. Figure 4-6. Portfolio risk versus return of bill/stock mixes, 1901–2000. There’s another factor to consider here as well, and that’s the probability that stock returns may be lower in the future than they have been in the past. The slope of the portfolio curve in Figure 4-6 is steep—in other words, in the twentieth century, there was a generous reward for bearing additional portfolio risk.

Efficiently Inefficient: How Smart Money Invests and Market Prices Are Determined
by Lasse Heje Pedersen
Published 12 Apr 2015

When done carefully, portfolio optimization provides a tool to reap the full benefits of diversification, to efficiently exploit high-conviction trades without excessive concentration, to systematically adjust positions based on the time-varying risk and expected return, and to minimize subjectivity in the portfolio choice. In summary, good portfolio construction techniques can help achieve a favorable risk-return profile for a set of trading ideas. A systematic approach helps reduce a trader’s own behavioral biases, that is, his tendencies to make certain mistakes. For instance, people like to hang on to their losing positions even if the reason they liked the securities no longer applies, and they like to sell winners to lock in gains even if the trade has gotten even better. 4.2.

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LA: It’s purely driven by the discipline of making sure our portfolio is always focused on the opportunities we judge to be the most attractive. In the utopian world, every single day we would consider the return we think we can achieve in every one of our positions, how much risk we need to take to achieve that return, and how that risk-return profile compares to every other investment opportunity that we have. So if something is being bought or sold, that typically means we have concluded that another investment is more attractive at that point in time than a current investment. Of course, this is all easier in theory than in practice, but that’s our mindset.

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A significant portion of the capital invested in the markets is invested in a manner that is very aligned with the relevant weightings to an index, typically on a cap-weighted basis. At Maverick, we are blissfully ignorant of a particular stock’s or sector’s weighting in any index—all we care about is the attractiveness of an investment on a risk-return basis. Last but not least, I think stability has been a big advantage for us over the years. We’ve enjoyed stability of both our investment team and our investor base, which really does allow us to invest with a longer term horizon. The vast majority of the capital we manage is attributable to profits we have generated for our investors, and most of the capital we manage has been invested in Maverick for more than ten years.

The Power of Passive Investing: More Wealth With Less Work
by Richard A. Ferri
Published 4 Nov 2010

See American Stock Exchange (Amex) AQR Capital Management Art of Selling Intangibles, The (Gross) Asness, Cliff Assessments Asset allocation strategy: in 5-step process active asset classes and individual investors and for an IPS market conditions and passive risk/return assessment in strategic tactical Asset class: long-term expected risk/returns non-core asset classes volatility of Assets under management (AUM) AUM. See Assets under management (AUM) Bad accounting Banz, Rolf Barclays Capital Aggregate Bond Index Barra Inc. Basu, Sanjoy Batterymarch Financial Management Beardstown Ladies, the Bear market: advisors and endowment effect and market timing gaps and policy changes and risk and Beat-the-market advice Behavioral finance Benchmarking, improper Benchmark(s): buying defining good definition of identification of proper index funds and strategy index products and Benchmarks and Investment Management (Siegel) Benefits, passive index investing Berkshire Hathaway Inc.

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The objective of portfolio management is to create and follow an investment policy that provides the resources required to meet current and future obligations. At its core, the portfolio management process relies on a prudent mix of asset classes that’s based on research and reasonable assumptions about future risks, returns, and correlation with each other. Strict adherence to an asset allocation strategy is required for the investment policy to have its desired effect and avoid unwanted drift. This requires the regular monitoring of asset class levels since the markets are constantly moving. Occasional rebalancing back to the target asset allocation ensures that the portfolio stays on track.

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Fiduciary 360 and its affiliate the Foundation for Fiduciary Studies are two of many private organizations dedicated to investment fiduciary education, practice management, and support. These organizations have identified similar characteristics of both model acts. There are seven Global Fiduciary Precepts.1 1. Know standards, laws, and trust provisions. 2. Diversify assets to specific risk/return profile of the trust. 3. Prepare investment policy statement. 4. Use prudent experts (for example, an investment advisor) and document due diligence when selecting experts. 5. Monitor the activity of the prudent experts. 6. Control and account for investment expenses. 7. Avoid conflicts of interests and prohibited transactions.

Beyond the Random Walk: A Guide to Stock Market Anomalies and Low Risk Investing
by Vijay Singal
Published 15 Jun 2004

While market efficiency is desirable, there are three limitations in achieving that ideal: the cost of information, the cost of trading, and the limits of arbitrage. Strictly speaking, arbitrage refers to a profit earned with zero risk and zero investment. However, in this book the term is used in its more popular interpretation, that is, a superior risk-return trade-off that probably requires both risk and investment. LIMITATION 1: COST OF INFORMATION In an article aptly titled “On the Impossibility of Informationally Efficient Markets,” Sandy Grossman and Joe Stiglitz go about proving just that. The concept behind the impossibility of informationally efficient markets is straightforward.

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The idea is that financial assets are perfect substitutes for one another, and the market is huge. Any single supply or demand shock is small compared to the overall size of the market. And since financial assets are perfect substitutes, excess demand for a stock will be met by arbitrageurs. They will short-sell that stock, increasing its supply, and will buy another stock with equivalent risk-return characteristics. In such an event, any price change will be imperceptible. However, as reported in the previous section, there is a permanent 169 170 Beyond the Random Walk price impact. If there is no new information associated with index changes, then the only reason for the price impact is that financial assets do not have perfect substitutes.

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Bottom Line Merger arbitrage can generate continuous and sustainable abnormal returns of 4–10 percent annually. Evidence relating to the profitability of merger arbitrage is long-term and consistent. Mutual funds specializing in merger arbitrage are a convenient way to earn a reasonable yet low-risk return. Stocks can be used to execute merger arbitrage transactions on an individual basis to possibly generate higher returns. Internet References Mutual Funds Specializing in Merger Arbitrage http://www.gabelli.com/funds/products/408.html: The site for Gabelli’s ABC Fund (GABCX). http://www.thearbfund.com: The site for the Arb Fund (ARBFX). http://www.enterprisefunds.com/funds/sector/ mergers_and_acquisitions.shtml: The site for Enterprise M&A Fund (EMACX).

The Rise of the Quants: Marschak, Sharpe, Black, Scholes and Merton
by Colin Read
Published 16 Jul 2012

Tobin’s insight was to offer investors the opportunity to include in their portfolio a riskless asset or any combination of the optimal security portfolio and the riskless asset. From this framework, an investor is offered a range of investment opportunities that each yield the best possible return for any level of risk, according to each investor’s risk return preferences. While the model assumes that all would require a greater return to take on greater risk, some investors may nonetheless reside at a low level of risk and return, while others may accept a higher combination of risk and return. These qualities can be superimposed on the Markowitz bullet and the capital allocation line.

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This approach shares obvious implications with the efficient market hypothesis, as the next volume of this series will describe. In essence, investment in a given security becomes somewhat irrelevant, then, if each security is priced efficiently according to its risk. A risk-free asset and any single asset can then provide any risk-return trade-off if both long and short positions are permitted. The need for a broader market portfolio is obviated. Weaknesses with the CAPM model A model based on the mean and variance approach is accurate only if we accept a number of restrictive assumptions. First, we must assume asset returns are normally distributed or, more generally, elliptically distributed.

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The short selling of high beta stocks should then allow the purchase of the low beta stocks, with some profit left over and with very little or, ideally, zero risk. This higher risk-free return could then be used to buy and sell along a Markowitz security line with a higher risk-free return intercept. An investor could then earn a superior risk-return trade-off for any level of desired risk through leverage purchases of the market portfolio. Their clients at Wells Fargo thought the Fischer-Scholes intuition was like financial alchemy that somehow denied the by then in vogue and widely accepted efficient market hypothesis. The firm’s rejection of their insights elicited the same reaction from Black as any such rejection had had on him since adolescence – it made him believe his hypothesis with even greater fervor.

Understanding Asset Allocation: An Intuitive Approach to Maximizing Your Portfolio
by Victor A. Canto
Published 2 Jan 2005

An increased equity exposure is the way the firm moved along the expected returns and the risk/return tradeoff ’s volatility. There were two components to this. First, as the firm moved from the conservative portfolio to the growth portfolio, it increased the equity exposure within each region without affecting the global allocation. Second, it increased the riskier assets’ exposure with the highest expected returns at the equity region’s expense with the lowest expected return. Increased uncertainty reduced the firm’s allocation to variables with the greatest expected returns. The greaterexpected-returns dispersion forced the firm’s risk/return tradeoff to mute increases in equities and regional exposures for all the portfolios.

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An efficient portfolio is a portfolio that contains returns that have been maximized in relation to the risk level that individual investors desire. In a market that is in equilibrium, where the number of winners and losers must balance out, adding one additional asset class or stock does not increase the portfolio’s risk return ratio. This means the portfolio containing risky assets with the highest Sharpe ratio must be the market portfolio. Asset Allocation and Retirement Will efficiency do the trick over the long haul? Do modern advancements in the financial world guarantee that the returns to an investment plan or portfolio are going to be high enough to generate sufficient funds to meet future obligations?

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The first step uses the asset classes’ historical returns and the variance–covariance matrix to build a combination of the various asset classes that leads one to the efficient frontier. This step also leads an investor to the point where maximum expected returns are reached for a determined risk level. The second step determines risk tolerance so an investor can choose the risk/return combination best suiting his or her preferences. I have two major objections to this process as it is currently practiced. The first objection is simply empirical: How long of a historical sample does one need to determine long-run historical returns and the variance–covariance matrix? In earlier chapters, I used traditional asset-allocation tools to decide whether individual asset classes—Treasury bonds (T-bonds), small-caps, large-caps, value stocks, growth stocks, and domestic/international stocks—would be included on the efficient frontier and thus be potentially included in an investor portfolio.

Risk Management in Trading
by Davis Edwards
Published 10 Jul 2014

To a trader that is limited by the amount of volatility rather than capital, this allows traders to improve their profits by 15 percent. (See Figure 3.12, Risk/Return.) 80 RISK MANAGEMENT IN TRADING 16.0% 100% Asset 1 Expected Return 15.0% 14.0% 13.0% 12.0% 11.0% 10.0% 100% Asset 2 9.0% 4.0% 4.5% 5.0% 5.5% 6.0% 7.0% 6.5% 7.5% 8.0% Portfolio Volatility Asset 1 Asset 2 FIGURE 3.11 Expected return (μ) Volatility (σ) Correlation (ρ) 15.0% 10.0% 7.5% 5.0% 50% Asset Allocation 2.35 k/R ew ard 2.25 2.20 Ris 2.15 tim al 2.10 2.05 Op Average Return / Volatility 2.30 2.00 1.95 1.90 1.85 Weight of Asset 1 FIGURE 3.12 Risk/Return 0% 10 0. .0 % 90 .0 % 80 % 70 .0 60 .0 % 50 .0 % .0 % 40 0% 30

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The business of trading for profit, called speculation, might be defined as “assuming substantial investment risk to obtain a commensurate profit”. This is very different than gambling, which might be defined “playing a game where the results depend on luck rather than player skill”. Risk management can help identify situations that have a better than average risk/ return relationship. This can improve the profitability of a hedge fund and differentiate a hedge fund from its peers. While risk management is often mathematical, it still requires good judgment to be effective. An often‐repeated maxim at hedge funds is that the best way to avoid trading losses is to make smart trading decisions.

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However, those rules are seldom useful for identifying opportunities in the future. Historical testing also has a selection bias because of the strong relationship between risk and return. The best trading strategies typically demonstrate consistent good performance with very low risk. In other words, successful trading strategies have a better risk/return relationship than other investments. However, because these strategies aren’t taking on the most risk, they are seldom the most profitable strategies. Typically the topperforming investment in any given historical period is a very risky investment that happened to get lucky. The selection of a strategy that maximizes the profits for one period without making them apply to other periods is called curve fitting g or over-fitting. g KEY CONCEPT: SIMULATION ACCURACY Past performance does not necessarily guarantee future returns!

Two and Twenty: How the Masters of Private Equity Always Win
by Sachin Khajuria
Published 13 Jun 2022

It comes down to a set of characteristics that can be based on both natural aptitude and learned experience: the willingness to embrace and investigate the unknown, or even chaos—or at least the absence of identifiable order; the drive to develop and execute a logical plan to understand whether a sector is suitable for investment, and how to structure that investment to achieve the best risk/return; the humility to admit what you do not know, to clarify what you need to believe about a deal in order to commit investors’ money to it—and to own up to error and try to fix mistakes; the insatiable appetite to find a good business and figure out how to make it even better; the understanding of whether the changes a business needs to be successful are realistic and achievable, regardless of whether they are difficult; the mix of patience and intellectual curiosity to dig for data to analyze and the conviction to base decisions to create value on that data and your judgment; the emotional intelligence and empathy to realize that the folks who are going to do the hardest work to create value during the life of an investment are on the shop floor—the management and employees of a business—and how to identify and partner with them.

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In our sketch, the Firm takes an enormous risk (with its investors’ capital) to turn Charlie’s fortunes around, at short notice, shoring up employment for thousands and giving a historic brand a new lease on life, at a time when the threat of bankruptcy was genuine. In real life, there are thousands of examples like this one every year, where private capital examines the risk/return trade-off for enterprises that might be on their knees and have nowhere else to go. Public markets may not contribute a dime. Governments may turn a blind eye. Nobody else might care, partly because traditional sources of capital prefer safer, less complex bets. When others flee, private equity steps in—and steps up.

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Some weaknesses in a deal can be resolved by improving governance rights; others might need part of the investment structure to change—for example, changing the perimeter of assets to be acquired or financed to make for a better deal. At today’s investment committee meeting at the Firm, two contrasting opportunities are under consideration: They are different in sector, geography, and risk/return—but similar in terms of how the Firm approaches them. Over the course of three hours, the committee debates searing questions in a dynamic dialog designed to peel back each of the proposed deals to their most truthful essence—and to try to put investors’ money to work. Let’s put ourselves in the boardroom to witness these billions of dollars on the move

Asset and Risk Management: Risk Oriented Finance
by Louis Esch , Robert Kieffer and Thierry Lopez
Published 28 Nov 2005

xix xix xxi PART I THE MASSIVE CHANGES IN THE WORLD OF FINANCE Introduction 1 The Regulatory Context 1.1 Precautionary surveillance 1.2 The Basle Committee 1.2.1 General information 1.2.2 Basle II and the philosophy of operational risk 1.3 Accounting standards 1.3.1 Standard-setting organisations 1.3.2 The IASB 2 Changes in Financial Risk Management 2.1 Definitions 2.1.1 Typology of risks 2.1.2 Risk management methodology 2.2 Changes in financial risk management 2.2.1 Towards an integrated risk management 2.2.2 The ‘cost’ of risk management 2.3 A new risk-return world 2.3.1 Towards a minimisation of risk for an anticipated return 2.3.2 Theoretical formalisation 1 2 3 3 3 3 5 9 9 9 11 11 11 19 21 21 25 26 26 26 vi Contents PART II EVALUATING FINANCIAL ASSETS Introduction 3 4 29 30 Equities 3.1 The basics 3.1.1 Return and risk 3.1.2 Market efficiency 3.1.3 Equity valuation models 3.2 Portfolio diversification and management 3.2.1 Principles of diversification 3.2.2 Diversification and portfolio size 3.2.3 Markowitz model and critical line algorithm 3.2.4 Sharpe’s simple index model 3.2.5 Model with risk-free security 3.2.6 The Elton, Gruber and Padberg method of portfolio management 3.2.7 Utility theory and optimal portfolio selection 3.2.8 The market model 3.3 Model of financial asset equilibrium and applications 3.3.1 Capital asset pricing model 3.3.2 Arbitrage pricing theory 3.3.3 Performance evaluation 3.3.4 Equity portfolio management strategies 3.4 Equity dynamic models 3.4.1 Deterministic models 3.4.2 Stochastic models 35 35 35 44 48 51 51 55 56 69 75 79 85 91 93 93 97 99 103 108 108 109 Bonds 4.1 Characteristics and valuation 4.1.1 Definitions 4.1.2 Return on bonds 4.1.3 Valuing a bond 4.2 Bonds and financial risk 4.2.1 Sources of risk 4.2.2 Duration 4.2.3 Convexity 4.3 Deterministic structure of interest rates 4.3.1 Yield curves 4.3.2 Static interest rate structure 4.3.3 Dynamic interest rate structure 4.3.4 Deterministic model and stochastic model 4.4 Bond portfolio management strategies 4.4.1 Passive strategy: immunisation 4.4.2 Active strategy 4.5 Stochastic bond dynamic models 4.5.1 Arbitrage models with one state variable 4.5.2 The Vasicek model 115 115 115 116 119 119 119 121 127 129 129 130 132 134 135 135 137 138 139 142 Contents 4.5.3 The Cox, Ingersoll and Ross model 4.5.4 Stochastic duration 5 Options 5.1 Definitions 5.1.1 Characteristics 5.1.2 Use 5.2 Value of an option 5.2.1 Intrinsic value and time value 5.2.2 Volatility 5.2.3 Sensitivity parameters 5.2.4 General properties 5.3 Valuation models 5.3.1 Binomial model for equity options 5.3.2 Black and Scholes model for equity options 5.3.3 Other models of valuation 5.4 Strategies on options 5.4.1 Simple strategies 5.4.2 More complex strategies PART III GENERAL THEORY OF VaR Introduction vii 145 147 149 149 149 150 153 153 154 155 157 160 162 168 174 175 175 175 179 180 6 Theory of VaR 6.1 The concept of ‘risk per share’ 6.1.1 Standard measurement of risk linked to financial products 6.1.2 Problems with these approaches to risk 6.1.3 Generalising the concept of ‘risk’ 6.2 VaR for a single asset 6.2.1 Value at Risk 6.2.2 Case of a normal distribution 6.3 VaR for a portfolio 6.3.1 General results 6.3.2 Components of the VaR of a portfolio 6.3.3 Incremental VaR 181 181 181 181 184 185 185 188 190 190 193 195 7 VaR Estimation Techniques 7.1 General questions in estimating VaR 7.1.1 The problem of estimation 7.1.2 Typology of estimation methods 7.2 Estimated variance–covariance matrix method 7.2.1 Identifying cash flows in financial assets 7.2.2 Mapping cashflows with standard maturity dates 7.2.3 Calculating VaR 7.3 Monte Carlo simulation 7.3.1 The Monte Carlo method and probability theory 7.3.2 Estimation method 199 199 199 200 202 203 205 209 216 216 218 viii Contents 7.4 Historical simulation 7.4.1 Basic methodology 7.4.2 The contribution of extreme value theory 7.5 Advantages and drawbacks 7.5.1 The theoretical viewpoint 7.5.2 The practical viewpoint 7.5.3 Synthesis 8 Setting Up a VaR Methodology 8.1 Putting together the database 8.1.1 Which data should be chosen?

