technology bubble

The Long Good Buy: Analysing Cycles in Markets
by Peter Oppenheimer
Published 3 May 2020

Equities bought at the peak of the bull market in the late 1960s, before the spike in global inflation and interest rates that was to occur over the life of the bond, also saw very negative returns. Exhibit 2.4 S&P 500 (10-year rolling annualised real returns) SOURCE: Goldman Sachs Global Investment Research. In an historical context, the period of the technology bubble and its collapse at the end of the 1990s is particularly striking. Equities bought at the top of the technology bubble in 2000 – and even through to 2003 – achieved over the subsequent decade some of the lowest real returns in US equities (along with the 1970s) in over 100 years. Equities bought during the period that followed have resulted in much stronger returns – in line with long-run averages.

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During the 1980s and 1990s, falling bond yields were associated with generally strong growth and lower risks – an environment that was conducive to value companies. Then, in the period running up to the technology bubble in the late 1990s, there was a sharp rotation in favour of growth stocks when low interest rates were seen as beneficial to growth companies that enjoyed long duration. Also, technology companies (and at the time telecom and media stocks) were seen as ‘new economy’ companies that would benefit from much higher future growth than those in traditional industries (often referred to at the time as ‘old economy’) where demand was mature. In the wake of the collapse of the technology bubble, many of these growth stocks (and technology stocks in particular) experienced the biggest falls in valuations.

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The annualised excess returns in equities compared with government bonds were very negative after the equity market bubble burst in the late 1920s, but they were extraordinarily high in the post-war years of the 1950s and 1960s (coming from low valuations post-war and supported by strong economic growth), as exhibit 2.6 illustrates. The technology bubble of the 1990s created a valuation-led collapse in stock prices, which resulted in a negative ex post (or achieved) ERP for several years. Equities bought at the height of the stock market before the financial crisis also generated very low achieved risk premia over the following decade. By contrast, the collapse in equity prices in 2008 – and the aggressive policy stimulus that followed – resulted in strong returns over the decade following the March 2009 trough.

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

The advantage that U.S. investors had gained through many years of investing abroad vanished, leaving many questioning the wisdom of international investing. The New Millennium and the Technology Bubble The last three years of the twentieth century, marked by the emergence of a huge technology bubble, saw strong gains in all of the world stock markets, with the European and American markets surging to all-time highs. But this was not to last. A few months into the new millennium, the technology bubble burst and stocks fell into a severe bear market. All of the developed countries’ markets fell by at least 50 percent: from March 2000 through October 2002, the U.S. market fell by one-half, matching its record post-Depression decline in the ferocious 1972 to 1974 bear market, while European and Japanese markets, which suffered declines of 60 and 63 percent, respectively, bottomed in March 2003—five months after the U.S. market bottomed and just prior to the U.S.

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Capital 137 Conclusion 138 CONTENTS CONTENTS ix Chapter 9 Outperforming the Market: The Importance of Size, Dividend Yields, and Price-to-Earnings Ratios 139 Stocks That Outperform the Market 139 Small- and Large-Cap Stocks 141 Trends in Small-Cap Stock Returns 142 Valuation 144 Value Stocks Offer Higher Returns Than Growth Stocks 144 Dividend Yields 145 Other Dividend Yield Strategies 147 Price-to-Earnings (P-E) Ratios 149 Price-to-Book Ratios 150 Combining Size and Valuation Criteria 152 Initial Public Offerings: The Disappointing Overall Returns on New Small-Cap Growth Companies 154 The Nature of Growth and Value Stocks 157 Explanations of Size and Valuation Effects 157 The Noisy Market Hypothesis 158 Conclusion 159 Chapter 10 Global Investing and the Rise of China, India, and the Emerging Markets 161 The World’s Population, Production, and Equity Capital 162 Cycles in Foreign Markets 164 The Japanese Market Bubble 165 The Emerging Market Bubble 166 The New Millennium and the Technology Bubble 167 Diversification in World Markets 168 Principles of Diversification 168 “Efficient” Portfolios: Formal Analysis 168 Should You Hedge Foreign Exchange Risk? 173 Sector Diversification 173 Private and Public Capital 177 x The World in 2050 178 Conclusion 182 Appendix: The Largest Non-U.S.

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262 Index Options 264 Buying Index Options 266 Selling Index Options 267 The Importance of Indexed Products 267 Chapter 16 Market Volatility 269 The Stock Market Crash of October 1987 271 The Causes of the October 1987 Crash 273 Exchange-Rate Policies 274 The Futures Market 275 Circuit Breakers 276 The Nature of Market Volatility 277 Historical Trends of Stock Volatility 278 The Volatility Index (VIX) 281 Recent Low Volatility 283 The Distribution of Large Daily Changes 283 The Economics of Market Volatility 285 The Significance of Market Volatility 286 Chapter 17 Technical Analysis and Investing with the Trend 289 The Nature of Technical Analysis 289 Charles Dow, Technical Analyst 290 The Randomness of Stock Prices 291 Simulations of Random Stock Prices 292 Trending Markets and Price Reversals 294 Moving Averages 295 Testing the Dow Jones Moving-Average Strategy 296 Back-Testing the 200-Day Moving Average 297 The Nasdaq Moving-Average Strategy 300 CONTENTS CONTENTS xiii Distribution of Gains and Losses 301 Momentum Investing 302 Conclusion 303 Chapter 18 Calendar Anomalies 305 Seasonal Anomalies 306 The January Effect 306 Causes of the January Effect 309 The January Effect Weakened in Recent Years 310 Large Monthly Returns 311 The September Effect 311 Other Seasonal Returns 315 Day-of-the-Week Effects 316 What’s an Investor to Do? 318 Chapter 19 Behavioral Finance and the Psychology of Investing 319 The Technology Bubble, 1999 to 2001 320 Behavioral Finance 322 Fads, Social Dynamics, and Stock Bubbles 323 Excessive Trading, Overconfidence, and the Representative Bias 325 Prospect Theory, Loss Aversion, and Holding On to Losing Trades 328 Rules for Avoiding Behavioral Traps 331 Myopic Loss Aversion, Portfolio Monitoring, and the Equity Risk Premium 332 Contrarian Investing and Investor Sentiment: Strategies to Enhance Portfolio Returns 333 Out-of-Favor Stocks and the Dow 10 Strategy 335 PART 5 BUILDING WEALTH THROUGH STOCKS Chapter 20 Fund Performance, Indexing, and Beating the Market 341 The Performance of Equity Mutual Funds 342 Finding Skilled Money Managers 346 xiv Persistence of Superior Returns 348 Reasons for Underperformance of Managed Money 348 A Little Learning Is a Dangerous Thing 349 Profiting from Informed Trading 349 How Costs Affect Returns 350 The Increased Popularity of Passive Investing 351 The Pitfalls of Capitalization-Weighted Indexing 351 Fundamentally Weighted versus Capitalization-Weighted Indexation 353 The History of Fundamentally Weighted Indexation 356 Conclusion 357 Chapter 21 Structuring a Portfolio for Long-Term Growth 359 Practical Aspects of Investing 360 Guides to Successful Investing 360 Implementing the Plan and the Role of an Investment Advisor 363 Concluding Comment 364 Index 367 CONTENTS F O R E W O R D Some people find the process of assembling data to be a deadly bore.

Boom and Bust: A Global History of Financial Bubbles
by William Quinn and John D. Turner
Published 5 Aug 2020

Second, how might a government prevent itself from, or be prevented from, creating a socially destructive bubble? During a technology bubble, the government can attack any area of the bubble triangle, but it is easiest for them to tighten monetary policy or macroprudential standards to reduce the money and credit which are fuelling the bubble. However, such policies are not without their dangers.10 It is difficult to identify with confidence whether or not there is a technology bubble or, if there is one, when it will burst.11 Ben Bernanke, former Chair of the Federal Reserve, has suggested that central banks should intervene only in the very unlikely circumstance that they have greater foresight than other market participants.12 Bernanke also suggests that too aggressive an approach to dealing with bubbles can actually do more harm than good.

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Whereas some of the highly innovative companies that formed during the bubbles of the 1920s eventually went on to be successful, companies that listed during the Japanese Bubble performed poorly in the long run.70 Of the 52 Japanese companies listed in the 2017 Fortune 500, none were originally incorporated during the 1980–92 period – a remarkable failure considering the number of companies that went public during the bubble.71 The lack of any silver lining underlines a key difference between technological and political bubbles. Technology bubbles often involve large sums of money flowing into extremely innovative sectors of the economy, which might 150 JAPAN IN THE 1980S otherwise have trouble attracting enough capital to get off the ground. As a result, they can be beneficial for society.72 During a political bubble these benefits are absent, as money typically flows into sectors of the economy with much fewer positive externalities.

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Steam technology was thus developed by small partnerships and private entrepreneurs. Unlike steam, the new fourth industrial revolution technologies – biotech, nanotechnology and artificial intelligence – have been developed by companies, not individual entrepreneurs. However, unlike during the dot-com and other technology bubbles, the funding for these companies comes from venture capitalists (VCs) and institutional investors rather than stock markets. Notably, press commentators have referred to the ‘tech unicorn bubble’, a unicorn being a VC-backed company with a valuation greater than $1 billion. One study found that the average unicorn was overvalued by about 50 per cent above its fair value, and some were overvalued by more than 100 per cent.7 Although private investors may have substantially overpaid for the unicorns, by our definition – an upward movement of prices that then collapses – this would not be described as a bubble.

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

The lesson behind financial innovation is clear: there are many benefits of socializing risk, but if we are not exceedingly careful to understand the potential nature and magnitude of that risk, we may impair an array of institutions at once. And so, we live in the age of a highly financialized economy. Now why, then, did the technology bubble not produce severe economic ramifications? After all, the disaster in the stock market surely should have caused the real economy to seize. Not necessarily. There were likely two related reasons why the technology bubble did not cause severe problems for the real economy. First, even though the risk of owning the technology enterprises was socialized through the stock market, the holders of the equity in these technology companies viewed it as being high-risk capital anyway.

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His poor health seemed to inspire some leniency and lighten the sentence of up to twenty-four years and five months the prosecutors pursued in the case.140 Rajaratnam spent the beginning of his career studying technology stocks, and he quickly ascended the corporate ladder at the investment bank Needham & Co., landing positions as the head of research in 1987, COO in 1989, and president by 1991. He eventually broke away from the firm, and he started Galleon Group in 1997 with several coworkers from Needham. Galleon was extremely successful despite the bursting of the technology bubble. In fact, the firm was up over 40 percent from 2000 to 2002 when the Standard & Poor’s 500 (S&P 500) was down 37.6 percent.141 And here is where Rajaratnam’s story becomes so similar to many of those of others convicted of insider trading. The striking feature of almost all inside traders is that they were either already successful or seemed poised for success.

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This was quite different than the highly rated tranches of mortgage debt (often having AA and AAA ratings), where agents believed in the soundness of the asset and often constructed their liabilities to depend fundamentally on their valuation not declining substantially. Agents thought, in short, that these mortgage assets involved their low-risk capital and as such could build more liabilities against them, and when that turned out not to be true, disaster struck. Furthermore, the technology bubble did not trigger a major credit event. Surely, tech companies themselves had a very difficult time accessing any form of capital in the wake of the bubble, but beyond this sector of the economy, there was not a wide seizure of credit. Potential lenders were not wary of all potential borrowers because generally there was not a massive shock to assets consumed by ostensibly low-risk capital.

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

Index Options Buying Index Options Selling Index Options The Importance of Indexed Products Chapter 19 Market Volatility The Stock Market Crash of October 1987 The Causes of the October 1987 Crash Exchange Rate Policies The Futures Market Circuit Breakers Flash Crash—May 6, 2010 The Nature of Market Volatility Historical Trends of Stock Volatility The Volatility Index The Distribution of Large Daily Changes The Economics of Market Volatility The Significance of Market Volatility Chapter 20 Technical Analysis and Investing with the Trend The Nature of Technical Analysis Charles Dow, Technical Analyst The Randomness of Stock Prices Simulations of Random Stock Prices Trending Markets and Price Reversals Moving Averages Testing the Dow Jones Moving-Average Strategy Back-Testing the 200-Day Moving Average Avoiding Major Bear Markets Distribution of Gains and Losses Momentum Investing Conclusion Chapter 21 Calendar Anomalies Seasonal Anomalies The January Effect Causes of the January Effect The January Effect Weakened in Recent Years Large Stock Monthly Returns The September Effect Other Seasonal Returns Day-of-the-Week Effects What’s an Investor to Do? Chapter 22 Behavioral Finance and the Psychology of Investing The Technology Bubble, 1999 to 2001 Behavioral Finance Fads, Social Dynamics, and Stock Bubbles Excessive Trading, Overconfidence, and the Representative Bias Prospect Theory, Loss Aversion, and the Decision to Hold on to Losing Trades Rules for Avoiding Behavioral Traps Myopic Loss Aversion, Portfolio Monitoring, and the Equity Risk Premium Contrarian Investing and Investor Sentiment: Strategies to Enhance Portfolio Returns Out-of-Favor Stocks and the Dow 10 Strategy PART V BUILDING WEALTH THROUGH STOCKS Chapter 23 Fund Performance, Indexing, and Beating the Market The Performance of Equity Mutual Funds Finding Skilled Money Managers Persistence of Superior Returns Reasons for Underperformance of Managed Money A Little Learning Is a Dangerous Thing Profiting from Informed Trading How Costs Affect Returns The Increased Popularity of Passive Investing The Pitfalls of Capitalization-Weighted Indexing Fundamentally Weighted Versus Capitalization-Weighted Indexation The History of Fundamentally Weighted Indexation Conclusion Chapter 24 Structuring a Portfolio for Long-Term Growth Practical Aspects of Investing Guides to Successful Investing Implementing the Plan and the Role of an Investment Advisor Concluding Comment Notes Index FOREWORD In July 1997 I called Peter Bernstein and said I was going to be in New York and would love to lunch with him.