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. • Direct costs (the capital needed to be exposed to the threefold surface of market, credit and operational risk is reduced). The promotion of a real risk culture increases the stability and quality of profits, and therefore improves the competitive quality of the institution and ensures that it will last. 2.3 A NEW RISK-RETURN WORLD 2.3.1 Towards a minimisation of risk for an anticipated return Assessing the risk from the investor’s point of view produces a paradox: • On one hand, taking the risk is the only way of making the money. In other terms, the investor is looking for the risk premium that corresponds to his degree of aversion to risk. • On the other hand, however, although accepting the ‘risk premium’ represents profit first and foremost, it also unfortunately represents potential loss.

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One of the most detailed analyses is that carried out by Fama and Macbeth,42 which, considering the relation Ek = RF + βk (EM − RF ) as an expression of Ek according to βk , tested the following hypotheses on the New York Stock Exchange (Figure 3.27): • The relation Ek = f (βk ) is linear and increasing. • βk is a complete measurement of the risk of the equity (k) on the market; in other words, the specific risk σε2k is not a significant explanation of Ek . 42 Fama E. and Macbeth J., Risk, return and equilibrium: empirical tests, Journal of Political Economy, Vol. 71, No. 1, 1974, pp. 606–36. Equities 97 Ek EM RF 1 bk Figure 3.27 CAPM test To do this, they used generalisations of the equation Ek = f (βk ), including powers of βk of a degree greater than 1 and a term that takes the specific risk into consideration.

How I Became a Quant: Insights From 25 of Wall Street's Elite
by Richard R. Lindsey and Barry Schachter
Published 30 Jun 2007

Operating at a high level of abstraction makes it easy to switch to a different manifestation of the mathematics, and to think about finance problems in the broadest possible terms. After thinking about infinite universes, it’s easy to deal with the most abstract elements of finance. Around this time, my responsibilities at BARRA expanded beyond bonds. I began working on a project to apply these ideas of risk, return, and cost to equity trading. The portfolio manager trades off these three components, deciding which stocks to buy and sell to optimize the portfolio. The trader has a different problem. The portfolio manager provides the trader with the list of stocks to buy and sell. The trader must decide how to optimally schedule those trades (i.e., how much of each stock to trade each day).

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As such, it evolved into a multiyear, multiman-year effort to develop the required component models and combine them. It provided me yet another opportunity to JWPR007-Lindsey 42 May 7, 2007 16:30 h ow i b e cam e a quant expand my sphere of knowledge well beyond that original interest rate option model. It also provided further evidence that the risk, return, and cost framework applied very generally to problems in finance. Active Portfolio Management In 1990, Richard Grinold offered an internal course at BARRA, combining academic theories and seminar presentations to sketch out a scientific approach to active management. Richard’s goal was to turn this into a book, and he offered the course as a way to make progress in that direction.

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The reported returns of these asset classes were based on appraisals and matrix pricing rather than market transactions; hence, they displayed artificially low volatility. When these asset classes were introduced to the optimizer it indicated that most of the portfolio should be allocated to them. Moreover, it showed that such an extreme allocation would substantially improve the risk/return trade-off. My conjecture is that critics of optimization latched on to this result to hype the sensitivity of optimizers to input errors. Of course, informed users of optimization understand the problem and employ a variety of methods to adjust the volatility assumptions appropriately, and thereby obtain reasonable results.

Stocks for the Long Run 5/E: the Definitive Guide to Financial Market Returns & Long-Term Investment Strategies
by Jeremy Siegel
Published 7 Jan 2014

Conclusion PART II THE VERDICT OF HISTORY Chapter 5 Stock and Bond Returns Since 1802 Financial Market Data from 1802 to the Present Total Asset Returns The Long-Term Performance of Bonds Gold, the Dollar, and Inflation Total Real Returns Real Returns on Fixed-Income Assets The Continuing Decline in Fixed-Income Returns The Equity Premium Worldwide Equity and Bond Returns Conclusion: Stocks for the Long Run Appendix 1: Stocks from 1802 to 1870 Chapter 6 Risk, Return, and Portfolio Allocation Why Stocks Are Less Risky Than Bonds in the Long Run Measuring Risk and Return Risk and Holding Period Standard Measures of Risk Varying Correlation Between Stock and Bond Returns Efficient Frontiers Conclusion Chapter 7 Stock Indexes Proxies for the Market Market Averages The Dow Jones Averages Computation of the Dow Index Long-Term Trends in the Dow Jones Industrial Average Beware the Use of Trendlines to Predict Future Returns Value-Weighted Indexes Standard & Poor’s Index Nasdaq Index Other Stock Indexes: The Center for Research in Security Prices Return Biases in Stock Indexes Appendix: What Happened to the Original 12 Dow Industrials?

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One of the first large nonfinancial ventures was the Delaware and Hudson Canal, issued in 1825, which also became an original member of the Dow Jones Industrial Average 60 years later.22 In 1830, the first railroad, the Mohawk and Hudson, was listed; and for the next 50 years, railroads dominated trading on the major exchanges. 6 * * * Risk, Return, and Portfolio Allocation Why Stocks Are Less Risky Than Bonds in the Long Run As a matter of fact, what investment can we find which offers real fixity or certainty income? ... As every reader of this book will clearly see, the man or woman who invests in bonds is speculating in the general level of prices, or the purchasing power of money.

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EFFICIENT FRONTIERS5 Modern portfolio theory describes how investors may alter the risk and return of a portfolio by changing the mix between assets. Figure 6-4 displays the risks and returns that result from varying the proportion of stocks and bonds in a portfolio over various holding periods ranging from 1 to 30 years based on 210 years of historical data. FIGURE 6-4 Risk-Return Tradeoffs (Efficient Frontiers) for Stocks and Bonds Over Various Holding Period 1802–2012 The “blank” square at the bottom of each curve represents the risk and return of an all-bond portfolio, while the darkened square at the top of the curve represents the risk and return of an all-stock portfolio.

Investing Amid Low Expected Returns: Making the Most When Markets Offer the Least
by Antti Ilmanen
Published 24 Feb 2022

As discussed, the optimizer may need to incorporate important considerations beyond mean and variance, such as ESG, illiquidity, or leverage. Just as importantly, the investors must ask if the total (asset) portfolio is what they care about. Perhaps the optimization problem is narrower (active risk budgeting or benchmark-relative optimization uses MVO on the active risk/return trade-off across strategies) or broader (surplus optimization uses MVO on the asset-liability surplus risk/return trade-off). One branch of literature considers the merits and pitfalls of two-stage optimization in delegated or decentralized asset management (see Sharpe (1981), Blake et al. (2013)). The asset owner makes asset class allocations and then gives mandates to active managers within each asset class (or within an even more granular regional or style box).

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—Yu (Ben) Meng, Chair of Asia Pacific of Franklin Templeton and former CIO of CalPERS “Antti provides a vital update to the canonical toolkit he presented in Expected Returns. The new book has even broader coverage, yet is more succinct. Investors who read this book will leave with a straightforward risk-return framework, a well-considered set of investment beliefs, a list of bad habits to avoid, and empirically good practices to follow. This book is the foundation of solid portfolio management for institutional and retail investors.” —Larry Swedroe, Chief Research Officer, Buckingham Wealth Partners Investing Amid Low Expected Returns Making the Most When Markets Offer the Least Antti Ilmanen Copyright © 2022 by Antti Ilmanen.

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For example, they may limit institutional risk taking in a low return world, thereby virtually ensuring that institutions will fail to reach their long-term goals (while maybe protecting them against even worse failures). 13.2. Techniques for Managing Investment Risk Risk management is not the same as risk minimization. Given any risk/return trade-off, risks need to be embraced at least to some extent. Yet, investors should try to measure and manage the key risks they face, and especially aspire to protect against risks that threaten survival or an organization's ability to achieve its key long-run goals. The classic techniques for managing investment risk are diversification, hedging, and insurance.

Mastering the Market Cycle: Getting the Odds on Your Side
by Howard Marks
Published 30 Sep 2018

Words like “seem” and “appear” are the right ones, since they indicate that risk and potential return can only be estimated, and that the investment world doesn’t work like a machine. That makes those words highly appropriate—actually, compelling—for use when discussing investing. (For a more thorough discussion, see chapter 5 of The Most Important Thing.) People who immediately “get” concepts like risk and risk/return usually have an intuitive sense that prepares them to be good investors. I hope the reasons behind my interpretation of the graphic will become immediately clear once I have prompted you to think about it. Let’s suppose a logical investor is offered two investments with the same expected return, but in one case the return is virtually assured and in the other it is highly uncertain.

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That’s the way it’s supposed to work, and in fact I think it generally does (although the requirements aren’t the same at all times). The result is a capital market line of the sort that has become familiar to many of us, as shown below. The process described above results in the formation of the risk/return continuum or “capital market line.” The process establishes the general level of return relative to risk, as well as the quantum of incremental promised return—or the “risk premium”—that will be expected for the bearing of incremental risk. In a rational world, the result will be as follows: Investments that seem riskier will be priced so that they appear to offer higher returns.

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It is for these reasons that, as you’ll see in the next chapter, the shakiest financings are completed in the most buoyant economies and financial markets. Good times cause people to become more optimistic, jettison their caution, and settle for skimpy risk premiums on risky investments. Further, since they are less pessimistic and less alarmed, they tend to lose interest in the safer end of the risk/return continuum. This combination of elements makes the prices of risky assets rise relative to safer assets. Thus it shouldn’t come as a surprise that more unwise investments are made in good times than in bad. This happens even though the higher prices on risky investments may mean the prospective risk premiums offered for making those riskier investments are skimpier than they were in more risk-conscious times.

Derivatives Markets
by David Goldenberg
Published 2 Mar 2016

Currency Forward Pricing 7.4 Stock Index Futures 7.4.1 The S&P 500 Spot Index 7.4.2 S&P 500 Stock Index Futures Contract Specifications 7.4.3 The Quote Mechanism for S&P 500 Futures Price Quotes 7.5 Risk Management Using Stock Index Futures 7.5.1 Pricing and Hedging Preliminaries 7.5.2 Monetizing the S&P 500 Spot Index 7.5.3 Profits from the Traditional Hedge 7.5.4 Risk, Return Analysis of the Traditional Hedge 7.5.5 Risk-Minimizing Hedging 7.5.6 Adjusting the Naive Hedge Ratio to Obtain the Risk-Minimizing Hedge Ratio 7.5.7 Risk Minimizing the Hedge Using Forward vs. Futures Contracts 7.5.8 Cross-Hedging, Adjusting the Hedge for non S&P 500 Portfolios 7.6 The Spot Eurodollar Market 7.6.1 Spot 3-month Eurodollar Time Deposits 7.6.2 Spot Eurodollar Market Trading Terminology 7.6.3 LIBOR3, LIBID3, and Fed Funds 7.6.4 How Eurodollar Time Deposits are Created 7.7 Eurodollar Futures 7.7.1 Contract Specifications 7.7.2 The Quote Mechanism, Eurodollar Futures 7.7.3 Forced Convergence and Cash Settlement 7.7.4 How Profits and Losses are Calculated on Open ED Futures Positions PART 2 Trading Structures Based on Forward Contracts CHAPTER 8 STRUCTURED PRODUCTS, INTEREST-RATE SWAPS 8.1 Swaps as Strips of Forward Contracts 8.1.1 Commodity Forward Contracts as Single Period Swaps 8.1.2 Strips of Forward Contracts 8.2 Basic Terminology for Interest-Rate Swaps: Paying Fixed and Receiving Floating 8.2.1 Paying Fixed in an IRD (Making Fixed Payments) 8.2.2 Receiving Variable in an IRD (Receiving Floating Payments) 8.2.3 Eurodollar Futures Strips 8.3 Non-Dealer Intermediated Plain Vanilla Interest-Rate Swaps 8.4 Dealer Intermediated Plain Vanilla Interest-Rate Swaps 8.4.1 An Example 8.4.2 Plain Vanilla Interest-Rate Swaps as Hedge Vehicles 8.4.3 Arbitraging the Swaps Market 8.5 Swaps: More Terminology and Examples 8.6 The Dealer’s Problem: Finding the Other Side to the Swap 8.7 Are Swaps a Zero Sum Game?

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Using the settlement prices, is there contango or backwardation? c. Is the price of storage always positive? TABLE 6.1 CME Corn Contract Price Quotes Reprinted by permission of the CME Inc., 2014. ■ SELECTED CONCEPT CHECK SOLUTIONS Concept Check 1 a. The meaning of the words is: another portfolio of financial instruments that has the same risk, return characteristics as the actual T-bill. This means the same maturity, the same risk, and as we shall see in this example, the same yield. Another way to think about the synthetic instrument is as a replicating portfolio. When we synthesized forward contracts, we saw that a synthetic forward contract is a portfolio consisting of the underlying spot instrument fully financed by a zero-coupon bond maturing at the expiration date of the forward contract.

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Currency Forward Pricing 7.4 Stock Index Futures 7.4.1 The S&P 500 Spot Index 7.4.2 S&P 500 Stock Index Futures Contract Specifications 7.4.3 The Quote Mechanism for S&P 500 Futures Price Quotes 7.5 Risk Management Using Stock Index Futures 7.5.1 Pricing and Hedging Preliminaries 7.5.2 Monetizing the S&P 500 Spot Index 7.5.3 Profits from the Traditional Hedge 7.5.4 Risk, Return Analysis of the Traditional Hedge 7.5.5 Risk-Minimizing Hedging 7.5.6 Adjusting the Naive Hedge Ratio to Obtain the Risk-Minimizing Hedge Ratio 7.5.7 Risk-Minimizing the Hedge Using Forward vs. Futures Contracts 7.5.8 Cross-Hedging, Adjusting the Hedge for non S&P 500 Portfolios 7.6 The Spot Eurodollar Market 7.6.1 Spot 3-month Eurodollar Time Deposits 7.6.2 Spot Eurodollar Market Trading Terminology 7.6.3 LIBOR3, LIBID3, and Fed Funds 7.6.4 How Eurodollar Time Deposits are Created 7.7 Eurodollar Futures 7.7.1 Contract Specifications 7.7.2 The Quote Mechanism, Eurodollar Futures 7.7.3 Forced Convergence and Cash Settlement 7.7.4 How Profits and Losses are Calculated on Open ED Futures Positions The crown jewels of futures contracts are the financial futures contracts which were introduced to the world in the late 1970s and early 1980s by the CME and the CBOT (since merged) in Chicago.

Capital Ideas: The Improbable Origins of Modern Wall Street
by Peter L. Bernstein
Published 19 Jun 2005

They help investors deal with uncertainty. They provide benchmarks for determining whether expectations are realistic or fanciful and whether risks make sense or are foolish. They establish norms for determining how well a market is accommodating the needs of its participants. They have reformulated such familiar concepts as risk, return, diversification, insurance, and debt. Moreover, they have quantified those concepts and have suggested new ways of employing them and combining them for optimal results. Finally, they have added a measure of science to the art of corporate finance. Many of these innovations lay hidden in academic journals for years, unnoticed by Wall Street until the financial turbulence of the early 1970s forced practitioners to accept the harsh truth that investment is a risky business.

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Still, research reveals that investors have a sharp nose for smelling out the truth for themselves. Thus, Modigliani and Miller put investors back in the catbird seat, with corporate managers at their mercy. Through arbitrage, profit-seeking investors can eliminate discrepancies in the perceived risk/return trade-offs of one security relative to another to the point where no one has any incentive to buy or sell. Trades take place only when investors disagree about the future of a company or when new information surfaces. Modigliani and Miller’s market is a market in equilibrium. And yet equilibrium is only a rough approximation of reality, because information pours into the marketplace constantly, in every shape and form.

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But then he accepted: “If I had stayed at Merrill, they would have made me into a narrow quant.”39 A zealous editor, Treynor encouraged the publication of papers on the new theories, wrote a series of challenging short editorials, and contributed articles himself under the pseudonym Walter Bagehot. His role was not to be an easy one. Concepts like random walks, efficient markets, complicated versions of risk/return tradeoffs, and betas, with their complex mathematical formulations, scandalized the more traditional members of the Journal’s advisory board. James Vertin, then at Wells Fargo in San Francisco and an ally of Treynor’s on the board, recalls, “They were going to close it down because it had all this dumb stuff in it that nobody could understand!”

Money Mavericks: Confessions of a Hedge Fund Manager
by Lars Kroijer
Published 26 Jul 2010

There are employees, counterparties and investors to whom I wish I had shown more gratitude, either financially or verbally. The list goes on … There is nothing intrinsically wrong with hedge funds. This is an industry that attracts some of the best minds in finance and gives them a wide mandate to generate returns that greatly enhance the risk/return profile of any portfolio. If they do well, they are amply rewarded, and if they fail, they are fired. While the hedge-fund industry was still a fairly small sector that profitably exploited selected pockets of market inefficiencies, the premise worked. As the number of hedge funds exploded to the near 10,000 in existence today, I think too many mediocre managers were paid too much for the industry to make sense to the end investor (like Mrs Straw, mentioned earlier).

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But if we assume that capital flows between different national markets are less efficient than flows within each market, we might be able to do better than simply allocate capital to each market in accordance with their relative market capitalisation (like the MSCI World does in the example above). In this case we should be able to enhance our risk/return profile by re-allocating capital on the basis of optimal portfolio theory, using inputs on expected market correlations, a reasonable estimate of the risk of each market, a return expectation (we can make this a function of the risk levels) and a few other fairly non-controversial assumptions. What we are trying to do is to create a portfolio of well-diversified liquid markets across the world in a way that is cheap to construct and where we have a reasonable estimate of the risk and expectation of an outperformance relative to the simple market capitalisation index.

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In an earlier edition of this book I argued that investors could gain from buying protection against the market scenarios where correlations spiked in a broad-based slump. By buying deep out-of-the-money puts on the market we could protect ourselves against disaster scenarios. This protection would eliminate the high correlation drawdowns and the resulting portfolio would be a lower correlation combination of securities with a better risk/return profile. While a valid idea, in reality this purchase of downside protection is impractical for most investors. First and foremost, many investors are not set up to trade options and are generally inclined to stay away from the space of derivative trading (a healthy trait indeed). Second, consistently buying out-of-the-money puts in a high volatility environment can be prohibitively expensive, particularly when you include the large bid/offer spreads and commissions charged.

The Alpha Masters: Unlocking the Genius of the World's Top Hedge Funds
by Maneet Ahuja , Myron Scholes and Mohamed El-Erian
Published 29 May 2012

At any point in time, it would combine these 60 to 100 positions with any client-chosen benchmark. For the Kodak pension fund, an early client, Bridgewater managed Pure Alpha combined with a passive holding in long-duration bonds and inflation-indexed bonds. It was the best way to produce the best risk return. “Now it would be called innovative,” says Dalio. “Back then I guess it would be called crazy.” By doing this, the client could always specify beta. “This is how we manage money now,” says Dalio. “Clients tell us they would like an equity account and set a benchmark, like the S&P 500. We either replicate the benchmark or buy futures to equal the benchmark.

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In addition to banks with two-tiered capital structures, Paulson also found opportunities in other financial companies with a holding company structure, such as insurance companies, and in leveraged buyouts. Almost all investors hated shorting bonds because most of the time the bonds paid out, and the negative carry from paying the interest on the short bond was a drag on performance. Paulson had not been dissuaded from this challenge. He liked the asymmetrical risk/return potential, and continued to pursue this area as an investment strategy with periodic success over time. By the spring of 2005, Paulson became increasingly alarmed by weak credit underwriting standards and excessive leverage being used by financial institutions. Credit quality had deteriorated to the point where the worst-performing companies could readily raise financing.

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Since then, numerous obstacles had delayed the deal, and a significant amount of Paulson & Co.’s wealth was on the line. Paulson was doing everything he could to encourage Dow to execute. Paulson feels it is easy to compute returns from a spread, but his and his team’s expertise comes into play when evaluating the risk-return trade-off for a deal in trouble. Deal completion risks are exacerbated when the economy and market weaken. When the economy slipped into a deep recession after Lehman failed, Dow found that the price it had agreed to pay for the company was too high and it wanted to exit the transaction. The spread went from $2 when the deal was announced to $25 as the stock fell to the low 50s.

Cloudmoney: Cash, Cards, Crypto, and the War for Our Wallets
by Brett Scott
Published 4 Jul 2022

Financial inclusion professionals who seek to incorporate poorer people into the banking sector recognised that phones could lower the fixed costs of providing services, which – when passed through a risk-return model – made serving poorer people more profitable (while also allowing banks to integrate financial data with other data collected on phones to build a profile of the customer). Almost all financial inclusion initiatives present digital technology as a great leap forward that will enable ‘the unbanked’ to get banked. Not mentioned, however, is that the economic risk-return equation is only half of a bigger equation. While banks may not like poorer people unless they can make dealing with them profitable, poorer people have often had no natural reason to like banks either.

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This is because financial institutions are attracted to risk-adjusted profit: the ultimate ‘irrational’ business line is one in which they take high risk and expect low (or no) monetary return, and the ultimate ‘rational’ one is that which yields high returns with low risk. When deciding upon which customers to offer accounts to, they carry out risk-return calculations, considering how costly it is to manage those accounts, and contrasting that with how much revenue they can expect to make from the customer by getting them to pay fees or take loans. Finally, they consider the risk the customer exposes them to. Banks have traditionally bent over backwards for rich aristocrats and merchants, in the knowledge that providing them with accounts was likely to yield good returns over time at relatively low risk.

The Missing Billionaires: A Guide to Better Financial Decisions
by Victor Haghani and James White
Published 27 Aug 2023

Tobin summarized this “important and beautiful result” as “Don't put all your eggs in one basket,” while Willem Buiter, in a review of Tobin's contributions added: “…and you will only need two baskets for all your eggs.”24 Finding the risk‐return optimal portfolio of all risky assets would be very challenging if we had to estimate the return distributions and correlations among all the thousands of individual public companies and other risky potential investments. But if we believe the market is fairly efficient, we can short‐circuit making a direct calculation. In an efficient market, the capitalization‐weighted portfolio of all risky assets is itself the best estimate of the risk‐return optimal portfolio. Even though this result may not hold precisely for large major markets like global equities, there's good reason to believe it comes pretty close.

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—Albert Einstein It is only your after‐tax wealth that you are able to spend or give away, so it's proper to be focused on after‐tax outcomes.a Tax rules are complex, and so for tax‐related decisions, it is common practice to focus on optimizing after‐tax wealth in a single central case. However for most tax decisions, risk is an integral part of the problem, and so a static analysis involving a comparison of after‐tax wealth under a “most likely” scenario may not lead to the correct decision. For a good illustration of the risk‐return trade‐off inherent in most tax decisions, imagine you put a small fraction of wealth into a stock that subsequently went up a lot. It now represents a large fraction of your total wealth, but you don't have a strong opinion about its pricing. At this stage you're probably taking too much total risk and are also insufficiently diversified.

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See also US stock market Stock pickers (stock picking), 211, 212, 215–216, 224, 246, 307, 335 Stocks: options on single, 260–261 trading volume of, vs. options, 245 volatile, 226, 226e Streetlight Effect, 202n Stumbling on Happiness (Gilbert), 75 Style premia, 219 Suboptimal betting, 20 Subsistence spending, 140, 183–186, 184e Sustainable spending rule, 158–159 Swensen, David, 107, 150, 162 Tail hedging, 255 Tail risk, negative, 228 Taleb, Nassim Nicholas, 23, 118 Target Date funds, 64 Tax deferral, 213 Tax efficiency, 62 Taxes (taxation), 265–273 capital gains, effect of, 268–269 and Expected Utility framework, 272 and family wealth, 161 of gifts, 182 optimized allocation with unrealized gains, 270–271 and realized gains, 266–268 and risk‐return trade‐off, 266 Tax‐inefficient investments, 229 Tax loss harvesting, 271 T‐bills, see US Treasury bills 1031 exchanges, 273 Tesla, 43–44, 226, 262 Thorp, Edward O., 24, 45 Time horizon, in Merton Share formula, 45–46 Time preference, 133, 135–137, 146, 155–159, 349n5, 189–190, 292, 294–295, 298 “Times Series Momentum” (Moskowitz et al.), 60 Tobin, James, 154, 155, 231–232, 344n2 Tobin's Q, 59 “Trading Can Be Hazardous to Your Health” (Barber and Odean), 6 Trading state claims, 293 Treasury bills, see US Treasury bills Treasury Inflation‐Protected Securities (TIPS), 52–56, 54e, 171, 204, 227, 231, 234, 234n, 237–239, 241, 336 A Treatise on Probability (Keynes), 275 Treynor, Jack, 232, 344n2 Trump, Donald J., 297 Turnover, and tax efficiency, 62 Tversky, Amos, 104, 107–110, 331, 332 Twitter, 43 Two‐asset world model, 43 Two envelopes paradox, 277–278 Uncertainty, risk vs., 275–284 United Kingdom, 156, 298, 299, 301 Unrealized gains, 270–271 US stock market, 4, 23–24, 55e, 294 and expected utility, 85–86 1929 crash, 252 1987 crash, 184–185, 207, 249, 290, 314 probability of 90% declines in, 123 realized return of, since 1900, 43 return distribution of, 112 US Treasury, 227 US Treasury bills (T‐bills), 23, 142, 205, 225, 228, 231, 237–238, 255, 257, 314, 314t, 345n4 US Treasury bonds, 50, 125, 212–213 Utility.

The Financial Crisis and the Free Market Cure: Why Pure Capitalism Is the World Economy's Only Hope
by John A. Allison
Published 20 Sep 2012

The smaller banks will eventually follow; if they do not, they will end up with lower returns on equity than their bigger competitors and will be vulnerable to being acquired. The larger company can simply leverage the “excess” equity in the smaller company, acquiring it. Also, anytime there is a downturn in the economy, the Fed consistently “saves” the very large banks, creating an unbalanced risk/ return trade-off. If you manage a large financial institution, why not be leveraged, which increases your profits in good times, because the Fed will always bail out your company during bad times? During my career, the Fed has systematically effectively encouraged banks to increase their leverage (sometimes intentionally, sometimes not).

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FDIC insurance primarily reduces the short-term risk of bank runs because depositors perceive their deposits to be insured by the federal government. However, I previously described the fact that FDIC insurance substantially increases the credit and liquidity risk that banks take by eliminating market discipline. Based on my long-term observation of the behavior of bank executives (human nature), the existence of FDIC insurance changes the risk/return trade-offs so significantly that in the good times (when bad loans are made), bankers take risks that they would never take in a free market. FDIC insurance is pro-cyclical; that is, it increases both the size of the bubble (the misinvestment) and the magnitude of the bust. In the short term, the Federal Reserve can be important in controlling liquidity risk.

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Also, do not be surprised if it returns to the same high-risk financing strategy in the future. After all, there is no downside risk when you have a strong relationship with Big Brother. Many people have declared TARP a success because most of the money will be paid back. This is a totally improper measure of performance. Even if the taxpayers get most of their money back, the risk/return trade-off was irrational at the time the government investments were made. Private investors would not have taken this risk given the relatively low returns to be earned. More significantly, a rational assessment of TARP must consider its short-term and long-term economic consequences. This is a challenging question to answer, but there is a historical precedent that is useful for comparison.

Python for Algorithmic Trading: From Idea to Cloud Deployment
by Yves Hilpisch
Published 8 Dec 2020

Maximum drawdown (vertical line) and drawdown periods (horizontal lines) The following code derives VaR values based on the log returns of the equity position for the leveraged trading strategy over time for different confidence levels. The time interval is fixed to the bar length of ten minutes: In [97]: import scipy.stats as scs In [98]: percs = [0.01, 0.1, 1., 2.5, 5.0, 10.0] In [99]: risk['return'] = np.log(risk['equity'] / risk['equity'].shift(1)) In [100]: VaR = scs.scoreatpercentile(equity * risk['return'], percs) In [101]: def print_var(): print('{} {}'.format('Confidence Level', 'Value-at-Risk')) print(33 * '-') for pair in zip(percs, VaR): print('{:16.2f} {:16.3f}'.format(100 - pair[0], -pair[1])) In [102]: print_var() Confidence Level Value-at-Risk --------------------------------- 99.99 162.570 99.90 161.348 99.00 132.382 97.50 122.913 95.00 100.950 90.00 62.622 Defines the percentile values to be used.

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Calculating the cumulative sum over time with cumsum and, based on this, the cumulative returns by applying the exponential function np.exp() gives a more comprehensive picture of how the strategy compares to the performance of the base financial instrument over time. Figure 4-4 shows the data graphically and illustrates the outperformance in this particular case: In [55]: data[['returns', 'strategy']].cumsum( ).apply(np.exp).plot(figsize=(10, 6)); Figure 4-4. Gross performance of EUR/USD compared to the SMA-based strategy Average, annualized risk-return statistics for both the stock and the strategy are easy to calculate: In [56]: data[['returns', 'strategy']].mean() * 252 Out[56]: returns -0.019671 strategy 0.028174 dtype: float64 In [57]: np.exp(data[['returns', 'strategy']].mean() * 252) - 1 Out[57]: returns -0.019479 strategy 0.028575 dtype: float64 In [58]: data[['returns', 'strategy']].std() * 252 ** 0.5 Out[58]: returns 0.085414 strategy 0.085405 dtype: float64 In [59]: (data[['returns', 'strategy']].apply(np.exp) - 1).std() * 252 ** 0.5 Out[59]: returns 0.085405 strategy 0.085373 dtype: float64 Calculates the annualized mean return in both log and regular space.

The Little Book of Hedge Funds
by Anthony Scaramucci
Published 30 Apr 2012

Using a top-down approach, they attempt to anticipate macroeconomic trends and price changes on capital markets by analyzing the variables associated with the different countries in which they allocate their capital. To do so, they study how certain political events, global macroeconomic factors, and financial fundamentals influence the prices of securities, indices, options, futures contracts, and so on. Simultaneously, they analyze both developed and emerging markets worldwide and the risk/return potential of a given investment.4 Once they determine a global investment thesis, they make leveraged bets on the direction of the movements in the market and earn the difference between the borrowing cost and the profit from their directional bets going the way that they predict. Although global macro strategies are different from the strategies created by A.

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Ultimately, the overall performance of a fund of hedge funds is a function of this strategic portfolio construction that is based on hedge fund strategy outlook, hedge fund manager selection, and liquidity and risk management. If done appropriately, this allocation will minimize volatility and maximize risk returns. The Specifics The best and brightest in the fund of funds industry do the following three things for their clients: 1. They have a deep understanding of the macroeconomic situations and the global economy, taking into account what the Federal Reserve and other central banks are doing and also what is going on in the world’s currency and commodities markets.

Chaos Kings: How Wall Street Traders Make Billions in the New Age of Crisis
by Scott Patterson
Published 5 Jun 2023

Soon after, he was asked to help Japanese clients (at the time very wealthy clients indeed) put together global fixed-income portfolios. He went to Black for help. “Well, you know, my attitude is to start out simple, and if it doesn’t work, then you can always do something more complicated,” Black said. He suggested using a standard risk-return model based on Harry Markowitz’s Modern Portfolio Theory method that encouraged the multi-basket diversification approach (the very approach derided by Spitznagel and Taleb). It didn’t work, at least at first. Through a series of tweaks and new methods based in part on his work on vector autoregressions, Litterman ultimately designed a model that spit out optimal asset allocations depending on investors’ risk appetites.

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Over thirteen years, Universa’s Black Swan risk-mitigation strategy, on average, had outperformed the S&P 500 by more than 3 percentage points a year. And it did so by “having far less risk,” Spitznagel claimed in Safe Haven. Spitznagel’s argument captivated Peter Coy, a financial writer for the New York Times. In a November 2021 review of Safe Haven called “The Risk-Return Trade-Off Is Phony,” he wrote: “Conventional wisdom in investing says there’s a trade-off between risk and return. To make a lot of money, you must take the chance of big losses. Play it safe and you’ll most likely have to settle for meager returns. The investor Mark Spitznagel says that reducing risk actually increases returns, and he has evidence.”

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“I think there’s something going on with blockchain” Author interview with Schmalbach. “We are witnessing a fundamental reordering” https://www.aon.com/reputation-risk-report-respecting-grey-swan/index.html. CHAPTER 23: THE GREAT DILEMMA OF RISK Spitznagel’s argument captivated Peter Coy Peter Coy, “The Risk-Return Trade-Off Is Phony,” New York Times, November 15, 2021, https://www.nytimes.com/2021/11/15/opinion/risk-investing-market-hedge.html. CHAPTER 24: DOORSTEP TO DOOM Bitcoin rallied in 2021, hitting an all-time high Elaine Yu and Caitlin Ostroff, “Bitcoin’s Price Climbs Above $20,000 After Sharp Crypto Selloff,” Wall Street Journal, June 19, 2022, https://www.wsj.com/articles/bitcoins-price-falls-below-20-000-11655542641.

Be Your Own Financial Adviser: The Comprehensive Guide to Wealth and Financial Planning
by Jonquil Lowe
Published 14 Jul 2010

Given the many potential sources of risk and the fact that investment products can often be used in different ways that may increase the M09_LOWE7798_01_SE_C09.indd 254 05/03/2010 09:51 9 n Saving and investing 255 inherent risk, there is no neat, definitive way to rank products in order of their risk–return balance. You will always have to look at each product individually to assess precisely where the balance lies. Nevertheless, Figure 9.1 gives an indication of rank as a rough starting point. The letters after each investment indicate the predominant risks in each case. Balancing risks It is impossible to eradicate all risk from your saving and investment strategies.

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Asset allocation Although investment diversification has been described above in the context of shares, it applies equally to any other type of investment that is traded on a market, such as bonds and even residential property (see the discussion of buy-to-let on p. 330). Diversification also applies across the boundaries of different investments. Just as combining uncorrelated or weakly correlated shares reduces risk for any given level of return, combining different types of investments – called asset classes – also improves the risk-return balance, provided the classes are uncorrelated or only 3 www.advfn.com. Accessed 3 October 2009. 4 www.advfn.com. Accessed 3 October 2009. M10_LOWE7798_01_SE_C10.indd 299 05/03/2010 09:51 300 Part 3 n Building and managing your wealth weakly correlated. Traditionally, there are four main asset classes which, in ascending order of capital risk, are: OO Cash, meaning deposit-type investments where you earn interest and the risk to your capital is usually negligible.

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Normally this refers to commercial property, for example, holding of office blocks, shopping centres and industrial parks or shares in companies that specialise in owning and managing these. Private investors often hold residential property as an investment. OO Equities. These are shares in companies. In general, these four classes tend to be sufficiently uncorrelated – responding to economic events in different ways – to improve the risk-return balance when they are combined in a portfolio. For example, equities and property tend to do well in times of inflation, unlike cash and bonds. But cash and bonds may produce solid returns in an economic downturn, while property and equities tend to suffer. The extent to which different investments or assets are correlated can be measured and represented by a statistic called a ‘correlation coefficient’.

Our Lives in Their Portfolios: Why Asset Managers Own the World
by Brett Chistophers
Published 25 Apr 2023

The greater the amount of work required, the higher the percentage. In the world of infrastructure and real-estate investment, funds are usually distinguished not only on the basis of their structure – that is, the open-end versus closed-end distinction outlined earlier in this chapter – but also according to their estimated risk–return profile. At one end of the spectrum are so-called ‘core’ funds, which are low-risk and generally invest in assets generating secure and predictable incomes, but with little potential for capital appreciation. At the other end of the spectrum are ‘opportunistic’ funds, where the risk is higher, but so also is the potential for capital gain and thus outsized investment returns.

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While the incorporation of water-supply infrastructures into asset-manager society is accelerating, it remains a relatively circumscribed phenomenon: for now, at least, ownership of such infrastructures by asset managers is much less common than asset-manager ownership of energy, transportation or telecoms infrastructures. There are good reasons for this. As a 2020 OECD report on institutional investment in infrastructure pointed out, a series of factors frequently serve to limit ‘the attractiveness of the [water] sector’s risk-return profile for private investors compared to other infrastructure sectors’. One is the difficulty of raising tariffs: ‘the water sector generally has a poor record of cost recovery, with tariffs often too low to fully cover operational and maintenance costs, and rarely covering capital costs. Many jurisdictions lack an independent regulator for tariff setting and concerns regarding affordability often keep tariffs below cost reflective levels’.

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This is not because asset managers do not prioritise exchange value or are not single-minded profit-maximisers: they very clearly do, and are. Nor is it to imply that such profit maximisation is not ill-suited to the sphere of social reproduction; it certainly is. As the UN’s rapporteurs scolded Blackstone (see Chapter 3), and as Daniela Gabor and Sebastian Kohl have recently argued, it is extremely hard to regard the ‘mandates and risk/return requirements’ of institutional investors and their asset managers as being compatible with ‘the delivery of housing as a human right’.47 Rather, the critique of ‘financialisation’ is a non-starter for our purposes because of the ill-founded distinction that it draws between asset managers (and other financial institutions) on the one hand and other private-sector real-asset owners on the other.

Rigged Money: Beating Wall Street at Its Own Game
by Lee Munson
Published 6 Dec 2011

Modern Portfolio Theory (MPT) assumes that investors will be rational. If given two portfolios with the same expected return, an investor will choose the less risky one. Why would you choose something more risky if it does the same thing as another portfolio with less risk? You wouldn’t if there was a bulletproof way of knowing the risk return of every security. People have different opinions on the matter. What makes the whole exercise of finding the less risky portfolio more dubious is that we use past performance to get this so-called expected return. Did I mention that there is no one way of coming up with this number? There is a whole army of analysts—including people like me—that have our own special ways of guessing what an asset class is expected to do in the future.