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When economic growth increases, Treasury bondholders will receive the double blow of rising interest rates and loss of safe-haven status. One of the prime lessons learned from long-term analysis is that no asset class can stay permanently detached from fundamentals. Stocks had their comeuppance when the technology bubble burst and the financial system crashed. It is quite likely that bondholders will suffer a similar fate as the liquidity created by the world’s central banks turns into stronger economic growth and higher inflation. Legislative Fallout from the Financial Crisis Just as the Great Depression generated a host of legislation such as the Securities and Exchange Act, which created the SEC, the Glass-Steagall Act, which separated commercial and investment banks, and establishment of the Federal Deposit Insurance Corporation, the financial crisis of 2008 spurred legislators to design laws to prevent a repeat of the financial collapse.

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At the market peak in March 2000, the total market value of firms traded on the Nasdaq reached nearly $6 trillion, more than one-half that of the NYSE and more than any other stock exchange in the world. At the beginning of the millennium, Nasdaq’s Microsoft and Cisco had the two largest market values in the world, and Nasdaq-listed Intel and Oracle were also among the top 10. When the technology bubble burst, trading and prices on the Nasdaq sank rapidly. The Nasdaq Index declined from over 5,000 in March 2000 to 1,150 in October 2002 before rebounding to 3,000 at the end of 2012. Trading also fell off from an average of over 2.5 billion shares when prices peaked to approximately 2 billion shares in 2007.

Unconventional Success: A Fundamental Approach to Personal Investment
by David F. Swensen
Published 8 Aug 2005

The highest-quality, top-tier venture firms generally refuse to accept new investors and ration capacity even among existing providers of funds. Venture firms willing and able to accept money from new sources may represent relatively unattractive, second-tier investment opportunities. Prior to the technology bubble of the late 1990s, investors in venture partnerships received returns inadequate to compensate for the risks incurred. For a few glorious years, the Internet mania allowed venture investors to share in a staggering flood of riches. Yet, the bubble-induced enthusiasm for private technology investing produced an unanticipated problem for venture investors.

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Trailing ten-year numbers for the Venture Economics sample clock in at 29.4 percent per annum, compared to 23.0 percent per annum for the common stock equivalent. Perhaps the 6.4 percentage points of incremental returns provide adequate recompense for the extraordinary risk of investing in start-up enterprises. Even so, the incremental return exists solely because of the technology bubble. Examine the trailing ten-year results for a period ending in the pre-bubble year of 1996. The Venture Economics sample of nearly six hundred funds produced a trailing ten-year return of 15.2 percent per annum, relative to a public market equivalent of 14.9 percent per annum. The decade ending December 31, 1996, represents a much more reasonable assessment of venture capital’s relative return-generating power than does the decade ending December 31, 2000.

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Unfortunately, in the broader venture world, significant general partner co-investment represents the exception, not the rule. Interestingly, however, a fair number of the venture capital elite invest substantial amounts of personal funds side by side with their limited partners. Investment success allows fund sponsors to move the terms of trade in the general partners’ favor. The technology bubble of the late 1990s provides a case in point. Inspired by enormous investor demand, venture firms raised bubble-era funds in the neighborhood of ten times the size of funds raised only a decade earlier, moving from a typical 1990-vintage fund size of $100 million to $150 million to a 2000-vintage fund size of $1 billion to $1.5 billion.

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

In fact, the $500 billion loss from subprime-mortgage-related securities is dwarfed by the more than $5 trillion of losses in the value of shares on U.S. stock markets in the early 2000s, when the so-called technology bubble of the late 1990s burst.3 How could this loss in the value of mortgage-related securities have such a large effect on the global financial system and on the broader economy? Why was the subprime crisis so much more damaging than the bursting of the technology bubble a few years earlier? And why has this crisis been so much more damaging to the world economy than the many banking crises of the early 1990s, including the Japanese crisis, which also involved very large losses in real estate lending?

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Their attempts to deal with the situation further depressed financial markets, which then affected other financial institutions.5 When dominos are standing near one another, one piece falling can make all the others fall, too. Similarly, the initial losses on subprime-mortgage-related securities triggered a chain reaction that eventually threatened to bring down the entire financial system. This is why the final damage was much greater than the initial loss might have led one to expect. By contrast, when the technology bubble burst and stock markets declined in the early 2000s, the losses were mainly borne by final investors.6 Because of those losses, many people will end up with substantially smaller pensions, but at the time there were few defaults and bankruptcies that dragged down other institutions, and there were no furious asset sales that further stressed the system.

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., 326n60, 331n25 Stiglitz, Joseph E., 324n46 stock(s): average return on, 107, 277n15; bank versus nonbank, 8, 182; in compensation, 123; market value of, 86–87, 112–14; required return on, 107, 277n14. See also equity stock exchanges, corporate debt and, 234n26 stock market, U.S.: crash of 1987 in, 262n51; technology bubble of 1990s in, 60, 61, 255n3 stock options, 214 Stout, Lynn, 285n32 strategic theory of international trade, 320n23 stress tests, 186–87; limitations of, 170, 186–87, 315n76; risk assessment with, 73, 186–87, 315n76 structured investment vehicles (SIVs): breakdown in funding for, 299n45; definition of, 159; regulation of, 161–62; risks of, 162 subprime mortgage(s): claimed to be short-term loans, 298n44; in financial crisis of 2007-2009, 60–61; interest rates on, 276n12 subprime mortgage crisis, U.S.: careless lending in, 56; contagion in, 60–61; dividends paid during, 174–75; flawed regulation as factor in, 323n38; versus technology bubble of 1990s, 60, 61 subprime-mortgage-related securities: reasons for impact of losses from, 60–61; value of losses from, 60, 255n2 subsidiaries, in resolution of failed institutions, 76–77, 262n62 subsidies, 129–47; for bank borrowing, 9, 129–30, 137–38, 139–40, 235n30; for corporate borrowing, 130, 139–40; costs of, to society, 145–47; explicit (See explicit guarantees); externalities and, 197–99; guarantees as type of (See guarantees); implicit (See implicit guarantees); and international competition, 197–99; perverse, 13, 81, 130, 139, 188, 198, 226; and size of banks, 89, 130, 270n31; tax, 139–40, 188 Sumitomo Corporation, 260n39 Summers, Lawrence, 230n7, 298n39, 331n19 Sundaresan, Suresh, 316n81 supervisors: assessment of insolvency by, 176; concern for international competitiveness, 319n8; in regulatory capture, 204–5; response to violations of capital requirements, 188–90; role in financial crisis of 2007-2009, 204, 212, 226, 336n56 Sutton, Willie, 200, 321n29 swaps: in bankruptcy, exceptions for, 236n35; use of term, 259n34.

Heads I Win, Tails I Win
by Spencer Jakab
Published 21 Jun 2016

Stocks would rise by almost 370 percent in the Roaring Twenties rally that followed, and the measure hit a then all-time high of 32.6 in September 1929. That was followed by the Great Crash and Depression, and in less than three years the CAPE had plunged to a very low 5.6. The highest reading of all time came shortly before the technology bubble burst when the CAPE hit 44 times. It dropped to a little over 13 times at the March 2009 bear market low. Stocks fell by 41 percent over that nearly nine-and-a-quarter-year span. You won’t be surprised to hear, then, that the CAPE can be a remarkably good predictor of what sort of short- and medium-run returns to expect from the stock market.

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A 1999 research paper by Roni Michaely and Kent Womack calculated that the twelve-month excess return of stocks recommended by an analyst working for the underwriter of a stock offering was negative 7.5 percent, whereas it was positive 7.4 percent for similar recommendations by analysts not working for an underwriter.7 Another conclusion one might reach from that data, but probably an incorrect one, is that independent analysts really do have skill, because their picks generated “excess return.” But understand that this was for initial public offerings during the technology bubble—a time when almost every issue was technology-related and when that sector did far better than the broad market. In a more sedate period, as I’m about to show, buy recommendations aren’t worth much. If memory serves me right, my personal ratio of buys to sells was more balanced. That, though, was probably because I worked in emerging markets where the bulk of my compensation came from client commissions rather than investment banking fees.

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By my calculation, an “x” appears in company names seventeen times more frequently than in actual English words. Please don’t take the “x” warnings too literally, though. Lynch wrote this in an earlier era, having retired from his phenomenal run atop the Fidelity Magellan Fund before the technology bubble had even begun to inflate. A decade later, “.com” would have served the same role of attracting investors like moths to a flame. A quarter century earlier, in the Swinging Sixties, it was anything with the suffix “tronic” or the word “scientific.” Hot companies included Vulcatron, Circuitronics, Astron, and the gratuitously snazzy-sounding “Powerton Ultrasonics.”

Why I Left Goldman Sachs: A Wall Street Story
by Greg Smith
Published 21 Oct 2012

In those days, Goldman had fresh fruit, big plates of it, everywhere on the trading floor. There was so much of it that it couldn’t possibly all be eaten—I remember seeing piles of rotting fruit with clouds of tiny flies swarming around them. It was said that Goldman was spending tens of thousands of dollars a month just on fruit. When the technology bubble burst, the fruit was the first thing to go. ——— But in the summer of 2000, the bubble hadn’t burst yet: Tech was still booming. Dot-coms were all the rage. All a company had to do then was put that magic suffix .com after its name, or the prefix e- in front of it, and its value would instantly soar, to absurd, stratospheric levels.

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In the course of business, I’d call him almost every day: it felt quite surreal to be on the phone with a buddy I used to get hammered and go to Stanford Cardinal hoops games with, discussing hot tech stocks such as Check Point Software and Comverse Technology. Prakash was a hard sell. The technology bubble was still bubbling in Israel, but he took an extremely skeptical view of stocks for which many investors were willing to pay huge sums. It made him (and still makes him) extremely good at what he did. Eliot Spitzer wasn’t alone in his suspicion of investment banks. Prakash used to give me a hard time about the role Goldman had played in the Internet bubble, which had burst while we were seniors in college and before our respective careers in finance began in 2001.

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It was April 2006, and the deep recession that had struck the markets after September 11 had faded, as recessions inevitably do, and been replaced by a new bubble, thanks to easy mortgages and the Federal Reserve pumping cheap money into the financial system the way Vegas pumps oxygen onto unsuspecting gamblers. The only trouble with bubbles is that it is hard to tell when you’re in one until it bursts. The technology bubble by now seemed a distant, almost ancient, memory. Bankers on Wall Street were toasting one another’s wisdom, just as homeowners were smiling as they watched their houses grow more valuable every week. The rising tide was making everyone feel smart. I was allowing myself to feel a little bit smart, too.

Mastering the VC Game: A Venture Capital Insider Reveals How to Get From Start-Up to IPO on Your Terms
by Jeffrey Bussgang
Published 31 Mar 2010

Eventually, we were chased out of Michael’s house and had to find proper office space. In our first year, we raised nearly $100 million in two rounds of financing from several blue-chip venture capital firms, hired fifty more employees, and signed a flurry of business partnerships. After many twists and turns, including surviving the bursting of the technology bubble, Upromise became a very successful company. Sallie Mae acquired it in 2006, a few years after I had left, and by 2010, the firm had $21 billion of college savings under management and 12 million households using the service. AN ENTREPRENEUR’S MAKEUP Although I spent the first ten years of my professional life as an entrepreneur, I didn’t fully understand the entrepreneur’s mind-set—my own mind-set, that is—until I went to the other side and became a venture capitalist.