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That said, how is an investor supposed to commit large allocations of capital in fixed income ETFs with that sinking feeling that this 30-year party may be over? MLPs are neither stock nor bond, but they can be an alternative to a portfolio seeking diversification and income outside of traditional asset classes. If you were thinking of buying higher-volatility bond ETFs like HYG, JNK, or PFD, read on and find another way to capture higher risk return and diversification. In their simplest form, MLPs are publicly traded organizations that are structured as limited partnerships (LP) rather than corporations. MLPs combine the tax benefits of an LP with the liquidity of a publicly traded security. Because the MLP passes through income, the limited partner can achieve higher current cash flow, meaning the company doesn’t pay tax on income by passing that income to the investor.

Hubris: Why Economists Failed to Predict the Crisis and How to Avoid the Next One
by Meghnad Desai
Published 15 Feb 2015

Cash carries no risk and yields no return. From then on, one can rank assets by return as measured by the average yield and risk as measured by the variance of the return. The risk–return “frontier” is like a constraint. Each investor can then define his or her preference between risk and return, as with consumer utility functions. To maximize the preference we need the tangent of the preference function with the risk–return frontier, that is, the highest level of return consistent with the risk preference of the consumer. This gives us a theory of portfolio selection for investors, who may choose between cash, bonds, equities and other riskier assets.

The Invisible Hands: Top Hedge Fund Traders on Bubbles, Crashes, and Real Money
by Steven Drobny
Published 18 Mar 2010

When we get into a trade, we try to have an idea of the risk versus reward, and what type of trade it is. For a short-term tactical trade, we are trying to get a base hit because something seems out of line for a day or a few days. When we have more conviction on a particular theme, we will run a bigger position, going for a double or a triple. In either case, we look for asymmetric risk/return profiles, risking, say, 5 percent to make 10 or 15 percent, or risking 25 percent to make 50 to 100 percent. In general, we always sell winners “too soon” because we are scaling out into strength. It’s more art than science on the upside. We try to balance how consensus our idea has become, what kind of price target makes sense for our time horizon and the market action.

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This is compounded by the fact that managers putting on illiquid trades did not personally face the true costs, meaning real money funds most likely did not charge enough for this in the past. Second, many argue that the ability to control and know the cash flows makes private assets (e.g., real estate) useful liability hedges. This may or may not be true, though my inclination is that these assets can and should stand on their own risk/return merits. “Labeling” something a hedge does not necessarily make it one, leading to misspecified risks and asset weights. Third, there are the tax shield and operational efficiency arguments for private equity, though these have to be weighed against the high management fee structure associated with most private equity funds.

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See Maximum Sharpe Ratio Multiyear horizons NASDAQ (1995-2003) index (1994-2003) mispricing Negative carry Negative skew risk New Deal New York Mercantile Exchange (NYMEX) Nikkei (1980-1998) Nominal GDP Non-Accelerating Inflation Rate of Unemployment (NAIRU) Nonconstant volatility, presence Nonequity assets, inclusion Nongovernmental organizations (NGOs), data Normal backwardation North Sea crude Notre Dame (university endowment) Ohio, pension fund loss Oil (1986-2009) Oil (1998-2009) Oil fields, Commodity Investor purchase 1% effect One time stimulus programs Optimal portfolio construction, real money funds failure Optionality, usage Options markets, day-to-day liquidity Options, usage Orange County pension fund, problem Outcomes, positive asymmetry (achievement) Overnight index, geometric average Overnight indexed swap (OIS) spreads (2006-2008) Overvaluation zones, examination Overvalued assets (portfolio ownership), diversification (absence) Oxford Endowment, asset management Passive asset mix, importance Passive commodity indices, avoidance Paulson, Henry Peak oil, belief Pension Benefit Guaranty Corporation (PBGC), corporation pension fund guarantees Pensioner, The CalPERS control, example dollar notional thinking illiquid asset avoidance illiquidity premium measurement process illiquidity risk, hedge process interview investment scenario lessons leverage, usage performance, compounding cost post-crash investment, peer performance returns, targeting risk management risk premiums, specification risk/return approach 60-40 policy, standardization Pension funds allocation base currency commodity investment reasons constraint increase investment implementation, changes talent, quality long-term investment horizon real risk swaps/futures, usage Pensions assets, conservative management cash level change contributions, delay funding levels plans, constraints profits structure, impact systems, demographic challenges (impact) underfunding, shortfall Perfection, paradox Personal budgets, problems Philippines, peso (1993-1994) Philosopher, The Physical commodities, front contract advantage Pioneering Portfolio Management (Swensen) Plan assets, value (estimate) Plasticine™ Plasticine Macro Trader, The China perspective commodities, ownership complacency context, creation contrarian perspective diversification interpretation equities, delusion Favorite Trade format disapproval,–370368 hedge funds usage ideas, generation (global macro perspective) information, filtration interview investment safety investment storm investor letter, impact Japan bullishness liquidity, importance long-only community, adaptation long-only investment market behavior entry, awareness irrationality, relationship mentor lessons pension fund portfolio management performance portfolio construction, rethinking creation operation predictability, degree risk management evolution importance lessons success, consideration trade development ideas, importance problem theses, development trading decisions trend, anticipation P&L trading Popper, Karl Portable alpha allocation Portfolio Commodity Hedger construction construction guidelines rethinking diversification risk diversity Equity Trader construction illiquid assets, leverage illiquidity level, risk management levering, risk collars (usage) liquidity management, difficulty management investor approach recipe marginal trade optimization P&L volatility, limits policy activity, increase (impact) real money manager construction replication/modeling risks concentration, increase management size, reduction stress tests, conducting structure Portfolio-level expected alpha Positioning, understanding Positions notional value oversizing running scaling Positive asymmetry, achievement Potash Corporation of Saskatchewan (2008) Precommitments, method Predator, The bearishness, development CalPERS operation inflection points, awareness information collection examination process interview lessons liquidity, valuation macro overlay, profitability markets fundamentals/psychology, impact psychology, understanding mental flexibility optimist, perspective risk management stock market increase, nervousness stocks long position picking, profitability style, evolution tactical approach time horizon trade problem quality trading ideas, origination uniqueness Premium.

No One Would Listen: A True Financial Thriller
by Harry Markopolos
Published 1 Mar 2010

“In addition, experts ask why no one has been able to duplicate similar returns using the strategy and why other firms on Wall Street haven’t become aware of the fund and its strategy and traded against it, as has happened so often in other cases; why Madoff Securities is willing to earn commissions on the trades but not set up a separate asset management division to offer hedge funds directly to investors and keep all the incentive fees for itself, or conversely, why it doesn’t borrow money from creditors ... and manage the funds on a proprietary basis.” And then he presented Madoff’s responses, describing him as appearing “genuinely amused by the interest and attention aimed at an asset management strategy designed to generate conservative, low-risk returns that he notes are nowhere near the top results of well-known fund managers on an absolute return basis. “The apparent lack of volatility in the performance of the fund, Madoff says, is an illusion based on a review of monthly and annual returns. On an intraday, intraweek, and intramonth basis, he says, ‘the volatility is all over the place, with the fund down by as much as 1 percent.”

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I had no personal relationship with any of them, and I certainly didn’t want Bernie Madoff to know we were tracking him. Like Access, these funds needed Bernie to survive; they didn’t need me. Where would their loyalty be? And what would happen to me when Madoff found out I had warned them? I did appreciate the fact that they were trapped. They had to have Madoff to compete. No one had a risk-return ratio like Bernie. If you didn’t have him in your portfolio, your returns paled in comparison to those competitors who did. If you were a private banker and a client told you someone he knew had invested with Madoff and was getting 12 percent annually with ultralow volatility, what choice do you have?

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Bernie Madoff is willing to answer each of those inquiries, even if he refuses to provide details about the trading strategy he considers proprietary information. And in a face-to-face interview and several telephone interviews, Madoff sounds and appears genuinely amused by the interest and attention aimed at an asset management strategy designed to generate conservative, low risk returns that he notes are nowhere near the top results of well-known fund managers on an absolute return basis. Lack of Volatility Illusory The apparent lack of volatility in the performance of the fund, Madoff says, is an illusion based on a review of the monthly and annual returns. On an intraday, intraweek and intramonth basis, he says, “the volatility is all over the place,” with the fund down by as much as 1 percent.

Corporate Finance: Theory and Practice
by Pierre Vernimmen , Pascal Quiry , Maurizio Dallocchio , Yann le Fur and Antonio Salvi
Published 16 Oct 2017

By varying ρH,C between −1 and +1, we obtain: Proportion of C shares in portfolio (XC) (%) 0 25 33.3 50 66.7 75 100 Return on the portfolio: E(rH,C) (%) 6.0 7.8 8.3 9.5 10.7 11.3 13.0 Portfolio risk σ(rH,C) (%) ρH,C = −1 10.0 3.3 1.0 3.5 8.0 10.3 17.0 ρH,C = −0.5 10.0 6.5 6.2 7.4 10.1 11.7 17.0 ρH,C = 0 10.0 8.6 8.7 9.9 11.8 13.0 17.0 ρH,C = 0.3 10.0 9.7 10.0 11.1 12.7 13.7 17.0 ρH,C = 0.5 10.0 10.3 10.7 11.8 13.3 14.2 17.0 ρH,C = 1 10.0 11.8 12.3 13.5 14.7 15.3 17.0 Note the following caveats: If Criteo and Heineken were perfectly correlated (i.e. the correlation coefficient was 1), then diversification would have no effect. All possible portfolios would lie on a line linking the risk/return point of Criteo with that of Heineken. Risk would increase in direct proportion to Criteo’s stock added. If the two stocks were perfectly inversely correlated (correlation coefficient −1), then diversification would be total. However, there is little chance of this occurring, as both companies are exposed to the same economic conditions.

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As long as the correlation coefficient is below 1, diversification will be efficient. There is no reason for an investor to choose a given combination if another offers a better (efficient) return at the same level of risk. Efficient portfolios (such as a combination of Criteo and Heineken shares) offer investors the best risk–return ratio (i.e. minimal risk for a given return). Efficient portfolios fall between Z and Criteo. The portion of the curve between Z and Criteo is called the efficient frontier. For any portfolio that does not lie on the efficient frontier, another can be found that, given the level of risk, offers a greater return or that, at the same return, entails less risk.

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Continuing with the Heineken example, and assuming that rF is 3%, with 50% of the portfolio consisting of a risk-free asset, the following is obtained: Hence: For a portfolio that includes a risk-free asset, there is a linear relationship between expected return and risk. To lower a portfolio’s risk, simply liquidate some of the portfolio’s stock and put the proceeds into a risk-free asset. To increase risk, it is only necessary to borrow at the risk-free rate and invest in a stock with risk. 2. Risk-free assets and the efficient frontier The risk–return profile can be chosen by combining risk-free assets and a stock portfolio (the alpha portfolio on the chart below). This new portfolio will be on a line that connects the risk-free rate to the portfolio alpha that has been chosen. But as we can observe on the chart, this portfolio is not the best portfolio.

Frequently Asked Questions in Quantitative Finance
by Paul Wilmott
Published 3 Jan 2007

The expected return is then and the standard deviation of the return, the risk, is where ρij is the correlation between the ith and jth investments, with ρii = 1. Markowitz showed how to optimize a portfolio by finding the Ws giving the portfolio the greatest expected return for a prescribed level of risk. The curve in the risk-return space with the largest expected return for each level of risk is called the efficient frontier. According to the theory, no one should hold portfolios that are not on the efficient frontier. Furthermore, if you introduce a risk-free investment into the universe of assets, the efficient frontier becomes the tangential line shown below.

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J. 35 917-926 Poundstone, W 2005 Fortune’s Formula. Hill & Wang Why Hedge? Short Answer ‘Hedging’ in its broadest sense means the reduction of risk by exploiting relationships or correlation (or lack of correlation) between various risky investments. The purpose behind hedging is that it can lead to an improved risk/return. In the classical Modern Portfolio Theory framework, for example, it is usually possible to construct many portfolios having the same expected return but with different variance of returns (‘risk’). Clearly, if you have two portfolios with the same expected return the one with the lower risk is the better investment.

Smarter Investing
by Tim Hale
Published 2 Sep 2014

The second is usually something that sounds so fantastic that you get sucked into the upside and blinded to the risks (e.g. the true cases of firms peddling freeholds to apartment blocks in Beirut at the height of the troubles there, or repossessed homes in Florida). Alternatively, it is an investment strategy that is akin to picking up pennies in front of a steam roller. Good until you stumble. Any risk-return asymmetry is illusory. Mental tick box 6: If you get excited about a specific opportunity, stand back, take a deep breath and ask yourself where the catch is. Return and risk are always closely related. Ask yourself why, if the opportunity is so great, is someone trying to sell it to you? Surely they would keep it all to themselves.

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Whisky and water – keeping it simple James Tobin’s Separation Theorem (Tobin, 1957) suggests that the most efficient portfolio available is the ‘market portfolio’, i.e. the market cap weighted global asset mix (i.e. all the bonds and equities in the world). No portfolio has a theoretically better set of risk/return characteristics as this equilibrium portfolio. Thus, in a theoretical world, investors should own this market portfolio and simply add risk-free assets to it to create lower risk/lower reward portfolios, or leverage it if they wish to increase the risk of the portfolio beyond that of the market portfolio.

Corporate Warriors: The Rise of the Privatized Military Industry
by Peter Warren Singer
Published 1 Jan 2003

"Threat of Terror Abroad Isn't New for Oil Companies like Occidental," Wall Street JournaL February 7, 2002; Alfredo Rangel Suarez, "Parasites and Predators: Guerillas and the Insurrection Economy of CAy\omh'vA," Journal of International Affain33, no. 2 (Spring 2000): 577-O01: Nancy Dunne. "Dope Wars (Part II): Crackdown on Colombia," Financial Times, August C), 2000. 26. Jimmy Burns, "Corporate Security: Anxiety Stirred by Anti-Western Sentiment," Financial Times. April l l, 2002. 27. "Corporate Security: Risk Returns," Economist, November 20. 1999. 28. "Risky Returns: Doing Business in Chaotic and Violent Countries,'* The Economist, November 20, lcjcjg. 2C). The new nature of warfare has meant that this presence of mining and lucrative returns will often be intimately connected with the potential for conflict, as noted in chapter 4. 30.

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Natural Resources, and Violent Political Economies." Social Science Forum, March 21, 2000. Available at http://www.social-science-iorum.org/ new_page_27.htm. This contract, in turn, was guaranteed by loans from the \S.S. government and the World Bank. NOTES TO PAGES 82-89 32. "Corporate Security: Risk Returns." 33- www.airpartner.com. Another competitor is International SOS, a firm that offers global medical assistance, www.internationalsos.com. 34. Herbst. "The Regulation of Private Security Forces," p. 125. 35. Correspondence with the firm Frost & Sullivan. 36. Anna Leander, "Global Ungovemance: Mercenaries, States and the Control over Violence."

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Military Posture for the Post-Cold War Era. Project on Defense Alternatives Briefing Report 9, March 1, 1998. Contamine, Phillipe. War in the Middle Ages. New York: Basil Blackwell, 1984. g26 BIBLIOGRAPHY Copetas, Craig. "It's Off to War Again for Big U.S. Contractor." Wall Street Join nal, April 4, 1999, p. A21. "Corporate Security: Risk Returns." The Economist, November 20, lyyy. Coney, Stan. "The Business of Cybersecurity—the War Against Privacy?" Australian Broadcasting Corporation, August 20, 2000. http://www.abc.net.au/rn/talks/ bbing/siOyi io.htm Croatian Foreign Press Bureau. Daily Bulletin, July 15, 1996. Cross, Tim. "Logistic Support for UK Expeditionaiy Operations."

Debunking Economics - Revised, Expanded and Integrated Edition: The Naked Emperor Dethroned?
by Steve Keen
Published 21 Sep 2011

These investments give the highest return and the lowest risk possible. Any other combination that is not on the edge of the cloud can be topped by one farther out that has both a higher return and a lower risk.12 If this were the end of the matter, then the investor would choose the particular combination that coincided with their preferred risk–return trade-off, and that would be that. 11.3 Investor preferences and the investment opportunity cloud However, it’s possible to combine share-market investments with a bond that has much lower volatility, and Sharpe assumed the existence of a bond that paid a very low return, but had no risk.

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This portfolio was represented by a straight line linking the riskless bond with a selection of shares (where the only selection that made sense was one that was on the Investment Opportunity Curve, and tangential to a line drawn through the riskless bond). Sharpe called this line the ‘capital market line’ or CML (ibid.: 425). 11.4 Multiple investors (with identical expectations) With borrowing, the investor’s risk–return preferences no longer determined which shares he bought; instead, they determined where he sat on the CML. An ultra-conservative investor would just buy the riskless bond and nothing else: that would put him on the horizontal axis (where risk is zero) but only a short distance out along the horizontal axis – which means only a very low return.

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With these handy assumptions under his belt, the problem was greatly simplified. The riskless asset was the same for all investors. The IOC was the same for all investors. Therefore all investors would want to invest in some combination of the riskless asset and the same share portfolio. All that differed were investor risk–return preferences. Some would borrow money to move farther ‘northeast’ (towards a higher return with higher risk) than the point at which their indifference map was tangential to the IOC. Others would lend money to move ‘southwest’ from the point of tangency between their indifference map and the IOC, thus getting a lower return and a lower risk.

Market Sense and Nonsense
by Jack D. Schwager
Published 5 Oct 2012

See Minimum acceptable return (MAR) ratio Marcus, Michael Margin Margin calls Marginal production loss Market bubbles Market direction Market neutral fund Market overvaluation Market panics Market price delays and inventory model of Market price response Market pricing theory Market psychology Market risk Market sector convertible arbitrage hedge funds and CTA funds hidden risk long-only funds market dependency past and future correlation performance impact by strategy Market timing skill Market-based risk Maximum drawdown (MDD) Mean reversion Mean-reversion strategy Merger arbitrage funds Mergers, cyclical tendency Metrics Minimum acceptable return (MAR) ratio and Calmar ratio Mispricing Mocking Monetary policy Mortgage standards Mortgage-backed securities (MBSs) Mortgages Multifund portfolio, diversified Mutual fund managers, vs. hedge fund managers Mutual funds National Futures Association (NFA) Negative returns Negative Sharpe ratio, and volatility Net asset valuation (NAV) Net exposure New York Stock Exchange (NYSE) Newsletter recommendation NINJA loans Normal distribution Normally distributed returns Notional funding October 1987 market crash Offsetting positions Option ARM Option delta Option premium Option price, underlying market price Option timing Optionality Out-of-the-money options Outperformance Pairs trading Palm Palm IPO Palm/3 Com Past high-return strategies Past performance back-adjusted return measures evaluation of going forward with incomplete information visual performance evaluation Past returns about and causes of future performance hedge funds high and low return periods implications of investment insights market sector past highest return strategy relevance of sector selection select funds and sources of Past track records Performance-based fees Portfolio construction principles Portfolio fund risk Portfolio insurance Portfolio optimization past returns volatility as risk measure Portfolio optimization software Portfolio rebalancing about clarification effect of reason for test for Portfolio risks Portfolio volatility Price aberrations Price adjustment timing Price bubble Price change distribution The price in not always right dot-com mania Pets.com subprime investment Pricing models Prime broker Producer short covering Professional management Profit incentives Pro-forma statistics Pro-forma vs. actual results Program sales Prospect theory Puts Quantitative measures beta correlation monthly average return Ramp-up period underperformance Random selection Random trading Random walk process Randomness risk Rare events Rating agencies Rational behavior Redemption frequency notice penalties Redemption liquidity Relative velocity Renaissance Medallion fund Return periods, high and low long term investment S&P performance Return retracement ratio (RRR) Return/risk performance Return/risk ratios vs. return Returns comparison measures relative vs. absolute objective Reverse merger arbitrage Risk assessment of for best strategy and leverage measurement vs. failure to measure measures of perception of vs. volatility Risk assessment Risk aversion Risk evaluation Risk management Risk management discipline Risk measurement vs. no risk measurement Risk mismeasurement asset risk vs. failure to measure hidden risk hidden risk evaluation investment insights problem source value at risk (VaR) volatility as risk measure volatility vs. risk Risk reduction Risk types Risk-adjusted allocation Risk-adjusted return Risk/return metrics Risk/return ratios Rolling window return charts Rubin, Paul Rubinstein, Mark Rukeyser, Louis S&P 500, vs. financial newsletters S&P 500 index S&P returns study of Sasseville, Caroline Schwager Analytics Module SDR Sharpe ratio Sector approach Sector funds Sector past performance Securities and Exchange Commission (SEC) Select funds, past returns and Selection bias Semistrong efficiency Shakespearian monkey argument Sharpe ratio back-adjusted return measures vs.

All About Asset Allocation, Second Edition
by Richard Ferri
Published 11 Jul 2010

Investments that were once noncorrelated may become correlated in the future, and vice versa. Past correlations are a hint to future correlations, but not a reliable hint. Don’t trust any research report or book that says, “The correlation between asset class 1 and asset class 2 is X,” because by the time those words are printed, the correlation may have changed. The future risks, returns, and asset-class correlations cannot be known with any degree of certainty. Consequently, a perfect blend can never be known in advance. 3. During a time of extreme volatility when you want low correlation among asset classes, positive correlation can increase dramatically across all asset classes.

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A FINAL WORD ABOUT MULTI-ASSETCLASS INVESTING There are several ways to select a multi-asset-class portfolio. One way is to answer a few questions on a questionnaire and feed those answers into a computer. The problem with this approach is that the computer is purely mathematical and relies too much on past risks, returns, and correlations. Basically, the computer simulation assumes that whatever happened in past is the most probable scenario for the future. This is an extremely unreliable way to make investment decisions. The world is constantly changing, and no computer simulation can accurately predict the changes that will occur or how these changes will affect a portfolio. 82 CHAPTER 4 In addition, a computer does not know who you are and cannot assess your personality profile so that the allocation it recommends truly fits your needs.

Mathematics of the Financial Markets: Financial Instruments and Derivatives Modelling, Valuation and Risk Issues
by Alain Ruttiens
Published 24 Apr 2013

Tim BOLLERSLEV, “Generalized autoregressive conditional heteroskedasticity”, Journal of Econometrics, 31(3), (1986), pp. 307–327. 9. Tim BOLLERSLEV, Glossary to ARCH (GARCH), CREATES, School of Economics and Management, University of Aarhus, Denmark, 2008, working paper. 10. E. GHYSELS, P. SANTA-CLARA, R. VALKANOV, “There is a risk-return trade-off after all”, Journal of Financial Economics, vol. 76, 2005, pp. 509–548. 10 Option pricing in general 10.1 INTRODUCTION TO OPTION PRICING An option is a contract granting: the right to its holder, the option buyer – but the obligation to its issuer, the seller, to negotiate, that is, either to buy (call option) or to sell (put option), if the option buyer exercises its right, at a price, fixed in advance and called the exercise price or strike price some quantity of underlying instrument (stock, currency, bond, etc.), at a given maturity date or until a given maturity date: in the first case, one refers to a European option, in the second, to an American option.

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But more and more market participants, like hedge funds, traded these securities in a pseudo-arbitrage way, by combining for example a long position in CB with a short position in equivalent regular bond and call option, so that the market liquidity increased significantly, contributing to make disappear the price anomalies and related pseudo-arbitrage operations. So that, today, funds active on the CB market are more traditionally playing with the traditional advantages of the product, namely offering an intermediate risk/return profile between bonds and stocks, with some opportunities to play the volatility. Before looking after CB pricing, we need to specify some typical parameters of CBs. These will be illustrated with the following CB issue, in EUR: CB issue: DELHAIZE 2.75% 2009 (5 years) coupon: 2.75% (annual) issued amount: EUR 300 M denomination: EUR 250 000 issuing date: 30 April 2004 maturity date: 30 April 2009 conversion date: 24 April 2009 issuing price: 100% redemption amount: 100% conversion price: EUR 57.00 conversion ratio: 4385.9649 per EUR 250 000 call protection: Hard Call 3 years (until 15 May 2007) stock price at issuance date: EUR 40.50 Conversion Ratio For a given nominal value (i.e., a portion of the issued nominal amount), conversion ratio = number of ordinary shares offered in case of conversion “Hard” Call Protection CBs are generally issued with a period during which the issuer cannot early redeem his bond.

A Demon of Our Own Design: Markets, Hedge Funds, and the Perils of Financial Innovation
by Richard Bookstaber
Published 5 Apr 2007

Even with Hilibrand’s efforts, over time it became increasingly difficult to execute a trade without that trade revealing the new opportunity, and then before long the opportunity would vanish. 112 ccc_demon_097-124_ch06.qxd 7/13/07 2:43 PM Page 113 LT C M R I D E S THE LEVERAGE CYCLE TO HELL While opaqueness may have actually been beneficial in normal times, it was a different story when the firm was on the ropes. Short-term lenders have a stunted sense of risk-return trade-offs. Unlike commercial banks, whose creditors can look to the Federal Deposit Insurance Corporation (FDIC) or to the “too big to fail” doctrine, securities firms have no declared sugar daddy to deter runs. It is not a matter of simply paying a higher price if lenders perceive that their capital is at risk.

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It would be like opening up a program to study all objects made of materials other than wood, or initiating research on contemporary history for every country but France. You could do so, but I don’t know how that study would be much different from simply having a study of all materials or of all modern history. In fact, the proper study of hedge funds cannot be differentiated from a general study of investments. Issues of risk, return, and liquidity apply to all hedge fund strategies, and indeed to the whole range of possible investments. Consider the following scan of articles from various issues of the Journal of Alternative Investments, just one of a number of journals on hedge funds: “Currency Market Trading Performance”; “Timber Investment”; “Current Attitudes to Private Equity”; “Convertible Arbitrage: A Manager’s Perspective”; “Macro Trading and Investment Strategies”; “Commodity Trading Advisor Survey”; “Stock Selection in Eastern European Markets”; “Market Neutral versus Long/Short Equity”; “Merger Arbitrage: Evidence of Profitability”; “Analysis of Real Estate Investments in the U.S.”; “Benefits of International Small Cap Stocks.”

The Little Book That Builds Wealth: The Knockout Formula for Finding Great Investments
by Pat Dorsey
Published 1 Mar 2008

The short answer is “very carefully.” The long answer is that it takes practice and a fair amount of trial and error to become skilled at identifying undervalued stocks, but I think the following five tips will give you better odds of success than most investors. 1. Always remember the four drivers of valuation: risk, return on capital, competitive advantage, and growth. All else being equal, you should pay less for riskier stocks, more for companies with high returns on capital, more for companies with strong competitive advantages, and more for companies with higher growth prospects.Bear in mind that these drivers compound each other.

Red-Blooded Risk: The Secret History of Wall Street
by Aaron Brown and Eric Kim
Published 10 Oct 2011

The sports bettor types were the best at analyzing the data to determine what should happen, but they were often lousy at communicating it in a way traders could use. You can’t explain to a trader that, say, he should be willing to leave bigger positions open over a weekend because he had a greater risk-return ratio on those trades than on intraday or intraweek trades. That’s like telling a basketball player he missed more free throws long than short, so in future he should aim a foot in front of the basket instead of at the basket. Your observation might be true statistically, but your advice will just mess up his whole shot.

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It’s something the risk manager usually exploits privately, by giving the green light to projects that take advantage of it. People know the risk manager approves some projects and vetoes others, but they seldom ask why. If someone does ask, she is usually satisfied with “It was too risky” if the answer was no, and “It had a risk-return trade-off within our appetite” if the answer was yes. People don’t like long discussions about risk. Adding pure artificial risk to things is the hardest of the three unspeakable truths to explain, and in my experience it is the least known outside the profession. There is a tendency in large organizations to standardize everything.

The Myth of the Rational Market: A History of Risk, Reward, and Delusion on Wall Street
by Justin Fox
Published 29 May 2009

They followed the 150-year-old “Prudent Man” rule, a legal doctrine that instructed trustees of others’ money to “observe how men of prudence, discretion, and intelligence manage their own affairs” and conduct themselves accordingly.7 This had long been long interpreted to mean that trustees should stick the money in their charge in high-grade bonds and maybe a few blue-chip stocks. That approach was sorely tested in the 1960s, when imprudent investors seemed to be having all the fun and making all the money. It was tested even more in the 1970s, when neither bonds nor blue chips proved safe, leaving a big opening for the new approach to risk, return, and diversification that was introduced two decades before by Harry Markowitz. In this view it wasn’t the riskiness of an individual stock or bond that mattered, but the way it fit in to a portfolio. By the mid-1970s, this approach had a name—modern portfolio theory—and was beginning to make slight inroads in the institutional investing world.

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Jensen, ed., Studies in the Theory of Capital Markets (New York: Praeger, 1972), Black, Jensen, and Scholes found that low-beta stocks had higher returns than predicted by the original CAPM, but that the relationship between beta and returns seemed to fit an asset-pricing model in which borrowing limits and costs were taken into account. Meanwhile, Fama and James D. MacBeth, in “Risk, Return, and Equilibrium: Empirical Tests,” Journal of Political Economy (May–June 1973), concluded that “although there are ‘stochastic nonlinearities’ from period to period,” they could “not reject the hypothesis that in making a portfolio decision, an investor should assume that the relationship between a security’s portfolio risk and its expected return is linear” as CAPM implied. 31.

Expected Returns: An Investor's Guide to Harvesting Market Rewards
by Antti Ilmanen
Published 4 Apr 2011

Chapter 15 concluded that pure volatility risk may not be well rewarded because, while index option selling has been profitable, single-stock option selling has not. A correlation risk premium seems better than a volatility risk premium at explaining index option richness. Given the tradeoff between reward and risk, what would be more natural than to find a positive relation between expected volatility and expected returns? • While a positive risk–return relation tends to work in long-run average returns across asset classes (recall Figure 2.1), cross-sectional relations within asset classes, surprisingly, have the opposite pattern. High-volatility stocks underperform low-volatility stocks, long-duration bonds underperform shorter ones, and credit risk taking at long maturities likewise may earn a negative reward.

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Lo; and Igor Makarov (2004), “An econometric model of serial correlation and illiquidity in hedge-fund returns,” Journal of Financial Economics 74, 529–609. Ghayur, Khalid; Ronan G. Heaney; Stephen A. Komon; and Stephen C. Platt (2010), Active Beta Indexes: Capturing Systematic Sources of Active Equity Returns, Hoboken, NJ: John Wiley & Sons, Inc. Ghysels, Eric; Pedro Santa-Clara; and Rossen Valkanov (2005), “There is a risk–return tradeoff after all,” Journal of Financial Economics 76, 509–548. Gibson, Rajna; and Songtao Wang (2010), “Hedge fund alphas: Do they reflect managerial skills or mere compensation for liquidity risk bearing?” Swiss Finance Institute research paper 08-37. Giesecke, Kay; Francis A. Longstaff; Stephen Schaefer; and Ilya Strebulaev (2010), “Corporate bond default risk: A 150-year perspective,” UCLA working paper.

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Lopez de Silanes, Florencio; Ludovic Phalippou; and Oliver Gottschalg (2009), “Giants at the gate: Diseconomies of scale in private equity,” working paper, available at SSRN: http://ssrn.com/abstract=1363883 Lustig, Hanno; and Adrien Verdelhan (2007), “The cross-section of foreign currency risk premia and US consumption growth risk,” American Economic Review 97(1), 89–117. Lustig, Hanno; and Adrien Verdelhan (2010), “Business cycle variation in the risk–return tradeoff,” UCLA working paper. Ma, Cindy; and Andrew MacNamara, (2009), “The price of illiquidity: Valuation approaches across asset classes,” Houlihan Lokey research report. Macaulay, Frederick (1938), The Movements of Interest Rates, Bond Yields and Stock Prices in the United States since 1856, New York: National Bureau of Economic Research.

Working the Street: What You Need to Know About Life on Wall Street
by Erik Banks
Published 7 Feb 2004

Bad markets, lack of transaction flow, some bad trades, or a few lost deals can spell the end of a producer’s career. That’s not necessarily true of staffers, who are generally much more insulated, living a bit farther away from the edge of the precipice. Someone still has to keep the books, do the audits, and look after the technology, regardless of how business is faring. So it follows from the risk/return equation we talked about earlier that the relative lack of job security commands a higher risk premium—payable in the form of a larger bonus. Remember, there can be no “free lunch.” If you want more return, you have to take more risk. But there actually is a bit of a free lunch out there. Though it’s true that producers earn more than staffers, an excellent staffer can earn more than a mediocre producer, and sometimes almost as much as a good producer.

Investing to Save the Planet: How Your Money Can Make a Difference
by Alice Ross
Published 19 Nov 2020

One reason that it could be unsuitable for venture capitalists, according to the report, is that such investors have a typical time horizon of between three and five years to make their money back, and thus are impatient for technology to be developed and scaled up faster. The correct lesson from the failure of cleantech between 2006 and 2011 is that it ‘clearly does not fit the risk, return, or time profiles of traditional venture capital investors. And as a result, the sector requires a more diverse set of actors and innovation models.’ Breakthrough Energy, with its ‘patient capital’ approach, is one such model. Institutional investors like pension funds and sovereign wealth funds, which can wait for decades to make returns but are often inexperienced technology investors, are another source.

Triumph of the Optimists: 101 Years of Global Investment Returns
by Elroy Dimson , Paul Marsh and Mike Staunton
Published 3 Feb 2002

The Sharpe ratio is defined in terms of excess Triumph of the Optimists: 101 Years of Global Investment Returns 112 returns in recognition of the fact that investors can blend an investment in equities with lending or borrowing at the interest rate to achieve any desired level of risk. To illustrate use of the Sharpe ratio, we compare the risk/return trade-off for US equities versus the world index. From 1900–2000, US real equity returns had a standard deviation of 20.16 percent per year, versus 17.04 percent for the world portfolio (see Table 8-2). A US investor could have achieved the same risk as on the world portfolio by starting each year with a proportion 17.04/20.16 = 84.5 percent in US equities and the remaining 15.5 percent in risk free bills.

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We should not generalize from this, however, and over the second half-century from 1950–2000, both US bond and equity investors would have gained significantly from investing worldwide. Many textbooks give a misleading impression of the gains from international diversification by presenting ex post efficient frontiers of the risk-return tradeoff based on hindsight about returns. Sadly, we can usually spot the high-return, low-risk markets only after the event, and past performance is a poor guide to the future. So looking ahead, and while we know there is no guarantee, our best guess is that international investment will offer a higher reward for risk than domestic investment, because of the risk reduction from diversification.

Economics Rules: The Rights and Wrongs of the Dismal Science
by Dani Rodrik
Published 12 Oct 2015

And it didn’t hurt that these views were shared by some of the top economists in government, such as Larry Summers and Alan Greenspan. In sum, economists (and those who listened to them) became overconfident in their preferred models of the moment: markets are efficient, financial innovation improves the risk-return trade-off, self-regulation works best, and government intervention is ineffective and harmful. They forgot about the other models. There was too much Fama, too little Shiller. The economics of the profession may have been fine, but evidently there was trouble with its psychology and sociology. Errors of Commission: The Washington Consensus In 1989, John Williamson convened a conference in Washington, DC, for major economic policy makers from Latin America.

Why Stock Markets Crash: Critical Events in Complex Financial Systems
by Didier Sornette
Published 18 Nov 2002

A Working Hypothesis 27 27 30 33 The Basics Price Trajectories Return Trajectories Return Distributions and Return Correlation 38 The Efficient Market Hypothesis and the Random Walk The Random Walk 38 vi contents 42 45 A Parable: How Information Is Incorporated in Prices, Thus Destroying Potential “Free Lunches” Prices Are Unpredictable, or Are They? 47 Risk–Return Trade-Off Chapter 3 49 What Are “Abnormal” Returns? financial crashes are “outliers” 49 51 51 54 Drawdowns (Runs) Definition of Drawdowns Drawdowns and the Detection of “Outliers” Expected Distribution of “Normal” Drawdowns 56 60 60 62 65 69 70 73 75 Chapter 4 positive feedbacks 81 Drawdown Distributions of Stock Market Indices The Dow Jones Industrial Average The Nasdaq Composite Index Further Tests The Presence of Outliers Is a General Phenomenon Main Stock Market Indices, Currencies, and Gold Largest U.S.

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Preserving the same qualitative pattern, during the 1897–1997 DJIA period, the weekly decline (rise) probability is 43.98% (55.87%). For the Nasdaq from 1962 to 1995, the daily decline (rise) probability is 46.92% (52.52%). For the IBM stock from 1962–1996, the daily decline (rise) probability is 47.96% (48.25%). RISK–RETURN TRADE-OFF One of the central insights of modern financial economics is the necessity of some trade-off between risk and expected return, and although Samuelson’s version of the efficient markets hypothesis places a restriction on expected returns, it does not account for risk in any way. In particular, if a security’s expected price change is positive, it may be just the reward needed to attract investors to hold the asset and bear the associated risks.

A Failure of Capitalism: The Crisis of '08 and the Descent Into Depression
by Richard A. Posner
Published 30 Apr 2009

The pooling of the mortgages that backed each security diversified the risk of default geographically and thus reduced it; a rise in defaults in Florida might be offset by a decline in defaults in New York. So far, so good, as far as management of risk was concerned. In addition, each security was sliced into different risk-return combinations and a purchaser could pick the one he wanted. (In other words, shares in each security were sold.) The top tier would have the first claim on the income generated by the pool of mortgages that backed the security, and so it had the highest credit rating and paid the lowest interest rate.