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And so rather than deploy $100 million to $200 million over three or four years into start-ups at a clip of $5 to $10 million at a time, they tried to invest $1 to $2 billion over the same period by forcing $25 to $50 million at a time into their companies. And we all know how that movie ended. With the burst of the technology bubble in 2000 and 2001, things obviously have changed. Or have they? After all, the more capital under management VCs have, the more money they make in fees. So, the natural incentive for many is to keep fund sizes large, and therefore fees large, even if the fundamentals do not support it. Kleiner Perkins cut their post-bubble fund, raised in 2004, to $400 million—smaller than their 2000 fund, but still nearly three times what they raised in their first few decades as a firm.

A Wealth of Common Sense: Why Simplicity Trumps Complexity in Any Investment Plan
by Ben Carlson
Published 14 May 2015

This is why investors constantly obsess over market crashes. Read enough market history and you are bound to come across the following events at some point: the 1929 to 1932 crash that saw stocks fall in excess of 80 percent; the 1987 Black Monday crash that saw stocks fall over 20 percent in a single day; the technology bubble and bust that saw the NASDAQ fall over 80 percent from the peak in 2000 and the great financial crisis of 2007 to 2009 that cut nearly every stock market in the world in half or worse. Market crashes leave lasting scars that make it difficult to move on and get over them. In 1987 the stock market had its largest one day crash ever, with the S&P 500 falling more than 20 percent.

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But also remember that there is no rainbow in the stock market without a few periods of rain mixed in. It's an unfortunate but necessary precondition. Speaking of difficult market environments. . . . Myth 8: The 2000s Were a Lost Decade for the Stock Market Bookended by the bursting of the technology bubble and the Great Recession, the 2000s were one of the worst decades ever in the U.S. stock market. Two times the S&P 500 was chopped in half in less than 10 years. The S&P 500 suffered through this horrific decade from 2000 to 2009 finishing with a total return of –9.1 percent. That means investors lost around 1.0 percent of their money every year, on average, in the 2000s. $10,000 invested on January 1, 2000 turned into $9,085 on December 31, 2009.

How Markets Fail: The Logic of Economic Calamities
by John Cassidy
Published 10 Nov 2009

(At the same time, some of the dot-coms, such as Amazon and eBay, did eventually develop into profitable companies.) Chicago School economics is premised on the idea that rationality and competition prevent bad outcomes: in this case, rationality actually aggravated the market failure. “Our findings are consistent with the view that investor sentiment driving the technology bubble was predictable to some extent, and that hedge funds were exploiting this opportunity,” Brunnermeier and Nagel wrote. “Under these conditions, riding a price bubble for a while can be the optimal strategy for rational investors.” As it happened, this result had been formally demonstrated a number of years before the Internet bubble, in a series of papers that put forward what came to be known as the “noise trader” approach to financial markets.

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In plans that offer a default asset allocation—a mixture of stocks and bonds, usually—about three quarters of all participants accept it. Similarly, if a plan’s default option involves investing in the parent company’s stock, many people accept that, too. “[T]his pattern of investment was unaffected by the prominent bankruptcies of Enron, WorldCom, Global Crossing, and many other firms in the aftermath of the collapse of the technology bubble,” Laibson notes. “Employees who lost their entire life savings in the Enron debacle were frequently discussed in the media at the time of the Enron bankruptcy, but American workers have not generalized that message.” Evidently, economic reasoning is not something that comes naturally to people.

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America’s Portfolio Managers Grow More Bullish on Stocks and Interest Rates,” Barron’s, May 3, 1999, 31–38. 181 Pension fund investment in the Internet bubble: Eli Ofek and Matthew Richardson, “DotCom Mania: The Rise and Fall of Internet Stock Prices,” Journal of Finance 57, no. 3 (June 2003): 1122. 181 “From an efficient markets perspective . . .”: Markus K. Brunnermeier and Stefan Nagel, “Hedge Funds and the Technology Bubble,” Journal of Finance 59, no. 5 (October 2004): 2013–40. 182 “follow the advice of financial . . .”: Andrei Shleifer, Inefficient Markets: An Introduction to Behavioral Finance (New York: Oxford University Press, 2000), 10. 183 “[R]ational arbitrage can . . .”: Ibid., 174. 184 “This risk comes from . . .”: Ibid., 14–15. 184 “We were too early in calling . . .”: Mitchell Pacelle, “Soros to Appoint a CEO After Firm’s Chaotic Year,” Wall Street Journal, August 10, 1999, C1. 185 Fama update on the efficient market hypothesis: Eugene G.

Losing Control: The Emerging Threats to Western Prosperity
by Stephen D. King
Published 14 Jun 2010

But emerging-market business cycles are not perfectly linked with the US. In the late 1990s, at the time of the Asian crisis, the US economy was booming. In the early years of the twenty-first century, when the US economy was struggling to cope with the consequences of the collapse in its late 1990s technology bubble, emerging markets were booming. Consider once again the linkages between US monetary policy and monetary conditions in emerging markets. If the US economy is relatively weak, the Federal Reserve will naturally have a bias towards ‘easy’ monetary policy. Indeed, in 2003, Fed funds, the key US policy rate, fell to just 1 per cent, a remarkably low number compared with earlier history.

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The stock market had risen dramatically through the 1980s and rising land prices seemed to be a one-way bet. Shortly afterwards, however, equity prices and then land prices began to fall, marking the beginning of a twenty-year period of persistent asset-price declines. Ten years later, at the height of the technology bubble in 1999, American and European boomers found themselves in a similar state of fervour. Even when stock prices slumped in 2000, house prices carried on rising, creating the false impression that people genuinely owned assets that would support them in their impending retirements. Other, more esoteric, assets became increasingly popular.

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

Easley, “Market Selection and Asset Pricing,” in Handbook of Financial Markets: Dynamics and Evolution, ed. T. Hens and K. Hoppe (Amsterdam: Elsevier, 2009); and J. De Long, A. Shleifer, L. Summers, and R. Waldman, “The Survival of Noise Traders in Financial Markets,” Journal of Business 64, no. 1 (1991): 1–19. 68 THE STOCK MARKET IS SMARTER THAN YOU THINK cases, such as the technology bubble of the 1990s, this could take a few years, but the stock market always corrects itself to align with the underlying fundamental economics. MARKETS AND FUNDAMENTALS: THE EVIDENCE Even some of the most conventional beliefs about the stock market are not supported by the facts. For example, most growth and value indexes, like those of Standard & Poor’s, categorize companies as either “value” or “growth” based on a combination of factors, including market-to-book ratios and priceto-earnings (P/E) ratios.

…

Similarly, market bubbles and crises have always captured public attention, fueling the belief that the stock market moves in chaotic ways, detached EXHIBIT 5.2 Distribution of Growth Rates for Growth and Value Stocks Growth stocks do not grow materially faster . . . . . . but do have higher ROICs Value median Growth median 8.7% 10.2% Value median Growth median 15% 35% 14 35 Growth 12 30 10 Value 8 6 % of companies % of companies Growth 25 20 15 4 10 2 5 Value 0 0 –3 1 5 9 13 17 21 3-year average sales growth, % 25 –5 5 15 25 35 45 50+ 3-year average ROIC excluding goodwill, % MARKETS AND FUNDAMENTALS: THE EVIDENCE 69 EXHIBIT 5.3 Stock Performance against Bonds in the Long Run, 1801–2013 $ 100,000,000 Stocks 10,000,000 1,000,000 Stocks (inflation-adjusted) 100,000 Bonds 10,000 Bills 1,000 100 10 CPI 1 0 1801 1816 1831 1846 1861 1876 1891 1906 1921 1936 1951 1966 1981 1996 2011 Source: Jeremy J. Siegel, Stocks for the Long Run: The Definitive Guide to Financial Market Returns and Long-Term Investment Strategies (New York: McGrawHill; 2014); Ibbotson Associates; Morningstar EnCorr SBBI Index Data. from economic fundamentals. The 2008 financial crisis, the technology bubble of the 1990s, the Black Monday crash of October 1987, the leveraged-buyout (LBO) craze of the 1980s, and, of course, the Wall Street crash of 1929 appear to confirm such ideas. But the facts tell a different story. In spite of these events, U.S. equities over the past 200 years have delivered decade after decade of consistent returns to shareholders of about 6.5 percent annually, adjusted for inflation.

…

Although the empirical results do not fit the theoretical model perfectly, they still clearly demonstrate that the market values companies based on growth and ROIC.10 Nevertheless, there have been periods when deviations from economic fundamentals were so significant and widespread that they affected the stock market as a whole. Two recent examples are the technology bubble that burst in 2000 and the credit bubble that collapsed in 2007 (see Exhibit 5.7). The technology market boom is a classic example of a valuation bubble, in which stocks are priced at earnings multiples that underlying fundamentals cannot justify. When Netscape Communications became a public company in 1995, it saw its market capitalization soar to $6 billion on an annual revenue base of just $85 million.

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

Globalization may be a cliché, but for portfolio managers it is fast becoming a reality. Access to a properly constituted and rigorously maintained international database is a sine qua non for the start of any investment process. The period since spring 2000 has come as a shock to those who had become used to the bull market conditions of previous years. The bursting of the technology bubble, the rapid decline in economic growth rates, especially in the United States, and the advent of international terrorism raised questions about what we can expect for the future. We assert in this book that the single most important variable for making investment decisions is the equity risk premium, and we argue that high long-term returns on equities, relative to bonds, are unlikely to persist.

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Many investors were ruined, especially those who had bought stocks with borrowed money. The crash lived on in the memories of investors—and indeed, those who subsequently chose to shun equities—for at least a generation. Yet in Figure 4-2, it features as little more than a short-term setback. The October 1987 crash, and the dramatic bursting of the technology bubble in 2000, hardly even register on this long-run graph. The setback in 2000, however, will look more severe when combined with the poor returns in 2001, including the sharp downturn in the wake of the tragic events of September 11. We should be cautious about generalizing from the United States which, over the twentieth century, rapidly emerged as the world’s foremost political, military, and economic power.

…

During historical periods for which there was a suitable database covering a reasonably long interval, the value premium was in general positive. Recent periods were more mixed. Over the last few years, different countries had value-growth premia that were sometimes positive and sometimes negative. Only after major turmoil commenced toward the end of the first quarter of 2000, when the technology bubble burst, was there a tendency for value stocks to perform internationally in unison, when they once again reasserted their performance edge over growth stocks. Chapter 11 Equity dividends In this chapter, we take a closer look at dividends. We saw in chapter 10 that dividends play a central role in equity investment and valuation.

Capitalism: Money, Morals and Markets
by John Plender
Published 27 Jul 2015

These fund managers, the agents, may have a very different agenda to that of savers and trustees, the principals. They also have more and better information about companies and markets. So there is, as the economists put it, both a principal–agent problem and an information asymmetry problem. These lead to conflicts of interest. The technology bubble in the second half of the 1990s provides a good example of how the conflict works. Dot.com stocks rose initially on the basis of a conviction that technology had fundamentally changed the way the economy worked, so that expectations of future profits spiralled while conventional methods of company valuation were abandoned.

…

Either way, pricking involves the central banker in substantial career risk because the logic of incurring a modest recession today to avoid a deeper one tomorrow is lost on politicians. They will simply note the current loss of output and jobs and call for the central banker’s head. That, no doubt, was why Alan Greenspan was so terrified of blowing the US economy out of the water with a pre-emptive strike against the technology bubble. The central banker’s dilemma was summed up with characteristic shrewdness by J. K. Galbraith, whose politics and economics were as far removed from Alan Greenspan’s as it was possible to be, in his book The Great Crash 1929: Action to break up a boom must always be weighed against the chance that it will cause unemployment at a politically inopportune moment.

Foolproof: Why Safety Can Be Dangerous and How Danger Makes Us Safe
by Greg Ip
Published 12 Oct 2015

Well, I remember her answering, it’s a central bank’s duty to act when the financial system is threatened. In the following decades, I saw a fiscal crisis convulse interest rates and the dollar in my native Canada, an exchange rate crisis erupt in Europe in 1992, the Asian financial crisis, the near failure of Long-Term Capital Management in 1998, and then the rise and fall of the technology bubble. By 2007, I was looking for the next crisis everywhere: in home prices, leveraged buyouts, the trade deficit. I was not, however, looking for catastrophe. I had by now developed a deep respect for the authorities’ ability to counteract mayhem; I assumed that the economy, though it might get bumped around a bit, would come out okay.

…

In effect, Amazon exploited the irrational exuberance of the dot-com bubble to stay afloat long enough to become a colossus, revolutionizing not just retailing but book publishing and cloud computing. Between 2004 and 2008, it paid back all its bondholders, some at a premium, except those who had converted their bonds to shares. Dot-com stocks were the most famous players during the technology bubble, but more money was lost in a different sector. A host of existing and start-up telecommunications companies persuaded investors there was a mint to be made laying the fiber-optic networks that would carry booming Internet traffic between cities and continents. To finance the high costs of laying miles of fiber, telecommunications companies such as Global Crossing, Williams Communications, Tycom, Flag, and 360 Networks raised billions of dollars issuing stock and bonds.