The Wisdom of Finance: Discovering Humanity in the World of Risk and Return
by Mihir Desai
Published 22 May 2017

The reason that the logic of diversification, the capital asset pricing model, and the idea of betas matches the Aristotelian taxonomy of relationships is that the underlying portfolio problem is the same. In finance, we are trying to figure out how to invest our assets and manage toward the best risk-return tradeoff. In life, we are trying to figure out how to allocate our time and energies across many people. It also matches because the underlying logic of insurance is present in both settings. For me, this parallel prompted several questions: Am I providing insurance to my loved ones and friends?

The Future of Money: How the Digital Revolution Is Transforming Currencies and Finance
by Eswar S. Prasad
Published 27 Sep 2021

A US investor who has an account at a financial services firm such as Fidelity or Vanguard can simply buy an international index fund offered by those brokerages. Investment managers at those funds manage the foreign investments so all that an investor has to do is pick a fund that gives her the diversification she is looking for. Of course, there are risk-return trade-offs even among international funds. Investing in an emerging market fund could yield higher returns but is also riskier; by contrast, investing in advanced economy government bonds is safe but typically yields low returns. International index funds are readily available to all US investors, although fees and minimum investment amounts can deter investors who might have limited funds.

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This proposition holds independently of where in the world the investor lives, although factors such as the tax laws in their country regarding domestic and foreign investments could influence the structure of this desirable portfolio. Investors in fact exhibit extensive home bias—they tend to heavily favor investments in their domestic stock markets rather than diversifying their portfolios. In principle, they could do far better to improve the risk-return trade-off of their portfolios through international diversification. In plainer language, judiciously buying stock in companies around the world, or simply investing in financial products that track other countries’ stock market indexes, would allow investors to attain higher average returns over a long period for a given degree of risk.

The Only Game in Town: Central Banks, Instability, and Avoiding the Next Collapse
by Mohamed A. El-Erian
Published 26 Jan 2016

They are also at the basis of work on driverless cars, remote health diagnoses, and a lot more. But this is, in fact, far from a simple dichotomy. Yes, the phenomenon of a “race against the machines” is being felt in the labor market, the value of education, employment remuneration, and the composition of jobs in a modern economy.4 It is also altering the risk/return configuration for new investments, amplifying “winner takes all” effects. The more innovative the economy, the higher the turnover, and the greater the importance of safety nets. Moreover, the dual transformative forces of these innovations—enabling and displacing—come with the potential for both good and bad.

The Sport and Prey of Capitalists
by Linda McQuaig
Published 30 Aug 2019

So, it wasn’t really the case that Canada was the disadvantaged partner desperately hoping to seize this “once-in-a-generation opportunity” to solve a problem — a problem that may not even have existed. If anything, the shoe was on the other foot. It was institutional capital that was seeking a once-in-a-generation opportunity to earn high-yield, low-risk returns at a time when few such opportunities seemed to exist in the global marketplace. So, it actually looks more like it was “advantage Canada” in this multi-billion-dollar infrastructure sweepstakes. But you’d sure never know it from the report put out by this council of advisers, who highlight all the things Canada must do to attract institutional capital.

The Rise of Carry: The Dangerous Consequences of Volatility Suppression and the New Financial Order of Decaying Growth and Recurring Crisis
by Tim Lee , Jamie Lee and Kevin Coldiron
Published 13 Dec 2019

The volatility of this strategy is also modest at just under 5 percent per year, similar to a 5-year Treasury bond. The ratio of these two figures—what asset managers call the information ratio (IR)—is around 0.4. This combination of a solid IR but low absolute returns presents asset managers with a conundrum. The risk-return trade-off appears good, but the strategy does not generate high enough levels of absolute returns. The “solution” is often to apply more leverage. This can generate higher abso- THE RISE OF CARRY 50 lute returns but, of course, comes with the trade-off of potentially much higher risk. In order to provide a set of returns that we can compare with familiar asset classes, we chose a leverage level of 1,000 percent ($5 short and $5 long for every $1 of capital).

The Heart of Business: Leadership Principles for the Next Era of Capitalism
by Hubert Joly
Published 14 Jun 2021

In its 2020 annual letter to CEOs, BlackRock head Larry Fink explained that climate change, in particular, creates investment risks. “Climate change,” he wrote, “has become a defining factor in companies’ long-term prospects […] Our investment conviction is that sustainability- and climate-integrated portfolios can provide better adjusted-risk returns to investors.”8 Business leaders, nongovernmental organizations (NGOs), and academics surveyed by the World Economic Forum in its 2020 Global Risks Report ranked the failure to mitigate and adapt to climate change as the top threat facing the world over the next 10 years.9 Shareholders’ expectations are shifting because investors themselves are not soulless entities unable to lift their gaze past the next quarterly results.

Buy Then Build: How Acquisition Entrepreneurs Outsmart the Startup Game
by Walker Deibel
Published 19 Oct 2018

If it goes wrong you could end up bankrupt, upside down on your investment, and divorced. Further, selling a privately held company is not quick and easy like a publicly traded stock. It’s critical you understand the risks. The ROI on small business ownership can be great, but just how risky is small business acquisition? 25 MARGIN OF SAFETY Risk is relative. The risk-return spectrum dictates that the more risk an investor takes the greater the return needs to be. Unfortunately, the “high risk, high return” model frequently plays out in the high-risk part winning out and 24 producing lower returns. Warren Buffett, widely considered one of the most successful investors in the world, practices what’s called value investing.

Simple Rules: How to Thrive in a Complex World
by Donald Sull and Kathleen M. Eisenhardt
Published 20 Apr 2015

One recent study of alternative investment approaches pitted the Markowitz model and three extensions of his approach against the 1/N rule, testing them on seven samples of data from the real world. This research ran a total of twenty-eight horseraces between the four state-of-the-art statistical models and the 1/N rule. With ten years of historical data to estimate risk, returns, and correlations, the 1/N rule outperformed the Markowitz equation and its extensions 79 percent of the time. The 1/N rule earned a positive return in every test, while the more complicated models lost money for investors more than half the time. Other studies have run similar tests and come to the same conclusions.

Exodus: How Migration Is Changing Our World
by Paul Collier
Published 30 Sep 2013

High-income countries have a manifest interest in the success of postconflict situations: in recent decades the costs of trying to shore them up have been stupendous. Historically, close to half of them have reverted to violence, so if migration policy can be helpful, it is sensible to make it so. However, if restrictions on immigration from the country are tightened once peace has been restored, those who fled during conflict may be less inclined to risk return: will they be able to get back if necessary? The right time to adopt migration policies that would be helpful in postconflict situations is during the conflict. Both from the perspective of the duty of rescue, and to help preserve the country’s human capital from violence, during conflict a migration policy needs to be exceptionally generous.

Quit Like a Millionaire: No Gimmicks, Luck, or Trust Fund Required
by Kristy Shen and Bryce Leung
Published 8 Jul 2019

Expected return, measured as a percentage, is the expected annualized return of an asset. Volatility, measured as a standard deviation, is the day-to-day gyration of said asset. The higher the standard deviation, the more volatile the asset. Let’s take two assets: equities, as represented by the S & P 500, and bonds. If we were to plot the risk/return numbers of these two assets, it would look like this: On the vertical axis is expected return, and on the horizontal axis is standard deviation. The S & P 500’s position at the top right indicates that it’s a high-return, highly volatile asset, while bonds, on the bottom left, are lower return and less volatile.

Finding Alphas: A Quantitative Approach to Building Trading Strategies
by Igor Tulchinsky
Published 30 Sep 2019

In the case of bad news, if a mispricing is detected, the fund manager can go long the equity and short the bond. Another way to play the same trade is to use CDSs instead of bonds: the fund manager can go long equity and buy undervalued CDS protection. There are many ways to construct the same trade, and it is up to the fund manager to conduct due diligence to find the one with the best risk-return profile. A second type of capital structure arbitrage involves finding mispricings between different categories of debt (for example, senior versus junior, secured versus unsecured, and bank loans versus bonds). During periods of stress or financial distress for the issuer company, discrepancies will occur in the relative prices of these debt instruments.

Restarting the Future: How to Fix the Intangible Economy
by Jonathan Haskel and Stian Westlake
Published 4 Apr 2022

And still others involve using cryptocurrencies to finance new businesses or new organisational structures like special purpose acquisition companies. Some of these products look like unimpeachably valuable financial innovations, connecting willing providers of capital to willing firms. Others look more questionable. Some critics have claimed that some consumer bonds and crowdfunding issues offer bad risk–return trade-offs to investors too naive to know better. In addition, some crowdfunding leverages investors’ goodwill towards a particular type of business to provide capital at a submarket rate. It is no coincidence that some subsectors with ferociously passionate customers, such as microbreweries and CrossFit gyms, are disproportionate users of crowdfunding.

Please Report Your Bug Here: A Novel
by Josh Riedel
Published 17 Jan 2023

I scrolled through the documentation on Portals in our internal wiki, trying to make sense of what was happening. The wiki included a live feed of feedback from various employees. A major known issue with the Portals app, in its private alpha stage, was that you could not bring anything back. Users had to return with only what they brought—yourself and what you packed, no souvenirs—or else risk returning with damaged goods. Certain employees, however, ignored this rule. A product designer, a fashionable guy who never wore the same pair of sneakers twice, was horrified one day to spot three of his colleagues in the same shoes he was wearing. “Where’d you find those?” he asked. “We got them on our lunch break, at that shop in Shoreditch you told us about,” his colleague answered.

The Bogleheads' Guide to Investing
by Taylor Larimore , Michael Leboeuf and Mel Lindauer
Published 1 Jan 2006

The mutual fund prospectus is the single best way to find out about the objectives, costs, past performance figures, and other important information about any mutual fund you're considering investing in. Although reading a prospectus may cause your eyes to glaze over, it's a very important step to help you determine if a particular fund satisfies your investment objectives (risk, return, etc.). Since you are planning on investing for the long-term (you are, aren't you?), reading a prospectus and understanding what you're investing in will be well worth the time and effort. We can't emphasize it enough: Read the fund's prospectus and understand what you re investing in! There are at least 10 advantages of investing in mutual funds: 1.

Refuge: Transforming a Broken Refugee System
by Alexander Betts and Paul Collier
Published 29 Mar 2017

This was a reaction to the immediate antecedent to UNHCR – the UN relief and rehabilitation agency, operational between 1943 and 1946. That agency had indeed sought to facilitate repatriation. But in 1947 the US terminated the agency and briefly created its own International Relief Organization (IRO) with a focus on resettling those who risked return to the East. Its condition for backing the embryonic UNHCR regime was that it too held this focus on nonreturn to persecution.3 Other governments had different goals that were also the result of their particular interests, but these were largely thwarted. Against the US position, the refugee-hosting countries of Western Europe wanted UNHCR to operationally provide material assistance to populations on their territories.

The End of Theory: Financial Crises, the Failure of Economics, and the Sweep of Human Interaction
by Richard Bookstaber
Published 1 May 2017

“Intertemporal Asset Pricing under Knightian Uncertainty.” Econometrica 62, no. 2: 283–322. doi: 10.2307/2951614. Evans, George W., and Seppo Honkapohja. 2005. “An Interview with Thomas J. Sargent.” Macroeconomic Dynamics 9, no. 4: 561–83. doi: 10.1017/S1365100505050042. Fama, Eugene F., and James D. MacBeth. 1973. “Risk, Return, and Equilibrium: Empirical Tests.” Journal of Political Economy 81, no. 3: 607–36. http://www.jstor.org/stable/1831028. Farmer, J. Doyne. 2002. “Market Force, Ecology and Evolution.” Industrial and Corporate Change 11, no. 5: 895–953. doi: 10.1093/icc/11.5.895. Farmer, J. Doyne, and John Geanakoplos. 2009.

The Age of Stagnation: Why Perpetual Growth Is Unattainable and the Global Economy Is in Peril
by Satyajit Das
Published 9 Feb 2016

The shadow banking system, a network of bank-like financing vehicles and investment funds created by banks to circumvent regulation, added to the problem. In a version of the financial shell game, banks shuffled assets to these vehicles so as to reduce capital and boost returns. In theory, banks were not exposed to potential losses from these transactions. In practice, the risk returned to the banks under certain conditions, especially if the ability of the vehicles to raise money was impaired, exposing banks to large losses. Further adding to the problem was the conflict of interest between: banks and rating agencies; investment managers and their institutional clients; and bonus-driven traders and the managers and shareholders of banks.

The End of Accounting and the Path Forward for Investors and Managers (Wiley Finance)
by Feng Gu
Published 26 Jun 2016

Record the progress over recent periods in the success of products under development in clinical tests, the number of products/devices in advanced state (Phase III clinical tests, FDA review), the extent of diversification of the development portfolio across therapeutic areas (an important risk measure), and the total size of the market for the main drugs under development (growth potential). These product-development dimensions provide a thorough risk–return profile of the major strategic asset of pharma companies. Regarding products already on the market: consider their therapeutic market share (e.g., HIV drugs) and the patent duration (time to expiration) of the leading drugs. These are the major indicators of the sustainability of the on-the-market drug portfolio.

Concentrated Investing
by Allen C. Benello
Published 7 Dec 2016

In fact, the reader will probably be quite surprised by how large the bets can be calculated to be. Once again, placing bets of significant size depends on appropriately skewed probabilities, and these types of probabilities are uncommon, but both the mathematics and the investors argue for large bets when situations with unusual risk/return arise. It is important to note that the risk referred to here is the risk of permanent loss of capital and not the more commonly used academic metric of volatility. The investors in this book are willing to suffer through periods of temporary (but significant) loss of capital in an attempt to find opportunities where the probability of the permanent loss of capital is small.

Work Less, Live More: The Way to Semi-Retirement
by Robert Clyatt
Published 28 Sep 2007

Then the high-tech part comes in, with reams of computer-based simu­ lations of various combinations of assets over different time periods. These systems, known as Portfolio Optimizers, find a cluster of optimal blends for a portfolio or the best combinations of asset classes to achieve desired rates of risk and return—at least as seen through the rear-view mirror of historical returns. Depending on where you want to be in the risk/return tradeoff, choose your proportions of asset classes and, to extend the metaphor, create a perfect soup. But Portfolio Optimizers are not foolproof. They can point you in the right direction when choosing an optimal blend of asset classes, but they have foibles. First, optimizers can tell you only what the optimal mix was during past years.

Better, Stronger, Faster: The Myth of American Decline . . . And the Rise of a New Economy
by Daniel Gross
Published 7 May 2012

So I bit the bullet and bought subscriptions. The result: a savings of $748 while I received the same product, plus the benefit of time-saving delivery and digital access. That’s like buying a stock that doubles in a year and then pays a 124 percent annual dividend. Investments in energy efficiency carry even better risk-return-reward profiles. Like many Americans whose homes are blessed (or cursed) with a swimming pool, I’ve come to look forward to the summers with a certain amount of dread. A wave of ecoguilt washes over me each time the hiss of the propane-fueled water heater pierces the air. It is then replaced by nausea when the propane bill arrives.

Advances in Financial Machine Learning
by Marcos Lopez de Prado
Published 2 Feb 2018

Paper trading will take place for as long as it is needed to gather enough evidence that the strategy performs as expected. Graduation: At this stage, the strategy manages a real position, whether in isolation or as part of an ensemble. Performance is evaluated precisely, including attributed risk, returns, and costs. Re-allocation: Based on the production performance, the allocation to graduated strategies is re-assessed frequently and automatically in the context of a diversified portfolio. In general, a strategy's allocation follows a concave function. The initial allocation (at graduation) is small.

The Last Punisher: A SEAL Team THREE Sniper's True Account of the Battle of Ramadi
by Kevin Lacz , Ethan E. Rocke and Lindsey Lacz
Published 11 Jul 2016

The hasty patrol had me feeling alive. It was a nice change to get out of the conventional routine and do some real Frogman work. We had to walk this full patrol and do our best to find the lost KYK. If we didn’t find it, we’d turn around and that would be it. Losing a KYK is nothing to take lightly, but the risk-return ratio wasn’t going to hold together beyond the mission we were already running. About halfway to the building where Chris had shot the two guys on the moped, he halted the patrol and took a knee. Carefully, he raised his M4 and lased a target about one hundred meters ahead. “Hey, I got a guy moving with an AK, creeping around in the shadows,” Chris said over comms.

Systematic Trading: A Unique New Method for Designing Trading and Investing Systems
by Robert Carver
Published 13 Sep 2015

In principle my framework can deal equally well both with assets whose returns naturally have low standard deviations and those that are very risky. It can also cope with changes in volatility over time. However instruments which have extremely low risk like pegged currencies should be excluded. Firstly, when risk returns to normal it is liable to do so very sharply, potentially creating significant losses. Secondly, these positions need more leverage to achieve a given amount of risk, magnifying the danger when they do inevitably blow up. Even if you don’t use leverage they will limit the risk your overall trading system can achieve.74 Finally, they also tend to be more costly to trade, as you will discover in chapter twelve, ‘Speed and Size’.

The Devil's Derivatives: The Untold Story of the Slick Traders and Hapless Regulators Who Almost Blew Up Wall Street . . . And Are Ready to Do It Again
by Nicholas Dunbar
Published 11 Jul 2011

And suppose that the VAR system—the policing mechanism keeping the firm safe—said that the bet had low VAR and didn’t require much capital. Think for a moment about the relationship between traders and those who provide them with capital. As in any business, different traders compete for this capital by trying to offer the best risk-return proposition. If the bottleneck is a mechanism that defines how questions of risk should be addressed, then the winner in the struggle for capital will be the one who best plays that mechanism to their advantage. Presented with this incentive, traders gave statistics and economic theory a much warmer welcome on the trading floor.

Free Market Missionaries: The Corporate Manipulation of Community Values
by Sharon Beder
Published 30 Sep 2006

They would be less bolshie and more understanding of what management and owners are trying to achieve, as they would all be rewarded along similar lines.52 In its submission, BHP told the same inquiry that employees owned shares or options worth 7.6 per cent of the company’s capital and that its motivation in providing this opportunity was to help wage earners to understand and experience private enterprise; to justify ‘the profit motive in terms of risk return for investors’; and to encourage ‘employees to take a more active interest as co-owners of the company and for them to look beyond their local domain’. 53 Rob Donkersley, Employee Relations Director for Coca-Cola Amatil, told the inquiry about his company’s employee share ownership plan: We feel we have captured the minds of our employees through this plan.

Kill Chain: The Rise of the High-Tech Assassins
by Andrew Cockburn
Published 10 Mar 2015

In the drug business, pilots had been willing to fly cocaine base from Peru to Colombia for little reward because there was minimal risk. Once that risk went up, as it did when they started getting shot down, the reward for the pilots became insufficient, and they refused to fly. In the insurgency it was people who were working for the money, such as the men digging holes to bury the bombs, who were susceptible to increased risk. Returning to Washington, Rivolo briefed his superiors on his conclusions, bluntly suggesting that the “attack-the-leaders” strategy enjoying the highest priority was “completely unproductive.” Far better, he insisted, to concentrate on those lower down. Later, he would calculate the precise degree of risk involved in planting a bomb.