Leading From the Emerging Future: From Ego-System to Eco-System Economies
by Otto Scharmer and Katrin Kaufer
Published 14 Apr 2013

The disconnect between actual ownership and best societal benefit results in a bubble in which state and private property, despite their merits, allow the overuse and mismanagement of the ecological and social commons in epic proportion. 8. A disconnect between technology and real societal needs. This disconnect generates technology bubbles that serve the well-being of a few in already overserved markets. For example, most R&D spending by the pharmaceutical industry caters to markets at the top while largely ignoring the needs at the base of the socioeconomic pyramid. FIGURE 1. The iceberg model: a surface of symptoms and structural disconnects (bubbles) below it.

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See Egyptian Revolution of 2011 Technological Revolution. See Second Industrial Revolution Technologies, reclaiming our access to, 109–110 Technology, 75, 77, 120, 241 creativity and, 108 disconnect between real societal needs and, 7 evolution of, 103–105 as force of liberation vs. force of dependency, 106–107 origin of the term, 108 Technology bubble, 7 Technology disconnect, 46 Technology fix, 107 Technology-fix myth, debunking the, 107 Text messaging, 199–200 Theory U debates over agricultural sustainability and, 224 Francisco Varela and, 145 innovation infrastructures and, 187–188 Matrix of Social Evolution and, 146 overview and core ideas of, 18–20, 145, 146 presencing and, 19, 119 See also U process; U.school Theory U (Scharmer), 18, 247 Thinking, 1–2, 11 systems, 82, 121, 198 See also Economic thought; Mental models Thinley, Jigme Yoser, 250–251 Third Industrial Revolution, 75, 77, 104, 105, 132 leading the, 108 Tho Ha Vinh, 159–160, 162 Thompson, Phil, 41 Thomsen, Ole, 207, 209 Thought, suspension of old habits of, 146 Tiki-taka soccer, 125 Todmorden, West Yorkshire, 135 Tools, 103 Torvalds, Linus, 109, 110 Total football, 124–125 Town hall community meetings, 200 Toynbee, Arnold, 51, 73 Tragedy of the commons, 12, 47, 131 Transparency, 236 lack of, 10 Triodos Bank, 101 Tyrants, the toppling of, 27–29.

The greatest trade ever: the behind-the-scenes story of how John Paulson defied Wall Street and made financial history
by Gregory Zuckerman
Published 3 Nov 2009

The 1998 collapse of mega–-hedge fund Long-Term Capital Management, which lost 90 percent of its value over a matter of months, also put a damper on the industry, while cratering global markets. By the end of the 1990s, there were just 515 hedge funds in existence, managing less than $500 billion, a pittance of the trillions managed by traditional investment managers. It took the bursting of the high-technology bubble in late 2000, and the resulting devastation suffered by investors who stuck with a conventional mix of stocks and bonds, to raise the popularity and profile of hedge funds. The stock market plunged between March 2000 and October 2002, led by the technology and Internet stocks that investors had become enamored with, as the Standard & Poor’'s 500 fell 38 percent.

…

As the World Trade Center toppled on September 11, 2001, and Osama bin Laden’'s lieutenants boasted of crippling the U.S. economy, the real estate market and the overall economy wobbled—--especially around the key New York area. Home prices had enjoyed more than five years of gains, but the economy was already fragile in the aftermath of the bursting of the technology bubble, and most experts worried about a weakening real estate market, even before the tragic attacks. But the Federal Reserve Board, which had been lowering interest rates to aid the economy, responded to the shocking September 11 attacks by slashing interest rates much further, making it cheaper to borrow all kinds of debt.

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

This means that high Sharpe ratio (SR) assets with low returns, but even lower volatility, will remain unloved by those who require high returns and can’t borrow to invest. They would rather buy high return assets with higher risk, even if the additional risk is not fully compensated for and the SR is lower. As a result undiversified portfolios are common, with equities contributing nearly all the volatility. People prefer riskier stocks, epitomised by the technology bubble in 1999. This effect also explains why short maturity bonds have historically had higher SR than longer maturity bonds.The lucky investors who can use leverage should outperform others over the long run. But beware: in a crisis a death spiral can easily develop in portfolios built on debt. Prices fall, brokers ask for more margin or restrict borrowing entirely, investors have to sell, and prices fall further.

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Thank you for that, and for everything. 301 Index 2001: A Space Odyssey, 19f 2008 crash, 170 Active management, 3 AIG, 2 Algorithms, 175, 199 Alpha, 3, 37, 106, 136 Alternative beta, 3-4 Amateur investors, 4, 6, 16, 48, 177, 210 and lack of diversification, 20 and over-betting, 21 and leverage, 35 and minimum sizes, 102 as day traders, 188 Anchored fitting: see Back-testing, expanding out of sample Annual returns, 178-179 Annualised cash volatility target, 137, 139, 149, 151, 159, 161, 171, 230, 250 Asset allocating investors, 3, 7, 42, 69, 98, 116, 147, 188, 225-244, 259 and Sharpe ratios, 46 and modular frameworks, 96 and the ‘no-rule’ rule, 116, 167, 196, 225, 228 and forecasts, 122-123, 159 and instrument weights, 166, 175, 189, 198-199 and correlation, 170 and instrument diversification multiplier, 175 and rules of thumb, 186 and trading speeds, 190-191, 205 and diversification, 206 Asset classes, 246&f Automation, 18-19 Back-testing, 5, 13-15, 16, 18, 19&f, 28, 53, 64, 67, 87, 113, 122, 146, 170, 182f, 187, 197, 205 and overfitting, 20, 29, 53f, 54, 68, 129f, 136, 145, 187 and skew, 40 and short holding periods, 43 in sample, 54-56 out of sample, 54-56 expanding out of sample, 56-57, 66, 71f, 84, 89f, 167f, 193-194 rolling window, 57-58, 66, 129f and portfolio weights, 69-73 and handcrafting, 85 and correlations, 129, 167&f, 175 and cost of execution, 179 simple and sophisticated, 186 need for mistrust of, 259 See also: Bootstrapping Barclays Bank, 1-2, 11, 31, 114 Barings, 41 Barriers to entry, 36, 43 Behavioural finance, 12 Beta, 3 Bid-Offer spread, 179 Block value, 153-154, 161, 182-183, 214, 219 Bollinger bands, 109 303 Systematic Trading Bond ETFs, 226 Bootstrapping, 70, 75-77, 80, 85-86, 146, 167, 175, 193-194&f, 199, 230, 248, 250 and forecast weights, 127, 205 see also Appendix C BP, 12, 13 Braga, Leda, 26 Breakouts, 109 Buffett, Warren, 37, 42 Calibration, 52-53 Carry, 67, 119, 123, 126, 127-128, 132, 247 and Skew, 119 Koijen et al paper on, 119f Central banks, 36, 103 Checking account value, recommended frequency, 149 Clarke, Arthur C, 19f ‘Close to Open’, 120-121 Cognitive bias, 12, 16, 17, 19-20, 28, 64, 179 and skew, 35 Collective funds, 4, 106, 116, 225 and derivatives, 107 and costs, 181 Commitment mechanisms, 17, 18 Compounding of returns, 143&f Contango: see Carry Contracts for Difference, 106, 181 Contrarians, 45 Corn trading, 247f Correlation, 42, 59f, 63, 68, 70, 73, 104, 107, 122, 129, 131, 167-168, 171 and Sharpe ratios, 64 and trading subsystems, 170 and ETFs, 231 Cost of execution, 179-181, 183, 188, 199, 203 Cost of trading, 42, 68, 104, 107, 174, 178, 181, 230 Credit Default Swap derivatives, 105 Crowded trades, 45 Crude oil futures, 246f Curve fitting: see over-fitting Daily cash volatility target, 137, 151, 158, 159, 161, 162, 163, 172, 175, 217, 218, 233, 254, 262. 270, 271, 217 Data availability, 102, 107 Data mining, 19f, 26-28 Data sources, 43-44 Day trading, 188 Dead cat bounces, 114 Death spiral, 35 DeMiguel, Victor, 743f Derivatives, 35 versus cash assets, 106 Desired trade, 175 Diary of trading, for semi-automatic trader, 219-224 Diary of trading, for asset allocating investor, 234- 244 Diary of trading, for staunch systems trader, 255- 257 Diversification, 20, 42, 44, 73f, 104, 107, 165, 170, 206 and Sharpe ratios, 65f, 147, 165 of instruments rather than rules, 68 and forecasts, 113 Dow Jones stock index, 23 Education of a Speculator, 17 Einstein, 70 Elliot waves, 109 Emotions, 2-3 Equal portfolio weights, 72-73 Equity value strategies, 4, 29, 31 Equity volatility indices, 34, 246, 247 Eurex, 180 Euro Stoxx 50 Index Futures, 179-180, 181, 182, 187-188, 193, 198 Eurodollar, trading recommendation, 247 Exchange rate, 161, 185 Exchange traded funds (ETFs), 4, 106, 183-184, 189, 197, 200, 214, 225, 226-228 holding costs of, 230 daily regearing of, 230f correlations, 231 Exchanges, trading on, 105, 107 Exponentially Weighted Moving Average Crossover 304 Index (EWMAC), 117-123, 126, 127-128, 132, 247 see also Appendix B Human qualities of successful traders, 259-260 Hunt brothers, 17 Fannie Mae and Freddie Mac, 2 Fees, 3 Fibonacci, 37, 109 Forecasts, 110-115, 121-123, 159, 175, 196, 211 scaling of, 112-113, 115, 133 combined, 125-133, 196, 248, 251 weighted average of, 126 and risk, 137 and speed of trading, 178 and turnover, 185 not changing once bet open, 211 see also Appendix D Forecast diversification multiplier, 128-133, 193f, 196, 249, 251 see also Appendix D Foreign exchange carry trading, 36 Fortune’s Formula, 143f FTSE 100 futures, 183, 210 Futures contracts, 181 and block value, 154-155 ‘Ideas First’, 26-27, 52-54, 103, 146 Ilmanen, Antti, 30f Illiquid assets, 198 Index trackers, 106 Inflation, 67 Instrument blocks, 154-155, 175, 182-183, 185, 206 Instrument currency volatility, 182-183, 203, 214 and turnover, 185, 195, 198 Instrument diversification multiplier, 166, 169-170, 171, 173, 175, 201, 206, 215, 229, 232, 253 Instrument forecast, 161, 162 Instrument riskiness, 155, 182 Instrument subsystem position, 175, 233 Instrument weights, 166-167, 169, 173, 175, 189, 198, 201, 202, 203, 206, 215, 229, 253 and Sharpe ratios, 168 and asset allocating investors, 226 and crash of 2008, 244 Gambling, 15, 20 Gaussian normal distribution, 22, 32&f, 39, 111f, 113, 114, 139f German bond futures, 112, 155, 181, 198 Gold, 246f Google, 29 Gross Domestic Product, 1 ‘Handcrafting’, 78-85, 116, 167-168, 175, 194, 199, 230, 248, 259 and over-fitting, 84 and Sharpe ratios, 85-90 and forecast weights, 127, 205 worked example for portfolio weights, 231-232 and allocation for staunch systems traders, 253 Hedge funds, 3, 177 High frequency trading, 6, 16, 30, 36, 180 Holding costs, 181 Housekeeping, daily, 217 for staunch systems traders, 254 Japan, 36 Japanese government bonds, 102, 112, 114, 200 JP Morgan, 156f Kahn, Richard, 42 Kaufman, Perry, 117 Kelly, John, and Kelly Criterion, 143-146, 149, 151 ‘Half-Kelly’ 146-147, 148, 230, 260 Koijen, Ralph, 119 Law of active management, 41-42, 43, 44, 46, 129f and Sharpe ratios, 47 Leeson, Nick, 41 Lehman Brothers, 2, 237 Leverage, 4, 21&f, 35, 95f, 138f, 142-143 and skew, 44-45 and low-risk assets, 103 and derivatives, 106 and volatility targeting, 151 realised leverage, 229 Life expectancy of investor, and risk, 141 305 Systematic Trading Limit orders, 179 Liquidity, 35, 104-105, 107 Lo, Andrew, 60f, 63f Long Term Capital Management (LTCM), 41, 46 Sharpe ratio of, 47 Low volatility instruments, need to avoid, 143, 151, 210, 230, 260 Lowenstein, Roger, 41, 46f Luck, need for, 260 Lynch, Peter, 37 Markowitz, Harry, 70, 72 Maximum number of bets, 215 Mean reversion trading, 31, 43, 45, 52, 213f ‘Meddling’, 17, 18, 19, 21, 136, 260 and forecasts, 115 and volatility targets, 148 Merger arbitrage, 29 Mid-price, 179, 181 Minimum sizes, 102, 107 Modular frameworks, 93, 95-99 Modularity, 5 Momentum, 42, 67, 68, 117 Moving averages, 94, 195, 197 MSCI, 156f Narrative fallacy, 20, 27, 28, 64 NASDAQ futures, 188 Nervousness, need for, 260 New position opening, 218 Niederhoffer, Victor, 17 Odean, Terence, 13, 20f Odysseus, 17 Oil prices, standard deviation of, 211 O’Shea, Colm, 94f Online portfolio calculators, 129f Overbetting, 21 Over the counter (OTC) trading, 105, 106, 107, 183f Overconfidence, 6, 17, 19f, 54, 58, 136 and lack of diversification, 20 and overtrading, 179 306 Over-fitting, 19-20, 27-28, 48, 51-54, 58, 65, 68, 121f, 156, 259 and Sharpe ratios, 46f, 47, 146 avoiding fitting, 67-68 of portfolio weights, 68-69 possibility of in ‘handcrafting’, 84 Overtrading, 179 Panama method, 247&f Passive indexing, 3 Passive management, 3, 4 Paulson, John, 31, 41 Pension funds, 3 ‘Peso problem’, 30&f Position inertia, 173-174, 193f, 196, 198, 217 Position sizing, 94, 153-163, 214 Poundstone, William, 143f Price movements, reasons for, 103, 107 Portfolio instrument position, 173, 175, 218, 254, 256, 257 Portfolio optimization, 70-90, 167 Portfolio size, 44, 178 Portfolio weighted position, 97, 99, 101, 109, 125, 135, 153, 165, 167, 177, 267 and diversification, 170 Price-to-earnings (P/E) ratios 4 Prospect theory, 12-13, 37 and momentum, 117 Quant Quake, the, 46 Raspberry Pi micro computers, 4 Relative value, 30, 43, 44-46, 213f Retail stockbrokers, 4 Risk, 39, 137-148, 170 Risk targeting, 136 Natural risk and leverage, 142 Risk parity investing, 38, 116&f Risk premia, 31, 119 RiskMetrics (TM), 156&f Roll down: see Carry Rolling up profits and losses, 149 Rogue Trader, 41 Rounded target position, 173, 175, 218 Index Rules of thumb, 186, 230 see also Appendix C Rumsfeld, Donald, 39&f Safe haven assets, 34 Schwager, Jack, 94f Self-fulfilling prophecies, 37 Semi-automatic trading, 4, 7, 11f, 18, 19f, 37, 38, 98, 163, 169, 209-224, 259 and portfolio size, 44, 203 and Sharpe ratios, 47, 147-148 and modular frameworks, 95 and trading rules, 109 and forecasts, 114, 122-123, 159 and eyeballing charts, 155, 195, 197, 214 and diversification, 166, 206 and instrument weights, 166, 175, 189 and correlation, 169 and trading subsystems, 169 and instrument diversification multiplier, 171, 175 and rules of thumb, 186 and overconfidence, 188 and stop losses, 189, 192 and trading speeds, 190-192, 205 Sharpe ratios, 25, 31-32, 34, 35, 42, 43, 44, 46-48, 53, 58, 60f, 67, 72, 73, 112, 184, 189, 210, 214, 250, 259 and overconfidence, 54, 136, 151 and rule testing, 59-60, 65 and T-Test, 61-63 and skew, 62f, 66 and correlation, 64 and diversification, 65f difficulty in distinguishing, 74 and handcrafting, 85-90 and factors of pessimism, 90 and risk, 137f, 138 and volatility targets, 144-145, 151 and speed of trading, 178-179, 196, 204 need for conservative estimation of, 195 and asset allocating investors, 225 and crash of 2008, 240 Schatz futures: see German bond futures Shefrin, Hersh, 13&f Short option strategies, 41 Short selling, 30, 37 Single period optimisation, 71, 85, 89 Skew, positive and negative, 32-34, 40-41, 48, 105, 107, 136, 139-141, 247, 259 and liquidity, 36 and prospect theory, 37 and risk, 39, 138 and leverage, 44-45, 142 and Sharpe ratios, 47, 62f, 146 and trend following, 115, 117 and EWMAC, 119 and carry, 119 and V2TX, 250 ‘Social trading’, 4f Soros, George, and sterling, 36f Speed of trading, 41-43, 47, 48, 104, 122, 174f, 177-205, 248 speed limits, 187-189, 196, 198-199, 204, 213, 228, 251, 260 Spread betting, 6, 106, 181, 197, 214 and block value, 154-155 and UK tax, 183f oil example, 214 Spreadsheets, 218 Stamp duty, 181 Standardised cost estimates, 203-205, 210, 226, 230 Standard deviations, 21-22, 31-32, 38, 40, 70, 103, 107, 111f, 129 and skew, 105 and forecasts, 112, 114, 128 recent, 155-158 returns, 167 and standardised cost, 182, 188, 192 and stop losses, 211 Static and dynamic trading, 38, 43, 168, 188 Staunch systems trading, 4, 7, 51-68, 69, 98, 109, 117-123, 167, 245-257 and Sharpe ratios, 46, 146, 189 and forecasts, 110-114, 122-123, 189 and instrument forecast, 161 and instrument weights, 166, 175, 198-199 and correlation, 170 and rules of thumb, 186 and trading speeds, 191-192, 205 307 Systematic Trading and back-testing, 193 and diversification, 206 Stop losses, 94-5, 115, 121f, 137f, 189, 192, 214, 216f, 217, 218 and forecasts, 211-212 and different instruments, 213 and price volatility, 216 Survivorship bias, 29 Swiss franc, 36, 103, 105, 142-143 System parameters, 186 Systematica hedge fund, 26 Taking profits and losses, 13-15, 16-18, 58, 94-95, 149 and trend following, 37 see also Appendix B Taleb, Nassim, 39f, 41 Tax (UK), 106, 183f Technical analysis, 18, 29 Technology bubble of 1999, 35 Templeton, John, 37 The Black Swan, 39f The Greatest Trade Ever, 31f, 41 Thorpe, Ed, 146f Thriftiness, need for, 260 Timing, 2 Too much/little capital, 206, 246f Trading capital, 150-151, 158, 165, 167, 178, 192, 199-202 starting low, 148 reducing, 149 and turnover, 185 daily calculation of, 217 Trading rules, 3-4, 7, 16, 25-26, 78, 95, 97-98, 101, 109, 121, 125, 135, 159, 161, 187, 249, 259 need for small number of, 67-68, 193 Kaufman, Perry’s guide to, 117 and speed of trading, 178, 205 cost calculations for, 204 see also Appendix B Trading subsystems, 98-99, 116, 159, 162, 163, 165, 166, 167&f, 169, 171f, 172, 175-176, 185, 187, 230, 251-252, 260 and correlation, 170 308 and turnover, 196 cost calculations for, 204 Traditional portfolio allocation, 167 Trend following, 28, 30, 37, 45, 47f, 67, 117, 137f, 194f, 212f, 247 and skew, 105, 115, 117, 213 Turnover, 184-186, 195, 197, 198, 205, 228, 260 methods of calculation, 204 back-testing of, 247-248 Twitter, 29 V2TX index, 246, 247, 249 Value at risk, 137 VIX futures, 105 Volatility, 21, 103, 107, 116, 129, 150, 226, 229 and targets, 95, 98, 106, 158, 159, 185 unpredictability of, 45 price volatility, 155-158, 162-163, 189, 196, 197, 200, 205, 214, 228, Appendix D and crash of 2008, 240-244 instrument currency volatility, 158, 161 instrument value volatility, 161, 172, 250 scalars, 159-160, 162, 185, 201, 206, 215, 217, 218, 229 look-back period, 155, 195-197 and speed of trading, 178 Volatility standardisation, 40, 71, 72, 73, 167, 182, 185 and forecasts, 112, 121, 129 and block value, 155 Volatility standardized costs, 247 Volatility targeting, 135-151, 171f, 188, 192, 201f, 213-215, 230, 233, 250, 259 Walk forward fitting: see Back testing, rolling window Weekly rebalancing process, for asset allocating investors, 233 When Genius Failed, 40, 46f Women as makers of investment decisions, 17&f www.systematictrading.org, 234 Zuckerman, Gregory, 31f THANKS FOR READING!

The Art of Execution: How the World's Best Investors Get It Wrong and Still Make Millions
by Lee Freeman-Shor
Published 8 Sep 2015

A paper by professors from Harvard University and the London School of Economics examined the performance of the stocks that represented investment managers’ very best ideas (based on holding sizes).54 To ensure their findings were robust, they focused on all the US-registered domestic equity funds that filed their quarterly holdings with the Securities Exchange Commission (SEC) over a 14-year period beginning in January 1991 and ending in December 2005. This was a period that captured both the massive technology bubble of the late 1990s and the subsequent popping of that bubble and stock market crash from 2000 to 2002. Given the fact that it is a requirement for most funds to file their holdings with the SEC, their study captured the majority of funds in existence that people could invest in during that period.

How an Economy Grows and Why It Crashes
by Peter D. Schiff and Andrew J. Schiff
Published 2 May 2010

But that benefit came with a heavy long-term cost. The United States ended that recession with greater imbalances than it had before the downturn began. That’s not supposed to happen. Instead of real growth, we kicked off an even bigger asset bubble (in housing) that temporarily overcame the drag of the busted technology bubble. The rising value of housing prices created a great many ‘benefits’ that masqueraded as economic health. But as we have seen, that vigor was illusory. The real tragedy is that six years later, when the next crash came, we had failed to learn anything from these mistakes. In diagnosing the causes and prescribing the best cures for the recession of 2008, economists and politicians are getting it dangerously wrong.

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

“The yen, which was as liquid as water, suddenly dried up like the Sahara,” he pleaded to his investors, failing to add that liquidity had evaporated not least because of Tiger’s recklessness.5 Tiger had been short an astonishing $18 billion worth of the currency—a position almost twice as large as Druckenmiller’s famous bet against sterling.6 By trading currencies even more ambitiously than his rivals at Quantum, Robertson had baked his own Sahara.7 In the aftermath of this disaster, Robertson promised his investors that he would scale back his currency trading. But Tiger’s yen losses were just a foretaste of the troubles in store—troubles that came in the surprising guise of a technology bull market. THE TECHNOLOGY BUBBLE OF THE LATE 1990S SERVES AS a test for two views of hedge funds.8 On the one hand there is the optimistic view—that sophisticated traders will analyze prices and move them to their efficient level. On the other hand there is a darker view—that sophisticated traders lack the muscle to enforce price efficiency and that, knowing the limits of their power, they will prefer to ride trends rather than fight them.

…

Michael Derchin, Tiger’s airline analyst, says Robertson “saw Soros make a lot of money on the macro side, and I think he got attracted to it. And so he made some very big macro bets that blew up on him.” Michael Derchin, interview with the author, March 18, 2008. 8. For an excellent scholarly treatment of this dilemma, see Markus K. Brunnermeier and Stefan Nagel, “Hedge Funds and the Technology Bubble,” Journal of Finance 59, no. 5 (October 2004). 9. John Cassidy, Dot.con: The Greatest Story Ever Sold (New York: HarperCollins, 2002), pp. 3–8. 10. Julian H. Robertson, letter to the limited partners, August 7, 1998. 11. Tiger’s share of US Airways fluctuated around the 20 percent level. In June 1998 it was just about exactly 20 percent, judging from SEC filings.

…

An academic study of hedge funds in this period confirmed that their portfolios were heavy with tech stocks, especially in the third quarter of 1999. Technology stocks went from 16 percent of their equity portfolios to 29 percent in just three months, even though the tech sector accounted for just 17 percent of all U.S. stocks at the end of September. See Brunnermeier and Nagel, “Hedge Funds and the Technology Bubble.” 30. John Griffin, interview with the author, November 29, 2007. 31. Oppel, “A Tiger Fights.” 32. Julian H. Robertson, letter to the limited partners, December 8, 1999. 33. Julian H. Robertson, letter to the limited partners, January 7, 2000. 34. Julian H. Robertson, letter to the limited partners, March 30, 2000. 35.

State-Building: Governance and World Order in the 21st Century
by Francis Fukuyama
Published 7 Apr 2004

However, there are at least three basic reasons why there can be no optimal specification of formal institutions and thus no optimal form of organization, particularly for public sector agencies. First, the goals of many organizations are unclear. Agents can carry out the will of principals only if the principals know 3 This approach has a number of drawbacks, as evidenced by the corporate scandals of Enron, Worldcom, and other companies at the end of the technology bubble of the 1990s. Stock prices reflect too many factors, many of them not under the control of managers, to be an accurate measure of the management’s individual efforts. weak states and the black hole of public administration 51 what they want the agents to do, but this is not always the case.