Bean Counters: The Triumph of the Accountants and How They Broke Capitalism
by Richard Brooks
Published 23 Apr 2018

‘You’ve got to be inside the industry and inside the thinking and inside the regulator’s mind, otherwise you can’t do the job,’ he insisted. ‘I feel really strongly about multi-disciplinary partnerships . . . Doing more than just audit [is] not just desirable but fundamental for audit quality because we might be auditing bank X but we might be doing risk returns or regulatory investigations for banks Y and Z. Without the ability to take an industry-wide view, to have the expertise in complex financial instruments and their accountancy treatment, our chances of auditing well and sceptically would be really low.’ It seemed not to matter that when put to the test in the years leading up to the financial crisis, this optimistic theory had failed spectacularly.

The Accidental Investment Banker: Inside the Decade That Transformed Wall Street
by Jonathan A. Knee
Published 31 Jul 2006

Second, young companies can do irreparable harm to themselves by going public too early. You (usually) only get to go public once. This is your chance to tell your story to the market, establish financial and operating metrics that you want to be judged by, and describe your strategic direction. A company that goes public before these elements are ready risks returning to the very investors who bought its stock in the IPO and saying, “Never mind.” It is almost impossible to recover credibility from this fundamental breach of trust. The number of “fallen angels”—highflying issues that fail to meet expectations and become penny stocks—that ever come back to life can be counted on one hand.

Why Startups Fail: A New Roadmap for Entrepreneurial Success
by Tom Eisenmann
Published 29 Mar 2021

Many aspiring entrepreneurs fail to consider the full range of financing alternatives available to them. Venture capital is the default, especially for graduates of elite MBA programs, where venture capital investors are lionized. But the pressure that comes with venture capital is not well suited for all businesses, nor is this risk/return profile suited for all entrepreneurs’ temperaments. For example, Quincy’s VCs pushed the founders to “swing for the fences,” saddling the startup with aggressive growth targets. Nelson recounted, “The investors advised us to keep a lot of inventory. They said stockouts were the worst thing that could happen to a retailer.

What's Next?: Unconventional Wisdom on the Future of the World Economy
by David Hale and Lyric Hughes Hale
Published 23 May 2011

FRAGILE STATES: States that fail to provide basic services to poor people because they are unwilling or unable to do so. FREE TRADE AREA: A group of countries within which tariffs and nontariff trade barriers between members are generally abolished. The group lacks a common trade policy toward nonmembers. FRONTIER MARKET: Emerging market countries with high volatility, low liquidity, and higher risk/return ratios that are not as prominent as major emerging market countries such as China and Brazil. GAAP (GENERALLY ACCEPTED ACCOUNTING PRINCIPLES): The common set of accounting principles, standards, and procedures that companies use to compile their financial statements. They are a combination of formal standards and traditional practices.

A Random Walk Down Wall Street: The Time-Tested Strategy for Successful Investing
by Burton G. Malkiel
Published 10 Jan 2011

Neither fundamental analysis of a stock’s firm foundation of value nor technical analysis of the market’s propensity for building castles in the air can produce reliably superior results. Even the pros must hide their heads in shame when they compare their results with those obtained by the dartboard method of picking stocks. Sensible investment policies for individuals must then be developed in two steps. First, it is crucially important to understand the risk-return trade-offs that are available and to tailor your choice of securities to your temperament and requirements. Part Four provided a careful guide for this part of the walk, including a number of warm-up exercises concerning everything from tax planning to the management of reserve funds and a life-cycle guide to portfolio allocations.

Nerds on Wall Street: Math, Machines and Wired Markets
by David J. Leinweber
Published 31 Dec 2008

The reason for this underweighting, rather than eliminating an unattractive stock completely, is because of index tracking risk. Totally eliminating a company increases the risk of the portfolio return differing substantially from the index if these forecasts are wrong and the stock moves in an opposite direction. The sizes of these decisions, called “active bets,” are constrained by the willingness to risk returns that stray from the index in either direction, in the hope of adding value by straying in a positive direction. 116 Nerds on Wall Str eet Constraints on Active Managers These constraints require active managers to keep a certain portion of their assets in an indexlike subportfolio, either by replication or by sampling, and to use the rest of the portfolio to make active bets trying to outperform the index.

Bad Money: Reckless Finance, Failed Politics, and the Global Crisis of American Capitalism
by Kevin Phillips
Published 31 Mar 2008

Kindleberger, Manias, Panics, and Crashes (New York: Harper Torchbooks, 1978), pp. 106, 254-56. 2 David Fromkin, Europe’s Last Summer (New York: Knopf, 2004), p. 168. 3 “The Loan Comes Due,” New York Times, August 5, 2007, Week in Review. 4 “Inside the Sub-prime Storm,” Schwab Investing Insights, August 16, 2007, p. 2. 5 “Risk Returns with a Vengeance,” Fortune, August 20, 2007; www.cnnmoney.com, August 21, 2007. 6 “Mortgage Fraud Is the Thing to Do Now,” Chicago Tribune, September 22, 2007; www.foreclosurepulse.com, July 12, 2007. 7 www.ml-implode.com. 8 Niall Ferguson, The Pity of War (New York: Basic Books, 1999), p. 192. 9 “Loan by Loan, the Making of a Credit Squeeze,” New York Times, Sunday Business, August 19, 2007. 10 S&P/Case-Shiller from “U.S.

Galactic North
by Alastair Reynolds
Published 14 Feb 2006

Just spewed out a lot more neutrons than normal, too much for the shielding to contain. Then it went into emergency shutdown mode. Some people were killed by the radiation but most died of the cold that came afterward.” “Hm. Except you.” Iverson nodded. “If I hadn't had to go back for that component, I'd have been one of them. Obviously, I couldn't risk returning. Even if I could have got the reactor working again, there was still the problem of the contaminant.” He breathed in deeply, as if steeling himself to recollect what had happened next. “So I weighed my options, and decided dying -- freezing myself -- was my only hope. No one was going to come from Earth to help me, even if I could have kept myself alive.

Market Risk Analysis, Quantitative Methods in Finance
by Carol Alexander
Published 2 Jan 2007

Most firms, especially financial firms, claim to have well-thought-out risk management policies, but few actually state trade-offs between risks and returns. Attention to risk limits may be unwittingly reinforced by regulators. Of course it is not the role of the supervisory authorities to suggest risk–return trade-offs; so supervisors impose risk limits, such as value at risk relative to capital, to ensure safety and xxii Foreword fair competition in the financial industry. But a regulatory limit implies severe penalties if breached, and thus a probabilistic constraint acquires an economic value.

Brazillionaires: The Godfathers of Modern Brazil
by Alex Cuadros
Published 1 Jun 2016

As he shook my hand, he effusively thanked me as if I personally had anything to do with the list. Then he launched straight into an attack on his own industry. He blamed his fellow bankers in the United States and Europe for the financial crisis. “The money people were making on Wall Street didn’t make sense,” he said. “It was too easy. Obviously the risk/return was imperfect. A guy would make millions and millions of dollars without running any personal risk. He would screw everything up, switch jobs, and not lose a thing. It can’t be like this.” What he described was Eike’s system, meritocracy gone amok, on a much grander scale. I wondered how much of Esteves’s criticism was just arrogance.

The Innovation Illusion: How So Little Is Created by So Many Working So Hard
by Fredrik Erixon and Bjorn Weigel
Published 3 Oct 2016

Providers of private retirement savings, especially with defined benefits, do not have the same luxury. They cannot always cut pensions or invent their own financial rules. Private providers can change their products away from defined benefits, but generally not retroactively. Naturally, private pension providers will push the risk–return profile when they invest, but when the regulatory environment is pulling in the opposite direction, investment gets ever more complex. And this is where gray capitalism gets grayer, or changes color. Gray capital has in fact another option to manage the quest for cash. Given their ownership role in the economy, investment institutions representing retirement savers can turn to their cash-strong investees and demand that they return more capital to shareholders.

A Random Walk Down Wall Street: The Time-Tested Strategy for Successful Investing (Eleventh Edition)
by Burton G. Malkiel
Published 5 Jan 2015

Neither fundamental analysis of a stock’s firm foundation of value nor technical analysis of the market’s propensity for building castles in the air can produce reliably superior results. Even the pros must hide their heads in shame when they compare their results with those obtained by the dartboard method of picking stocks. Sensible investment policies for individuals must then be developed in two steps. First, it is crucially important to understand the risk-return trade-offs that are available and to tailor your choice of securities to your temperament and requirements. Part Four provided a careful guide for this part of the walk, including a number of warm-up exercises concerning everything from tax planning to the management of reserve funds and a life-cycle guide to portfolio allocations.

The Party: The Secret World of China's Communist Rulers
by Richard McGregor
Published 8 Jun 2010

In between times, he completed an MBA at City University in London, where he still sends up-and-coming finance officials from China on scholarships for an education in liberal finance and economics. When the state banks were being restructured, Liu relentlessly drilled his subordinates on the importance of global regulatory norms, like capital ratios, risk returns and non-performing loan rates. On lazy Friday afternoons at the regulator, lower-level officials joked that Liu would terrify them by landing unannounced in their departments and putting them through an impromptu grilling on ‘Basel II’, the formula named after the Swiss city which dictates the optimum level of bank reserves.

Last Man Standing: The Ascent of Jamie Dimon and JPMorgan Chase
by Duff McDonald
Published 5 Oct 2009

With a number of defections from Salomon, most prominently John Meriwether and his team at the powerful hedge fund Long-Term Capital Management, other firms were using similar if not identical strategies, with the inevitable result that the arbitrage opportunity was shrinking. This, in turn, meant that the risk-return trade-off on the unit’s big bets was heading in the wrong direction. The arbitrage group’s members had also done a surprisingly poor job of ingratiating themselves with their new bosses. In his insightful indictment of financial innovation, A Demon of Our Own Design, Richard Bookstaber recalls a series of meetings in which the heads of Salomon’s proprietary trading—Rob Stavis, Costas Kaplanis, and Sugar Myojin—were tasked with making Weill, Dimon, and Travelers’ CFO Heidi Miller comfortable with their strategies and positions.

Traders, Guns & Money: Knowns and Unknowns in the Dazzling World of Derivatives
by Satyajit Das
Published 15 Nov 2006

New fund managers sprang up everywhere. DAS_C04.QXP 8/7/06 110 8:39 PM Page 110 Tr a d e r s , G u n s & M o n e y Fund managers competed with each other on the basis of returns and new investment products. They used derivatives for higher returns, leverage, access or to provide different types of risk/return tradeoffs. Private banks and investors also discovered derivatives as returns plummeted. Dealers had worked out how to embed derivatives in a note so that investors could trade them without trading them. Now all investors did derivatives. Today 70% + of derivatives activity is with investors. It is with your money.

Inside the House of Money: Top Hedge Fund Traders on Profiting in a Global Market
by Steven Drobny
Published 31 Mar 2006

If you get stopped out, think it through, and still have very strong views, then the expected return is still pretty good but with one very important proviso:You have to add in the loss to your trade because you’ve already incurred it.Thus the risk/reward must be less the second time than it was the first. Your risk/return ratio should at least be 4 to 1 in any given trade (the great traders think in terms of 8 to1 or 10 to 1).After you’ve hit the 1 a couple of times, all of a sudden what was a 4 to 1 trade is now a 4 to 3 trade, at which point you should move on to another trade, even if you don’t want to. Do you think managers should have specific rules regarding when they can get back in a trade after a stop-loss gets hit, such as a cooling-off period or the trade has to move back your way by X percent?

The Tyranny of Experts: Economists, Dictators, and the Forgotten Rights of the Poor
by William Easterly
Published 4 Mar 2014

Condliffe faced a problem that would recur again and again throughout the history of development. The horrible political situation in China seemed itself to be a huge barrier to development. Anyone mixed up in this politics would seem to be part of the problem, not part of the solution. But if he didn’t deal with the Guomindang, Condliffe risked returning home empty-handed. In this environment, the technocratic approach, which ignored politics, came to the rescue. The technocratic mind-set would allow Chinese economists to present themselves as neutral experts, no politics implied. In particular, Chinese economists who had been educated in the United States would have expert qualifications, some apparent distance from internal Chinese politics, and the ability to communicate with their funders.

The Downfall of Money: Germany's Hyperinflation and the Destruction of the Middle Class
by Frederick Taylor
Published 16 Sep 2013

If Lloyd George was disappointed – his coalition government, already in serious difficulties, finally fell in October – the French were furious, interpreting the separate agreement between Germany and Russia both as a cause of Genoa’s failure and as a typical act of bad faith. As for Rathenau himself, he had fought against the Rapallo Treaty, believing that Germany risked returning relations with the Western powers to the dark days of 1919. Only when it became clear that the Russians might otherwise make a deal with Britain and France and the rest which would leave Germany out in the cold again, did the Foreign Minister relent. The final decision to sign the Russian treaty came during what was described as a ‘pyjama party’ in Rathenau’s hotel suite during the night of 15/16 April.

The Cleaner: The True Story of One of the World's Most Successful Money Launderers
by Bruce Aitken
Published 2 Mar 2017

The market is “black” By noon, I was out and about in Hong Kong, thinking about how I was going to double my money as soon as I got to Saigon. First stop, American Express. Next stop, the chemist. You never know about customs when you arrive in Saigon, so I cashed a check for two thousand dollars, asking for twenty crisp hundred-dollar bills. That was a hell of a lot of money in those days, and more than I wanted to risk. Returning to my hotel, I wrapped the money in plastic and stuffed it into the back of a large tube of Colgate toothpaste I had sliced open with a razor blade. The flight to Saigon the next afternoon arrived on time. After dropping my things off at the company villa, I jumped into a taxi and headed downtown to the Astor Hotel.

Money for Nothing
by Thomas Levenson
Published 18 Aug 2020

They also got a “new” South Sea share in the trading side of the Company, now severed from the purely financial operation. This maneuver eliminated the confusion that Hutcheson had tried so hard to explain in 1720. Now there was a stable, liquid financial asset that had a publicly known and low-risk return—and another business playing in the high-risk, occasionally high-reward arena of transoceanic commerce.*2 It’s one of the oddities of the Bubble year that this step actually revitalized the venturing side of the South Sea experiment. The persistent disappointments of the trading ventures of the 1710s were part of what had goaded Blunt and his comrades toward bigger and bigger financial gambles.

Principles of Corporate Finance
by Richard A. Brealey , Stewart C. Myers and Franklin Allen
Published 15 Feb 2014

John doesn’t reply. Marsha: John, what’s wrong? Have you been selling yen again? That’s been a losing trade for weeks. John: Well, yes. I shouldn’t have gone to Goldman Sachs’s foreign exchange brunch. But I’ve got to get out of the house somehow. I’m cooped up here all day calculating covariances and efficient risk-return trade-offs while you’re out trading commodity futures. You get all the glamour and excitement. Marsha: Don’t worry, dear, it will be over soon. We only recalculate our most efficient common stock portfolio once a quarter. Then you can go back to leveraged leases. John: You trade, and I do all the worrying.

…

It assumes that all investors have similar tastes: The hedging motive does not enter, and therefore they hold the same portfolio of risky assets. Merton has extended the capital asset pricing model to accommodate the hedging motive.6 If enough investors are attempting to hedge against the same thing, the model implies a more complicated risk–return relationship. However, it is not yet clear who is hedging against what, and so the model remains difficult to test. So the capital asset pricing model survives not from a lack of competition but from a surfeit. There are too many plausible alternative risk measures, and so far no consensus exists on the right course to plot if we abandon beta.

…

See Portfolio risk present value and, 22–23 project, 219–222, 226–232, 333, 883 return and, 883–884 short-termism and, 874 in term structure of interest rates, 58–59 Risk aversion, 8 Risk class, 81 Risk-free rate of interest, 520n Risk management, 659–684, 887 agency problem, 660, 661–662 derivatives in, 662, 665–677 evidence on, 662 forward contracts, 665 hedging defined, 659–660, 665 with futures contracts, 666–672, 677–679 setting up hedge, 677–681 insurance, 550, 662–664 international risks in, 693–714 options, 664 reasons for, 659–662 swaps, 673–677 Risk-neutral option valuation, 537–540 Risk premium calculating, 164 defined, 164n dividend yields and, 166–167 historic, 197 market. See Market risk premium in Sharpe ratio, 196, 196n Risk-return trade-off, financial leverage and, 428–433 Risk shifting game, in financial distress, 460–461 Ritter, J. R., 330n, 380, 380n, 382n, 383n, 389n, 392 Ritz Carlton, 807 RJR Nabisco, 462, 837–839 ROA (return on assets), 305n, 597, 727, 728, 731 Road show, 378 Robert Bosch, 867 Roberts, M. R., 467n, 624n, 627n ROC (return on capital), 305n, 726, 727–728 Roche, 706–709 Rockefeller Center, 465n Rockefeller Center Properties, 465n Rodriguez, Alex, 301 ROE (return on equity), 85–89, 727, 728, 734 Roe, M., 855n Röell, A., 878 Rogalski, R.

Handbook of Modeling High-Frequency Data in Finance
by Frederi G. Viens , Maria C. Mariani and Ionut Florescu
Published 20 Dec 2011

This model includes the subjective expectations of investors in a risk variance optimization model. An alternative line of research is to use the scores of boosting instead of the subjective expectations of the investors. Creamer (2010) has followed this approach combining the optimal predictive capability of boosting with a risk return optimization model. Finally, this research can also be extended using boosting for the design of the enterprise BSC and by including other perspectives of those reviewed in this study. References 69 Initially, the corporate governance variables did not seem to be very relevant to predicting corporate performance.

Trend Following: How Great Traders Make Millions in Up or Down Markets
by Michael W. Covel
Published 19 Mar 2007

Tiger’s spiral downward started in the fall of 1998 when a catastrophic trade on dollar-yen cost the fund billions. An ex-Tiger employee was quoted as saying: “There’s a certain amount of hubris when you take a position so big you have to be right and so big you can’t get out when you’re wrong. That was something Julian never would have done when he was younger. That isn’t good risk-return analysis.”17 The problem with Tiger was its philosophically shaky foundation. Robertson stated: “Our mandate is to find the 200 best companies in the world and invest in them, and find the 200 worst companies in the world and go short on them. If the 200 best don’t do better than the 200 worst, you probably should go into another business.”

The Zero Marginal Cost Society: The Internet of Things, the Collaborative Commons, and the Eclipse of Capitalism
by Jeremy Rifkin
Published 31 Mar 2014

The Economist, in an editorial titled “Capital Markets with a Conscience” described the evolution of social entrepreneurialism. The notion of social capital markets can seem incoherent because it brings together such a diverse group of people and institutions. Yet there is a continuum that connects purely charitable capital at one extreme and for-profit capital at the other, with various trade-offs between risk, return and social impact in between. Much of the discussion . . . is expected to focus on that continuum and to figure out, for any given social goal, which sort of social capital, or mix of different sorts of it, is most likely to succeed.33 For example, while the benefit corporation is an attempt to modify the profit-making drive of capitalist firms to edge closer to the social and environmental priorities of nonprofits in the social Commons, nonprofit organizations are making their own modifications, edging closer to the profit orientation of capitalist firms.