The Ascent of Money: A Financial History of the World
by Niall Ferguson
Published 13 Nov 2007

Greenspan himself had felt constrained to warn about ‘irrational exuberance’ on the stock market as early as 5 December 1996, shortly after the Dow had risen above 6,000.z Yet the quarter point rate increase of March 1997 was scarcely sufficient to dispel that exuberance. Partly, Greenspan and his colleagues seem to have underestimated the momentum of the technology bubble. As early as December 1995, with the Dow just past the 5,000 mark, members of the Fed’s Open Market Committee speculated that the market might be approaching its peak.99 Partly, it was because Greenspan felt it was not for the Fed to worry about asset price inflation, only consumer price inflation; and this, he believed, was being reduced by a major improvement in productivity due precisely to the tech boom. 100 Partly, as so often happens in stock market bubbles, it was because international pressures - in this case, the crisis precipitated by the Russian debt default of August 1998 - required contrary action.101 Partly, it was because Greenspan and his colleagues no longer believed it was the role of the Fed to remove the punchbowl from the party, in the phrase of his precursor but three, William McChesney Martin, Jr.102 To give Greenspan his due, his ‘just-in-time monetary policy’ certainly averted a stock market crash.

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gold standard 58 Britain and 55-6 and crisis of 1914 300 inter-war years 161 Keynes on 58 and rentes 100 spread of 294 US abandonment of 307 and Wall Street Crash 161 Gordy, Berry 250 Gore, Al 117 An Inconvenient Truth 224 government bonds 65-72, 100 Government National Mortgage Association see Ginnie Mae government sponsored enterprises (GSEs) 251 graduates 5 grain 27 Grameen (‘Village’) Bank 279-80 Gramm, Senator Phil 170 Graunt, John 188 Gray, Edwin J. 258 Great Depression 9 and home ownership 241-6 see also unemployment Great Fire (1666) 186 Great Inflation see inflation Great Scene of Folly, The 147 Greece 296 Greenspan, Alan: and Black Monday (1987) 166 on bond market 65 and Enron 168-70 on ‘irrational exuberance’ 121 and mortgage crisis 266 successes of 168-9 and technology bubble 167-8 Greenwich, Connecticut 320 Griffin, Kenneth C. 2 Grinspun, Bernardo 111 Gross, William 68 gross domestic product (GDP): financial sectors and 5 international data 210-11 growth (economic) 31 GSEs see government sponsored enterprises Gualpa, Diego 21 Guangzhou (Canton) 289-91 Guatemala 2 Guicciardini, Francesco 46 Habsburg Empire 3 Haghani, Victor 322 ‘haircuts’ 115 Haiti 275 Halley, Edmund 188 Hamburg 186n.

Misbehaving: The Making of Behavioral Economics
by Richard H. Thaler
Published 10 May 2015

Graham noted that his strategy of buying the cheapest members of the Dow Jones Industrials would not have worked over an earlier period, 1917–33, and he cautioned that “Undervaluations caused by neglect or prejudice may persist for an inconveniently long time, and the same applies to inflated prices caused by overenthusiasm or artificial stimulants.” That advice was worth heeding during the technology bubble of the late 1990s, when value investing performed spectacularly badly, since the most expensive stocks, the Internet darlings, kept increasing in price, leaving those boring value stocks behind. Many in the investment community revered Benjamin Graham, but by the early 1980s most academic financial economists considered his work passé.

…

., 18 surge pricing, 136–38, 200n surplus value, 285–86, 285, 286, 288 Susanne (game show contestant), 299–300 Sydney, Australia, 138n Tarbox, Brian, 317–19, 321 tax cuts, 350–51 taxes, 165 compliance with, 334–36 and savings, 309–13 taxi drivers, hours worked by, 11, 199–201, 295 Taylor, Tim, 173n technology bubble, 7, 78, 220, 234, 250, 252 teenage pregnancy, 342 Teichman, Doron, 269 10% club, 277–78, 293–94 test periods, 227 texting, 190n, 342 Thaler, Alan, 14 Thaler, Jessie, 129 Thaler, Maggie, 118n theories, normative vs. descriptive, 25 theory-induced blindness, 93–94, 128 Theory of Games and Economic Behavior, The (von Neumann and Morgenstern), 29 Theory of Interest, The (Fisher), 88–89 Theory of Moral Sentiments, The (Smith), 87–88 “THERE ARE IDIOTS” paper (Summers), 240–41 Thinking, Fast and Slow (Kahneman), 38, 103n, 109, 186 Thompson, Rex, 242 Tierney, John, 327 time, value of, 21 time-inconsistency, 92–93, 99 time-shares, 71 Tirole, Jean, 307 Tobin, James, financial economics work of, 208 tokens, 149–53, 151, 263, 264–65 Tories, see Conservative Party, U.K.

My Start-Up Life: What A
by Ben Casnocha and Marc Benioff
Published 7 May 2007

ComplainandResolve.com had established relationships with several dozen local government agencies in Cali- MY DOT-COM LIFE BEGINS 11 fornia and helped more than one hundred citizens resolve their issues. By this measure I considered the effort a success, despite making no money. So that summer after seventh grade I reflected on how I had gotten engrossed in something as exciting and exhausting as my own internet company, even on a small scale. I wasn’t the only one reflecting. The 1990s technology bubble had burst and there were quite a few entrepreneurs doing some serious thinking . . . only theirs was disbelief over how they could have blown through $50M in a couple years, whereas mine was whether I wanted to really be someone different or instead spend more time with school friends talking about who were the hottest girls.

Wall Street Meat
by Andy Kessler
Published 17 Mar 2003

Now that’s the Jack that I remember. Jack paid a $15 million fine and is now barred for life from the securities business. My guess is that is a relief to him. As a boxer, he knows how to get up from a knockout punch. · · · There are plenty of smoking guns to blame for the Internet and Telecom and Technology Bubble. None are very satisfying. Fed Chairman Alan Greenspan pumped the money supply to stave off a banking crisis based on Y2K computer problems and the excess money went into the stock market. Or how about excessive stock options led greedy management to fudge earnings numbers to pump up their stock.

Crapshoot Investing: How Tech-Savvy Traders and Clueless Regulators Turned the Stock Market Into a Casino
by Jim McTague
Published 1 Mar 2011

The good-natured Gorelick described himself as a “recovering lawyer.” During the 1990s, he migrated from a big New York legal firm to an Internet start-up, Deja.com, a shopping comparison site where he served as a corporate counsel. He transitioned into a business role, and he liked it. The technology bubble burst in 2000 before Deja.com could bring an initial public offering (IPO) to market. It sold its shopping service to EBay and its newsgroup search archive to Google.1 Gorelick spent the next six months consulting and mulling over different career options. During that hiatus, he had some discussions with a former colleague—Robbie Robinette, who had a background in physics—about using sophisticated computers to trade stocks.

Street Fighters: The Last 72 Hours of Bear Stearns, the Toughest Firm on Wall Street
by Kate Kelly
Published 14 Apr 2009

When a female visitor joined him for lunch, he was heard complimenting the view from behind her. Still, Bear’s tough-nosed approach to business had given the firm long legs through some very difficult times. Founded in 1923, Bear had survived the Great Depression, the Second World War, the recession in the 1970s, the crash of 1987, and the bursting of the technology bubble. Bear’s risk-management models used computers to test the trades it made against market conditions from a number of those turbulent periods—and they always appeared to be safe, even under adverse conditions. Only a once-in-a-century meltdown could cause the system to collapse. Bear had started as a small stock-trading house with less than $1 million in capital and just seven employees.

Borrow: The American Way of Debt
by Louis Hyman
Published 24 Jan 2012

The same AAA rating given to the United States could be given, through insurance and securitization, to nearly any group of home loans. Having steadily risen since 1991, housing prices began to rise rapidly in the late 1990s. Bolstered by the low interest rates intended to stimulate the economy after the technology bubble collapse of 2000, Americans dived in headfirst. For most people, particularly of modest means, mortgages were the only kind of leverage they were able to get. Securitization provided endless capital, and investors required originators to produce more mortgages in which to invest. The traditional 20 percent down payment was no longer needed.

The Money Machine: How the City Works
by Philip Coggan
Published 1 Jul 2009

Two of those companies have been taken over; Mercury is now part of Blackrock, a big US group. Phillips & Drew lost business in the late 1990s because it was sceptical about the dotcom boom. Although it proved right in the long term, it lost clients in the short term and was taken over by UBS, the Swiss bank. In the US, by contrast, Janus was a fund management group that rode the technology bubble and then suffered heavily when the market collapsed. TRUSTS The next main set of institutional investors comprises the trusts, divided into unit and investment trusts. Both serve roughly the same function: to channel the funds of small investors into the equity markets. An investment trust is a public company like any other company except that its assets are not buildings and machinery but investments in other companies.

Investment Banking: Valuation, Leveraged Buyouts, and Mergers and Acquisitions
by Joshua Rosenbaum , Joshua Pearl and Joseph R. Perella
Published 18 May 2009

., housing, steel, and technology). These conditions directly affect availability and cost of acquisition financing and, therefore, influence the price an acquirer is willing, or able, to pay. They also affect buyer and seller confidence with respect to undertaking a transaction. For example, at the height of the technology bubble in the late 1990s and early 2000s, many technology and telecommunications companies were acquired at unprecedented multiples. Equity financing was prevalent during this period as companies used their stock, which was valued at record levels, as acquisition currency. Boardroom confidence was also high, which lent support to contemplated M&A activity.

Smarter Investing
by Tim Hale
Published 2 Sep 2014

Third, for investors who may be confused but are trying their best to be sensible, choosing a reputable firm to manage their money, which is staffed by bright people as most investment firms are, with a seemingly strong recent track record, appears like the safest thing to do and is a convenient way of passing on their investment responsibilities to someone else. Fourth, the industry has incredible firepower to influence investors. Marketing and branding strategies are backed with big bucks. In the USA, in 2000 at the high of the technology bubble, media advertising alone came to around $1 billion (Bogle, 2001). 1.4 Reducing confusion and complexity Imagine that the top edge of the triangle in Figure 1.1 represents your current interface with the market. It is crowded, noisy, confusing and all based on the premise that if you are smart, and have access to enough information, you can beat the market, or at least choose a manager who can.

DIY Investor: How to Take Control of Your Investments & Plan for a Financially Secure Future
by Andy Bell
Published 12 Sep 2013

By the late 1990s anyone with an internet connection and a computer could access real-time dealing, live valuations of shares and funds, as well as an increasing amount of market data to help them with their investment decision making. The proliferation of the internet fuelled a rapid growth in the number of online share dealing services. It was a growth that tracked the technology bubble of the late 1990s, of which it formed a part. The number of web-based brokerages is believed to have grown from around 12 in 1994 to well in excess of 100 by the turn of the century. With share prices on a seemingly one-way upwards trajectory, there was also a significant increase in the number of online investors.

Grave New World: The End of Globalization, the Return of History
by Stephen D. King
Published 22 May 2017

In The End of Alchemy, Mervyn King notes that Minsky’s periods of excess are not just in financial markets, but also in economic activity; yet, prior to the financial crisis, there was no evidence that economic growth was unusually rapid. King also notes that Minsky’s view is not helpfully predictive, relying too much on the idea that people can sometimes be irrational. Yet these arguments are not fatal to Minsky’s view: in the aftermath of the technology bubble, growth in the US only accelerated thanks to remarkably supportive monetary and fiscal policies. We now know that underlying economic performance – as measured by productivity growth – was already slowing rapidly. And an important part of Minsky’s argument is that behaviour by central bankers can encourage irrational behaviour by others.

Hatching Twitter
by Nick Bilton
Published 5 Nov 2013

Other times he hung out in the 550-foot-long park, an ovate patch of grass that looked like it belonged in front of the royal palace in London, not in San Francisco’s warehouse district. In the center of the park was a rickety old brown swing set. South Park had played a crucial role in the late nineties as home to many of the now-defunct start-ups that quickly wilted away after the technology bubble burst. Pets.com and other start-ups that had collectively squandered hundreds of millions of dollars on ridiculous parties, asinine salaries, and expensive TV ads met their timely demise overlooking South Park. It hadn’t always been the epicenter of tech. Before the start-ups had moved in, the park had been home to brothels, drug dealers, dive bars, and sordid hotels.

The Perfect Thing: How the iPod Shuffles Commerce, Culture, and Coolness
by Steven Levy
Published 23 Oct 2006

Even before personal stereos, some critics had observed the lure of isolated musical environments, which were then mostly found in the semiprivate enclosures of automobiles. In his 1974 book Television: Technology and Cultural Form, the sociologist Raymond Williams used the term "mobile privatization" to describe the phenomenon of people forming technological bubbles around themselves, isolating themselves from the scrum of human relations. "What is experienced ... in the conditioned atmosphere and internal music of this windowed shell," he wrote, is "the pursuit of self-determined private choices." Sounds good to me. But Williams was less into celebrating choice than decrying its effect.

When the Money Runs Out: The End of Western Affluence
by Stephen D. King
Published 17 Jun 2013

Many of the factors that led to such scintillating rates of economic expansion in the Western world in earlier decades are no longer working their magic: the forces of globalization are in retreat, the boomers are ageing, women are thankfully better represented in the workforce,3 wages are being squeezed as competition from the emerging superpowers hots up and, as those superpowers demand a bigger share of the world's scarce resources, Westerners are forced to pay more for food and energy. In the 1990s, it looked for a while as though new technologies might overcome these constraints. We hoped our economies would still be able to expand thanks to the impact of technology on productivity. The story didn't last. The technology bubble burst in 2000. Fearing the onset of a Japanese-style stagnation, Western policy-makers pulled out all the stops: interest rates plunged, taxes were cut and public spending was boosted. Yet, even before the onset of the subprime crisis in 2007, it looked as though these policies had led only to a serious misallocation of resources: too much money was pouring into housing and financial services (and, particularly across Europe, into public spending) and not enough into productive investment.

Concentrated Investing
by Allen C. Benello
Published 7 Dec 2016

TCA Cable was taken over by Cox three years later at four times Greenberg’s cost, as was US West Media Group by AT&T at four times Greenberg’s cost. He says that 196 Concentrated Investing Shaw Communications was at one point “a six- or eight-bagger but ended up being a four-bagger,” as well. It was helpful that cable stocks were caught up in the telecommunications, media, and technology bubble in the late 1990s. Eventually, the few remaining public cable companies, like Comcast, came crashing back down to Earth. Greenberg says it’s an amusing anecdote that demonstrates that a concentrated investor “better really know what you’re talking about.”70 You better really have studied things in depth because sometimes you’re going to hear people say, “Oh my gosh!

My Life as a Quant: Reflections on Physics and Finance
by Emanuel Derman
Published 1 Jan 2004

Each week I went to two fixed-income risk meetings, one equities risk meeting, one firmwide risk committee meeting, at least two Derivatives Analysis group meetings, and a meeting of all the managers in Firmwide Risk. Then there were three different meetings with three different controllers for equities, fixed income, and currencies and commodities respectively, as well as the periodic meeting of all the VPs in Firmwide Risk. That was when times were good. By mid-2000, after the bursting of the technology bubble and the subsequent decline in all stock markets, I had many more meetings with discouraged young quants in my group who foresaw a very limited upside. By early 2001 I was spending a large fraction of my time trying to cheer up disgruntled but talented people. There was one real perquisite to being a senior person in Firmwide Risk-you got to participate in the firm's central risk meeting once a week and watch all the biggest big shots in action as we listened to the state of our business prospects and discussed current events and strategies.

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

In the mid 1990s, the growth of new trading technologies, emerging markets and market liquidity lead to a rise of various equity and fixed income trading and arbitrage strategies. The financial crisis of 1998 exposed the risks of these strategies in terms of liquidity and transparency. Soon after however, the internet boom triggered the flood of capital into equity based strategies, including private equity. The market decline after the technology bubble in the early 2000s brought a renewed interest in risk managed products. Unfortunately, it was these very structured products that eventually failed in the 2007 and 2008 credit crisis and have focused investor and government concerns on issues related to various structured products and the use of over-the -counter derivatives in various fund products.

The Digital Divide: Arguments for and Against Facebook, Google, Texting, and the Age of Social Netwo Rking
by Mark Bauerlein
Published 7 Sep 2011

< Douglas Rushkoff > the people’s net Originally published in Yahoo Internet Life (2001). TO THOSE OF US who really love it, the Internet is looking and feeling more social, more alive, more participatory, and more, well, more Internet-y than ever before. This might sound surprising, given the headlines proclaiming the official bursting of the technology bubble. Likewise, analysts on the financial cable channels and the venture capitalists of Silicon Alley now shun any company whose name ends in .com and have moved on to more promising new buzzwords, such as wireless. But the statistics fly in the face of conventional wisdom. In terms of real hours spent online and the number of people getting new accounts every day, Internet use is up.

The Knowledge: How to Rebuild Our World From Scratch
by Lewis Dartnell
Published 15 Apr 2014

You might even briefly entertain some fantasy of moving into a plush penthouse apartment, surveying the serene, deserted city around you through its floor-to-ceiling plate-glass windows, and cultivating all you need to eat in a dense permaculture in the roof garden. A more plausible model for post-apocalyptic city dwelling would be to live immediately adjacent to a major park and plow up the turf to cultivate crops. In some cities, the environment will quickly become uninhabitable once the technological bubble bursts. Places like Los Angeles and Las Vegas have been incongruously built in very arid or even desert locales, and will rapidly wither as maintenance fails on the aqueducts supplying them with water from afar. Washington, DC, on the other hand, will face the opposite problem, as it was built on former swampland that will begin to revert to its original state with the loss of drainage.

Why Aren't They Shouting?: A Banker’s Tale of Change, Computers and Perpetual Crisis
by Kevin Rodgers
Published 13 Jul 2016

It is hoped that this will make up for the acknowledged blind spot in VaR: it doesn’t say what happens in the 1 per cent of times outside its methodology. The roll call of historic scenarios that banks are required to test positions against is like a track list from the greatest hits album of the band Banking Chaos: ‘the 1987 equity crash, ERM crises of 1992 and 1993, fall in bond markets in Q1 1994, 1998 Russian financial crisis, 2000 technology bubble burst, 2007/2008 sub-prime turbulence’.10 It almost makes me nostalgic to write them all down. Whether or not the new technique will be any more effective than the old is open to debate. As one cynical colleague of mine observed: ‘Running Stress VaR based on World War I is what the French did in the 1920s before they built the Maginot line.’

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

“Reconceptualizing ‘Market Risk’ from Scratch,” New York: Strategic Economic Decisions. Brock, H. W., 2006b. “The Logical Justif ication for ‘Active’ Investment Management” in Thoughts on the Bottom Line, Barclay Douglas, ed., New York: John Wiley & Sons. Brunnermeier, Markus, and Stefan Nagel, 2003. “Hedge Funds and the Technology Bubble,” Journal of Finance, Vol. 59, No 5 (October), pp. 2013–2040. Burton, Jonathan, 1998. “Revisiting the Capital Asset Pricing Model,” Dow Jones Asset Manager, May/June. Calio, Vince, 2005. “Operational Risk Back in Spotlight,” Pensions & Investments, October 4. Campbell, John, 2006. “Household Finance,” Journal of Finance, Vol. 61, No. 4 (August), pp. 1553–1604.

The Permanent Portfolio
by Craig Rowland and J. M. Lawson
Published 27 Aug 2012

How many investors dropped out of the market in 1987 in panic, locking in losses only to miss solid gains later? The Permanent Portfolio was up 3.5 percent in real terms that year. Table 3.7 Comparison of Annualized Real Returns by Decade for Four Portfolios. 1990s The 1990s saw another great time for stocks as the Internet technology bubble grew. As stocks soared, so did the real returns of stock-heavy allocations. By the year 2000 though, the bubble was getting ready to pop and erase a good portion of the previous stock gains. But again the Permanent Portfolio just chugged along with its steady consistent growth. When the Internet bubble was deflating the Permanent Portfolio protected its assets when the high-flyers took a big fall. 2000s When the 2000s came along, for stock investors it felt a lot like the 1970s, with very poor real returns on stocks.

Unfinished Business
by Tamim Bayoumi

The stark contrast between the robust recovery in the simulation and the slow one in reality illustrates how DSGE models helped to mislead monetary policymakers into thinking that they had more influence over the economy than they actually did. This belief in the efficacy of monetary policy was reinforced by the limited economic costs of the collapse of the technology bubble in global stock markets in 2001. The US Federal Reserve, in particular, ascribed the limited impact on the US economy to its swift monetary response. Consequently, rather than viewing the collapse in prices of overvalued equities as a warning sign of the risks from financial instability, the Fed came to believe that financial risks were limited.

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

Rather they, and corresponding changes at all the major investment banks, were driven by the unprecedented economic boom and bust that placed extraordinary pressures on the values that had once prevailed at these institutions. Much has already been written about the various economic “bubbles” of the late 1990s—the Internet bubble, the telecom bubble, the technology bubble and the stock market bubble. Much has also been written about the role of investment banks in fueling these ephemeral bubbles. Much less has been written, however, about the investment banks’ own bubble. While the investment banks in some ways made possible all the other bubbles—by, for example, legitimizing hundreds of speculative start-up companies for public market investors and opining as to the “fairness” of incredible values placed on these businesses—these institutions themselves were fundamentally transformed by the unprecedented number of deals the forces they unleashed created.

European Founders at Work
by Pedro Gairifo Santos
Published 7 Nov 2011

I also restructured the software development process, created a brand new internet-based business intelligence product and, over the next year and a half, we fixed the buggy product line which, in the end, was very attractive to customers. We started to grow again and over two years, our market cap went from $100 million to almost $5 billion. 1997 to 1999 was an amazing time for the company as we expanded into more and more countries. When the technology bubble burst, we emerged relatively unscathed because by then we were a large, stable, profitable company with thousands of customers. Our market cap dropped somewhat, but we were in good shape, and we felt that it was time to leapfrog our competition. We had been competing against Cognos for a very long time and it was head-to-head.

file:///C:/Documents%20and%...
by vpavan

By itself, debt isn't a bad thing. But if a company can't produce sufficient revenues to pay its debts, then it's asking for trouble. The reason so many telecom companies failed in recent years is that they took on huge amounts of debt in the late '90s to finance the building of fiber-optic networks. When the technology bubble burst and demand for network capacity withered, the telecoms had miles and miles of networks but too few paying customers. Their equipment suppliers also found that the inventory piling up in warehouses was worthless. Bankruptcies quickly followed, as the telecoms and equipment vendors were unable to make the interest payments on their debts.

The Blockchain Alternative: Rethinking Macroeconomic Policy and Economic Theory
by Kariappa Bheemaiah
Published 26 Feb 2017

This is a seemingly logical rationale, especially when taking into consideration the way the innovation mantra is being chanted across every sector and industry today. Indeed, this has even happened in the past. In the 1980s during the savings and loans crisis (S&L crisis), 1,043 out of the 3,234 savings and loan associations ( FDIC, 2000) failed and affected millions of everyday investors. In 2000, the bursting of the technology bubble did affect investors and technology in general. Yet none of these failures posed systemic risks and came at the cost of a financial meltdown. The plumbing of the financial system and its connection to other institutions ensure that large, complex financial organisations are systemically important financial institutions (SIFI11) that pose risks to the financial system and the economy.

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

Chinese official purchases could easily give a significant boost to the confidence of the gold market in 2012 or 2013, but the market will not know what is happening until the central bank makes an announcement. The price of gold has reached a new high in nominal terms, but it will not regain the inflation-adjusted peak it had in 1980 until the price rises to nearly $2,400 per ton. The price of gold began to rally in 2001 when the world economy was recovering from the collapse of the technology bubble. The price gains occurred against a backdrop of low US interest rates, record current account imbalances, and the emergence of China as a major economic power. The current economic environment will be conducive to further price gains. Interest rates are at record lows. Central banks will have to maintain accommodative monetary policies in order to protect their banking systems.

The Future of Technology
by Tom Standage
Published 31 Aug 2005

“If we go with the market, help our customers to realise the business value of it, then we can be a good business,” says ibm’s Mr Wladawsky-Berger. For a start, all that experi- 38 COMING OF AGE mentation during the dotcom boom actually produced some useful results. Things tried during a technological bubble tend to make a comeback. The first transatlantic cable, for example, was a disaster, but it prompted others to try again. Most business-to-business marketplaces failed dismally, because these start-ups thought technology would quickly overthrow existing power structures, explains Mr Moore.

The Investment Checklist: The Art of In-Depth Research
by Michael Shearn
Published 8 Nov 2011

Lenders and developers found themselves with many empty properties, and there were many bankruptcies during this period. This just goes to show that areas where there is an abundance of capital are usually poor hunting grounds for great investments. Investors who got caught up in the hype of the 1980s real estate boom or technology bubble of the late 1990s ultimately ended up losing most of their capital. Now that you know more about how to generally look for investment ideas, the following sections of this chapter describe a few more formalized ways to begin looking for investment ideas. Using Stock Screens A stock screen is a tool investors use to filter stocks, using pre-selected criteria.