The Shifts and the Shocks: What We've Learned--And Have Still to Learn--From the Financial Crisis
by Martin Wolf
Published 24 Nov 2015

Finally, the central bank can sterilize reserves by changing reserve requirements, and it can decide how onerous to make such requirements by determining the rate of interest it pays on reserves. Figure 41. US ‘Money Multiplier’ Source: Federal Reserve Bank of St Louis If interest rates were to remain at zero when a normal appetite for risk returns, credit and money would start to grow too fast, the economy would overheat, and everything would end up as critics fear. But the conditions that caused interest rates to fall to zero are the very conditions that prevent such a credit explosion. When the conditions change, policies must change.

Investment: A History
by Norton Reamer and Jesse Downing
Published 19 Feb 2016

This is known as the constant beta approach and is indeed the most straightforward way to forecast beta, though there are more mathematically sophisticated alternative approaches as well. Fama-French Three-Factor Model In 1992, Eugene Fama and Kenneth French wrote a famous paper entitled “The Cross-Section of Expected Stock Returns” that appeared in The Journal of Finance, in which they said that beta alone is insufficient to capture the risk-return trade-off. They introduced two additional factors—size (as measured by the market capitalization) and value (as measured by the book-to-market equity ratio)—as explanatory variables in the performance of stocks. They found that value firms (or firms with low price-to-book value, as compared with growth firms) and small firms (low market capitalization) have higher expected returns in the aggregate but also have higher risk.

The Cryptopians: Idealism, Greed, Lies, and the Making of the First Big Cryptocurrency Craze
by Laura Shin
Published 22 Feb 2022

“I practice this myself and it requires a kind of diligence.”5 The following day, one of the most influential Bitcoin industry players, Barry Silbert, a strawberry blond, baby-faced Wall Street wunderkind who had been successful in the traditional financial markets and by now had founded Digital Currency Group (DCG), which had been investing in all kinds of Bitcoin companies, tweeted, Bought my first non-bitcoin digital currency… Ethereum Classic (ETC) At $0.50, risk/return felt right. And I’m philosophically on board6 Vitalik was stunned. He had met with Barry at the DCG offices in March, and at that time Barry had offered to help him and be his advisor. Now he was finding out that despite the friendly overture, Barry had never bought ether and now instead had bought ether classic.

The Name of the Rose
by Umberto Eco
Published 26 Sep 2006

They are more afraid of Saint Sebastian or Saint Anthony than of Christ. If you wish to keep a place clean here, to prevent anyone from pissing on it, which the Italians do as freely as dogs do, you paint on it an image of Saint Anthony with a wooden tip, and this will drive away those about to piss. So the Italians, thanks to their preachers, risk returning to the ancient superstitions; and they no longer believe in the resurrection of the flesh, but have only a great fear of bodily injuries and misfortunes, and therefore they are more afraid of Saint Anthony than of Christ.” “But Berengar isn’t Italian,” I pointed out. “It makes no difference.

…

They are more afraid of Saint Sebastian or Saint Anthony than of Christ. If you wish to keep a place clean here, to prevent anyone from pissing on it, which the Italians do as freely as dogs do, you paint on it an image of Saint Anthony with a wooden tip, and this will drive away those about to piss. So the Italians, thanks to their preachers, risk returning to the ancient superstitions; and they no longer believe in the resurrection of the flesh, but have only a great fear of bodily injuries and misfortunes, and therefore they are more afraid of Saint Anthony than of Christ.” “But Berengar isn’t Italian,” I pointed out. “It makes no difference.

All the Devils Are Here
by Bethany McLean
Published 19 Oct 2010

Plus, they’d often told investors that the funds operated like a boring, old-fashioned bank—they were supposed to earn the difference between their cost of funds (a good chunk of which were provided through the repo market) and the yield on the super-safe, mostly triple- and double-A-rated securities that they owned. Investors expected fairly steady, low-risk returns. Any losses, no matter how small, could spook them. The Bear team had made money on short positions they had placed on the ABX, but the volatility was worrisome. Because the higher-rated securities were supposed to be nearly riskless, the Bear Stearns hedge funds were highly leveraged: only about $1.6 billion of the $20 billion was equity.

Debtor Nation: The History of America in Red Ink (Politics and Society in Modern America)
by Louis Hyman
Published 3 Jan 2011

Revolvers who borrowed because they spent more than they earned— persistently—made for bad business. No model could screen for these kinds of revolvers. But computer models, in general, had begun to acquire an accuracy that was impossible only a decade earlier, and it was on the basis of these models that lenders delved further down the risk/return curve, relying on their ability to transfer that default risk to the holders of the credit card securities and, ultimately, the insurance companies that backed those tranches. The Seduction of the Risk Model Beginning in 1987, Household Finance Company, by now one of the largest credit card issuers in the United States, began to segment its existing portfolio ever finer, building on the discriminant analysis techniques of the 1970s.

New Market Wizards: Conversations With America's Top Traders
by Jack D. Schwager
Published 28 Jan 1994

BEING RIGHT IS MORE IMPORTANT THAN BEING A GENIUS I think one reason why so many people try to pick tops and bottoms is that they want to prove to the world how smart they are. Think about winning rather than being a hero. Forget trying to judge trading success by how close you can come to picking major tops and bottoms, but rather by how well you can pick individual trades with merit based on favorable risk/return situations and a good percentage of winners. Go for consistency on a trade-to-trade basis, not perfect trades. 24. DON’T WORRY ABOUT LOOKING STUPID Last week you told everyone at the office, “My analysis has just given me a great buy signal in the S&P. The market is going to a new high.” Now as you examine the market action since then, something appears to be wrong.

The Bankers' New Clothes: What's Wrong With Banking and What to Do About It
by Anat Admati and Martin Hellwig
Published 15 Feb 2013

Innovation, ‘Pure Information’ and the SEC Disclosure Paradigm.” Texas Law Review 90: 1601–1715. Huertas, Thomas F. 2010. Crisis: Cause, Containment and Cure. Houndmills, Basingstoke, Hampshire, England: Palgrave Macmillan. Hughes, Joseph P., and Loretta J. Mester. 2011. “Who Said Large Banks Don’t Experience Scale Economies? Evidence from a Risk-Return Driven Cost Function.” Financial Institutions Center, Wharton School, University of Pennsylvania, Philadelphia. Hull, John. 2007. Risk Management and Financial Institutions. Upper Saddle River, NJ: Pearson Prentice Hall. Hyman, Louis. 2012. Borrow: The American Way of Debt. New York: Vintage.

More Money Than God: Hedge Funds and the Making of a New Elite
by Sebastian Mallaby
Published 9 Jun 2010

The third uncorrelated position would add only $32 million of risk to the portfolio, even if, taken by itself, it threatened a loss of $100 million.19 The fifth uncorrelated position would add $24 million of risk; the tenth would add only $16 million; and so on. Through the magic of diversification, risk could almost disappear. Trades that seemed crazy to others on a risk/return basis could appear highly profitable to Meriwether and his partners. Ten years later, when the credit bubble imploded in 2007–2009, value-at-risk calculations fell out of favor. Warren Buffett admonished fellow financiers to “beware of geeks bearing formulas.” Nevertheless, Meriwether’s metric represented an advance on the traditional leverage ratio as a way of gauging risk.

What Makes Narcissists Tick
by Kathleen Krajco

One slick technique I have observed is what I call the Drive-By: The narcissist barges into a room loudly talking to drown out and stifle the extant conversation. Thus he butts in on it to take attention away from whoever is talking and suck it to himself. But he is only passing through, so he doesn't risk return fire. That is, he needn't be there for a reply to his announcement or remark. Nobody can get him to pause long enough to hear one short sentence. He just accelerates to exit the other end of the room faster if someone draws a breath and opens their mouth to speak to him. OperationDoubles.com © 2004 – 2007, Kathleen Krajco — all rights reserved worldwide. 

Extreme Money: Masters of the Universe and the Cult of Risk
by Satyajit Das
Published 14 Oct 2011

Philip Falcone’s Harbinger Capital, Mike Burry’s Scion Funds and Lahde Capital, a Santa-Monica-based fund set up by Andrew Lahde, all recorded substantial returns. Burry wrote to his investors: “The opportunity in 2005 and 2006 to short subprime mortgages was an historic one.” Lahde, a small fund, returned money to investors, recognizing that: “The risk/return characteristics are far less attractive than in the past.”17 The funds that profited from the collapse were generally smaller funds, outside the mainstream. Before the crisis, when asked about John Paulson, a banker at Goldman Sachs told a potential investor that he was “a third rate hedge fund guy who didn’t know what he was talking about.”18 One person noted: “In the hedge-fund industry the only bad thing you can do is lose people’s money.”19 Even that wasn’t strictly speaking true.

Hedge Fund Market Wizards
by Jack D. Schwager
Published 24 Apr 2012

Sometimes I have no directional trades on, and sometimes directional trades dominate my book. Basically, I like buying stuff cheap and selling it at fair value. How you implement a trade is critical. I develop a macro view about something, but then there are 20 different ways I can play it. The key question is: Which way gives me the best risk/return ratio? My final trade is rarely going to be a straight long or short position. How would you characterize yourself as a trader? I don’t have any tolerance for trading losses. I hate losing money more than anything. Losing money is what kills you. It is not the actual loss. It’s the fact that it messes up your psychology.

Money and Government: The Past and Future of Economics
by Robert Skidelsky
Published 13 Nov 2018

Indeed, one of the main advantages of fiscal policy is that a government can direct the flow of the new spending in the economy. When a recession hits, private investment spending falls far more than consumption spending, and this cannot be wholly explained as a rational response to a fall in the long-run risk-return profile of investment – ‘animal spirits’ must be at play. Keynes recognized this psychological aspect to investment spending. In this event, the government can use fiscal policy to maintain a ‘normal’ level of 286 t h e n e w mon e t a r i s m investment, in order to avoid the erosion of the economy’s productive capacity.

The Price of Time: The Real Story of Interest
by Edward Chancellor
Published 15 Aug 2022

In 2014, Larry Summers suggested that in the post-crisis period interest rates that were consistent with full employment were not consistent with financial stability.fn7 Seasoned market observers had no doubt that ultra-low rates were behind the frantic search for yield and that financial risks were mispriced. ‘[N]ever … have investors reached so high in price for so low a return,’ wrote PIMCO’s Bill Gross.49 ‘The Federal Reserve policy of zero per cent interest rates and monetary expansion,’ commented James Grant, ‘has, by design, forced investors further out on the risk–return spectrum than they would otherwise have been had short-term real interest rates been positive.’ Grant compared low interest rates to ‘beer goggles’ which blinded investors to financial risk.50 Christopher Cole of Artemis Capital suggested that monetary policymakers had brought investment returns from the future into the present, while pushing financial risk from the present into the future.51 To be fair, some central bankers expressed concerns about the impact of monetary policy on investors’ behaviour.

The Power Law: Venture Capital and the Making of the New Future
by Sebastian Mallaby
Published 1 Feb 2022

Rock and his partner articulated an approach to risk management that would resonate with future venture capitalists. Modern portfolio theory, the set of ideas that was coming to dominate academic finance, stressed diversification: by owning a broad mix of assets exposed to a wide variety of uncorrelated risks, investors could reduce the overall volatility of their holdings and improve their risk-return ratio. Davis and Rock ignored this teaching: they promised to make concentrated bets on a dozen or so companies. Although this would entail obvious perils, these would be tolerable for two reasons. First, by buying just under half of a firm’s equity, the Davis & Rock partnership would get a seat on the board and a say in its strategy: in the absence of diversification, a venture capitalist could manage his risk by exercising a measure of control over his assets.

Americana: A 400-Year History of American Capitalism
by Bhu Srinivasan
Published 25 Sep 2017

As an undergrad at Berkeley in the 1960s, Milken had come across a study by an economist named Walter Braddock Hickman. In a look at nearly every corporate bond that had existed between 1900 and 1945, Hickman’s research revealed that a diversified portfolio of the lowest-rated bonds, the bonds that seemed to present the most risk, returned substantially more than a portfolio of middle-grade bonds. There were, as is the case now, very few companies at the highest tier of credit known as triple-A, but this middle grade of bonds was the bulk of the corporate bond market. However, investors mistakenly assumed that the middle tier of companies was safer than it really was and that the bottom tier was riskier than it actually was.

Shake Hands With the Devil: The Failure of Humanity in Rwanda
by Romeo Dallaire and Brent Beardsley
Published 9 Aug 2004

After sending Tikoka to check out the current state of unrest north of Kadafi Crossroads, I decided the convoy would not be safe coming back that afternoon and issued an order for them not to return but to stay in Mulindi until the all-clear was given. But the Belgian escort deliberately disobeyed that order; they decided to risk returning to Kigali after dark with the whole convoy rather than spend an uncomfortable night camped out in their vehicles. They had just entered the suburb north of Kadafi Crossroads, which had been a major flashpoint that day, when a grenade was tossed at the lead vehicle, followed by machine-gun fire.

Americana
by Bhu Srinivasan

As an undergrad at Berkeley in the 1960s, Milken had come across a study by an economist named Walter Braddock Hickman. In a look at nearly every corporate bond that had existed between 1900 and 1945, Hickman’s research revealed that a diversified portfolio of the lowest-rated bonds, the bonds that seemed to present the most risk, returned substantially more than a portfolio of middle-grade bonds. There were, as is the case now, very few companies at the highest tier of credit known as triple-A, but this middle grade of bonds was the bulk of the corporate bond market. However, investors mistakenly assumed that the middle tier of companies was safer than it really was and that the bottom tier was riskier than it actually was.

The Rough Guide to Chile & Easter Island (Travel Guide with Free eBook)
by Rough Guides
Published 15 Mar 2023

You have to wait around until the bus is full, and you’ll probably get an unwanted city tour as other passengers are dropped off before you reach your own hotel. By taxi By the airport exit, there’s a desk where you can book official airport taxis, which cost at least CH$20,000 to the city centre. If you bargain with the private taxi drivers touting for business, you can usually pay less, but taking these taxis is at your own risk. Returning to the airport, the taxis charge a few thousand pesos less – it’s a good idea to book a radiotaxi ahead (see page 91). By car There are a number of car rental booths at the airport, including Avis (2 2795 3971, http://avis.com), Rosselot (http://rosselot.cl) and Dollar (http://dollar.com).

Security Analysis
by Benjamin Graham and David Dodd
Published 1 Jan 1962

While traders today typically price put and call options via the Black-Scholes model, one can instead use value-investing precepts—upside potential, downside risk, and the likelihood that each of various possible scenarios will occur—to analyze these instruments. An inexpensive option may, in effect, have the favorable risk-return characteristics of a value investment—regardless of what the Black-Scholes model dictates. Institutional Investing Perhaps the most important change in the investment landscape over the past 75 years is the ascendancy of institutional investing. In the 1930s, individual investors dominated the stock market.

The Rough Guide to Portugal (Travel Guide eBook)
by Rough Guides
Published 1 Mar 2023

At Castro de Vale de Águia (2.5km) are the first amazing views over a double bend in the river; at the rustic-in-the-extreme hamlet of Vale de Águia (4.5km) follow the “Aldeia Nova” sign along a tarmac road to Aldeia Nova (6.5km), where there’s a bar (probably closed) and a sign for “São João das Arribas” and “Castro”. Down this track, at the small chapel of São João das Arribas (8km), are simply extraordinary views of the Douro gorge, plus remains of the Iron Age, later Roman, castro. It’s a great place for a picnic. The no-risk return is to go back the way you came, though the actual waymarked route runs west through Pena Branca (12km) and then south to the Fresno River where you cross the low bridge (16km) and then head up past farms until you crest a hill and see Miranda (20km) ahead. Arrival and departure miranda do douro By bus Buses stop by the roundabout, opposite the fire station.

Hawaii
by Jeff Campbell
Published 4 Nov 2009

In certain areas, it’s an accepted way to get around easily (sometimes as noted in the text). However, hitchhiking anywhere is not without risks, and Lonely Planet does not recommend it. Get local advice, never hitchhike alone and size up each situation carefully before getting in a car. Travelers should understand that, by hitchhiking, they are always taking a small but serious risk. Return to beginning of chapter MOPED & MOTORCYCLE Motorcycle hire is not common in Hawaii, but mopeds are a transportation option in some resort areas. You can legally drive either vehicle in Hawaii as long as you have a valid driver’s license issued by your home country. The minimum age for renting a moped is 16; for a motorcycle it’s 21.

Valuation: Measuring and Managing the Value of Companies
by Tim Koller , McKinsey , Company Inc. , Marc Goedhart , David Wessels , Barbara Schwimmer and Franziska Manoury
Published 16 Aug 2015

However, such benefits need to outweigh any potential unintended consequences that inevitably arise with the complexity of financial engineering. This section considers three of the more common tools of financial engineering: derivative instruments that transfer company risks to third parties, off-balance-sheet financing that detaches funding from the company’s credit risk, and hybrid financing that offers new risk/return financing combinations. Derivative Instruments With derivative instruments, such as forwards, swaps, and options, a company can transfer particular risks to third parties that can carry these risks at a lower cost. For example, some airlines hedge their fuel costs with derivatives to be less exposed to sudden changes in oil prices.

Stigum's Money Market, 4E
by Marcia Stigum and Anthony Crescenzi
Published 9 Feb 2007

If we were to fear that a company might be dramatically downgraded or in the worst case go bankrupt, we would take that company out of the market well before that time. That is the theory of the liquidity backup lines that go with commercial paper issuance.” Dealers steer clear of issuing unrated commercial paper. Most dealers will not touch the stuff; said one, “Even if you charge 25 bp to sell shaky paper, the risk-return just is not there. You have to invest more in credit monitoring, which carries costs; and if one of your shaky issuers goes under, you have to have sold a lot of paper for 25 or 50 bp to recoup the costs and the anguish of resolving that.” Years ago, Drexel was the primary issuer of unrated paper, at one point doing business with 50 to 60 issuers.

Ireland (Lonely Planet, 9th Edition)
by Fionn Davenport
Published 15 Jan 2010

Be prepared too for signs hidden behind vegetation, signs pointing the wrong way, signs with misleading mileage or no signs at all. Many minor roads are single-vehicle width: stay alert for oncoming vehicles around blind corners. Most of all, prepare yourself for reckless young drivers who put the lives of their fellow motorists at risk. Return to beginning of chapter DONEGAL TOWN pop 2339 Pretty Donegal town occupies a strategic spot at the mouth of Donegal Bay, on the River Eske in the shadow of the Blue Stack Mountains. It was once a stamping ground of the O’Donnells, the great chieftains who ruled the northwest from the 15th to 17th centuries, who left behind an atmospheric old castle.