Buy Now, Pay Later: The Extraordinary Story of Afterpay
by Jonathan Shapiro and James Eyers
Published 2 Aug 2021

‘They were balanced and reserved and never hyped it up—which is unusual for tech entrepreneurs,’ said Cyan’s Dean Fergie.2 He had tried Afterpay to buy his thirteen-year-old son a Culture Club hoodie online, and it had worked seamlessly. Afterpay had underappreciated potential, he decided, so he bid into the float. In 2016, after the experience of some technology bubbles, there was little appetite across the broader market to invest in speculative, early-stage concept companies that had yet to generate a profit. A year before, Afterpay had been little more than an idea. Now it was pitching itself as a start-up worth $100 million. Was there space in a crowded market for a new platform?

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

While trying to put his own stamp on Chase, Harrison was widely criticized for overpaying in a flurry of acquisitions at the top of the bull market of the late 1990s. His timing was lousy. He snapped up the technology investment bank Hambrecht & Quist in September 1999, just a few months before the technology bubble burst, paying an overblown $1.4 billion. He followed that with the $7.7 billion acquisition of the London-based merchant bank Robert Fleming Holdings in April 2000, and then paid $500 million in July for the mergers and acquisitions boutique Beacon Group. With the last deal, he committed one of the cardinal sins of the M&A game—buying an entire company to secure the services of a single individual.

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

Schwartz (1977), “Convertible Bonds: Valuation and Optimal Strategies for Call and Conversion,” The Journal of Finance 32, 1699–1715. Brinson, Gary P., L. Randolph Hood, and Gilbert L. Beebower (1986), “Determinants of Portfolio Performance,” Financial Analysts Journal 42(4), 39–44. Brunnermeier, Markus, and Stefan Nagel (2004), “Hedge Funds and the Technology Bubble,” Journal of Finance 59, 2013–2040. Brunnermeier, Markus, Stefan Nagel, and Lasse Heje Pedersen (2008), “Carry Trades and Currency Crashes,” NBER Macroeconomics Annual 23, 313–348. Brunnermeier, M., and L. H. Pedersen (2005), “Predatory Trading,” Journal of Finance 60, 1825–1863. Brunnermeier, M., and L.

Dancing in the Glory of Monsters: The Collapse of the Congo and the Great War of Africa
by Jason Stearns
Published 29 Mar 2011

He only wanted to allow one Rwandan trader, who was close to the Rwandan government, to have access to the mine. He said it was for security reasons, but we knew it wasn’t.”43 The initial profits, however, were nothing compared to what was to come. “Everything changed in 2000, when the coltan price soared,” Pierre Olivier remembered. It was a fluke. That year, the information technology bubble coincided with heightened demand for cell phones and the Christmas release of a Sony PlayStation console. Demand for tantalum, the processed form of coltan, had been rising steadily for years, but now the markets got caught up in a buying frenzy. Within months, the local market price of tantalum shot up from $10 to $380 per kilo, depending on the percentage of ore content, while the world price peaked at $600 per kilo of refined tantalum.44 Dozens of comptoirs—mineral trading houses—opened up in Bukavu and Goma to take advantage of the coltan rush.

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

Yet almost all the information one generates is deeply flawed, and is more likely to be flawed, the more JWPR007-Lindsey May 7, 2007 17:27 Allan Malz 303 sophisticated it is. Second, not only is it inevitable that the information is deeply flawed, but it is also not such a bad thing. I’ve been fortunate to be in at least some of the right places at the right time: at the Fed during the Golden Age of Supervision, at RiskMetrics during and after the technology bubble, and at a hedge fund during what may prove the heyday of hedge funds. Perhaps it’s the distorted perspective that comes from studying modern finance too much, but it seems to me that my career has been driven a lot more by my response to random events and larger forces than by my personal attempts to shape a path.

Makers and Takers: The Rise of Finance and the Fall of American Business
by Rana Foroohar
Published 16 May 2016

Lauren Carroll, “Hillary Clinton: Top Hedge Fund Managers Make More than All Kindergarten Teachers Combined,” PolitiFact, June 15, 2015. 54. William Lazonick, “Profits Without Prosperity,” Harvard Business Review 92, no. 2 (September 2014). 55. James K. Galbraith and Travis Hale, “Income Distribution and the Information Technology Bubble,” Working Paper No. 27, University of Texas Inequality Project, January 2004. 56. Robert Frank, The High-Beta Rich: How the Manic Wealthy Will Take Us to the Next Boom, Bubble, and Bust (New York: Crown Business, 2011), 54. 57. Richard Wilkinson and Kate Pickett, The Spirit Level: Why Equality Is Better for Everyone (London: Penguin Books, 2009). 58.

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

Losses and leverage are not good bedfellows. Sound, highly-rated companies also found reefs. Asbestos liability and the Californian electricity deregulation claimed victims. As the credit cycle turned, the arbitrage CDOs were hard hit. They had been based on US high yield (junk) bonds. The US recession and the unwinding of the technology bubble saw record numbers of default. Contagious crises in Asia, Eastern Europe and Latin America didn’t help. The credit models failed miserably. The concept of average credit losses proved average – it seemed the worst case was much worse. If the average was made of one year of very large losses and several years of no losses, then that didn’t work well either.

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

D1 D2 D3 D4 D5 D6 D7 D8 D9 D10 D1a D1b D1c D10b D10c D10c Index Bull Market Period Mar 2000 Alpha Jan 1998– TABLE 4.12 Persistence in Performance Subperiod Analysis CTA Performance, Survivorship Bias, and Dissolution Frequencies 71 analyses are less significant.9 The table also indicates that each decile is significantly exposed to the CTA Global Index. The R2 is particularly high, especially for the upper deciles, but is generally low for the subdeciles. The central part of Table 4.12 reports the decile analysis over the April 2000 to December 2002 period. This period corresponds to a bear market since the technology bubble exploded in March 2000. It indicates that all the deciles but D6 have negative alphas. The only one significantly negative is D5. This result indicates that no group of funds offers persistent returns during the bear market that began in the first half of 2000. As expected, the top-performing subdecile (D10c) yields a positive (but not significant) alpha.

Three Felonies a Day: How the Feds Target the Innocent
by Harvey Silverglate
Published 6 Jun 2011

On August 5, 1992, perhaps contrite from her involvement in perpetrating the myth that Milken was a criminal, Judge Wood reduced his sentence on the basis of his “substantial cooperation” with the government (which got no one convicted) to two years. He was released in March of the following year. 106 Following (or Harassing?) the Money The frothy boom-and-bust that characterized the ’80s and produced scapegoats like Milken was followed by the “technology bubble” of the ’90s. That decade saw its own series of questionable federal investigations and highly dubious prosecutions. As the clatter over new stock offerings by high-tech start-up companies grew to a crescendo, complaints emerged about how brokers were doling out their newly issued shares. These shares, for which demand substantially exceeded supply, were allegedly handed out in a way that took advantage of their scarcity.

The Contrarian: Peter Thiel and Silicon Valley's Pursuit of Power
by Max Chafkin
Published 14 Sep 2021

Over the previous eighteen months a media company had seemed to fold or lay off half its staff every few weeks, and I found myself dreading—or maybe fantasizing about, it was hard to tell—the day when I too would get laid off. Thiel showed up wearing a crisp blue dress shirt and joined me at a table without ordering anything or making any effort at pleasantries. Then he launched into an impromptu dissertation on the three recent economic bubbles. The first, of course, was the technology bubble; then came the bubble in subprime mortgages. Then, there was the bubble we were currently in: “Higher education,” he said. He explained his thinking, pausing on several occasions to draw on my notebook. Tuition prices had been soaring, and we’d been paying those ever-increasing premiums with federally guaranteed student loans, taking on ever-increasing debt loads—debt that, by the way, could not be discharged in bankruptcy.

On the Brink: Inside the Race to Stop the Collapse of the Global Financial System
by Henry M. Paulson
Published 15 Sep 2010

Structural differences in the economies of the world had led to what analysts call “imbalances” that created massive and destabilizing cross-border capital flows. In short, we were living beyond our means—on borrowed money and borrowed time. The dangers for the U.S. economy had been obscured by an unprecedented housing boom, fed in part by the low interest rates that helped us recover from the downturn that followed the bursting of the late-’90s technology bubble and the impact of the 9/11 attacks. The housing bubble was driven by a big increase in loans to less creditworthy, or subprime, borrowers that lifted homeownership rates to historic levels. By the time I took office in July 2006, fully 69 percent of U.S. households owned their own homes, up from 64 percent in 1994.

Good Economics for Hard Times: Better Answers to Our Biggest Problems
by Abhijit V. Banerjee and Esther Duflo
Published 12 Nov 2019

Ryan painstakingly explained to a journalist why all of these things lined up to make tax increases look good and tax decreases look bad: I wouldn’t say that correlation is causation. I would say Clinton had the tech-productivity boom, which was enormous. Trade barriers were going down in the Clinton years. He had the peace dividend he was enjoying.… The economy in the Bush years, by contrast, had to cope with the popping of the technology bubble, 9/11, a couple of wars and the financial meltdown.… Some of this is just the timing, not the person.… Just as the Keynesians say the economy would have been worse without the stimulus [that Mr. Obama signed], the flip side is true from our perspective.53 Paul Ryan is right about one thing.

How Money Became Dangerous
by Christopher Varelas
Published 15 Oct 2019

“When the harsh light of reality finally shines on this, there will be no defending the action.” The sole reason senior management allowed me to renounce the practice so blatantly and not engage in it was, frankly, because I was bringing in so much M&A business that they couldn’t risk losing me. The article appeared in late 1997, as the technology bubble built toward its peak. Over the next couple of years, I became more senior, and the pressure to spin IPOs increased. But as one of the top revenue generators in the investment bank, I had more than a little leverage to continue my resistance. Robert and I spoke later that week. The bosses had already sent a handful of envoys to reprimand him.

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

Always the choice to lend was at the same time a choice to borrow, and that choice was determined by a combination of risk and return—that is, yield on the investment. This process of investment is not unique to debt, it is the foundation of our capitalist system. The current financial crisis stems from the same source as the large capital poured into consumer credit: a frantic drive for yield. Capital sloshed about in the past few years from the technology bubble to the housing bubble, as investors sought safe (but always better than average!) returns on their money. Money poured into the riskiest tranches of mortgage-backed securities, not from malice, but for a simple increase in return over a treasury bond. As this book goes to press, the world’s great capital reserves have fled the equity markets for American federal debt.

Crash of the Titans: Greed, Hubris, the Fall of Merrill Lynch, and the Near-Collapse of Bank of America
by Greg Farrell
Published 2 Nov 2010

He said the story in the morning’s paper was “nonspecific” and “relied on unidentified sources.” He pointed to Cribiore and assured everyone that the search for a new CEO was proceeding “with speed and careful deliberation.” “This is not the first time that our firm has faced challenges,” Fleming continued. “The crash of 1987, the credit crisis of 1998, the bursting of the technology bubble in 2000, and the terror attacks of 9/11. In many ways we can better navigate this challenge because it does not call for an overhaul of our strategy or a resizing of our business. “We have accomplished a great deal in the past five years. Following the bursting of the tech bubble and 9/11, we pulled together as a firm and embarked on a new strategy to create a truly global, diversified financial services company.

The Price of Inequality: How Today's Divided Society Endangers Our Future
by Joseph E. Stiglitz
Published 10 Jun 2012

., 131, 132, 285, 317, 318, 350 Sweden, 366 economic mobility in, 18 financial crisis response in, 168, 169, 361 financial stability in, 220 GDP of, 183 inequality in, 23, 127 labor in, 230 tax system in, 22 Switzerland, 183 tariffs, 50, 61, 325 taxes: alternative minimum, 394 on capital gains, 71–72, 87, 88, 115, 211, 274, 330, 361, 378, 395 corporate, 62, 73–74, 95, 115, 142, 179, 214, 215, 221–22, 224, 225, 270, 272, 273–74, 278, 283, 296, 331 economic growth and, 22–23, 84, 86, 88 and economic stimulus, 216, 217, 218, 221 estate, 73, 76, 88, 166, 167, 274, 361, 395 on financial sector, 213–14, 215, 247, 248 globalization and, 62, 63, 142, 278 income distribution and, 30, 31, 72 loopholes in, 42–43, 72, 115, 212, 214, 215, 221, 222, 272, 273 market correction through, 34 middle-class deductions in, 222–24, 379 and national debt, 207, 376 on natural resources, 39–40, 213 on pollution, 213, 215, 224 on poor, 74, 88, 218 progressive, 5, 31, 107, 114–16, 142, 212, 218, 273–74, 379, 395 Reagan’s revision of, 5, 71, 114, 221 regressive, 38, 74, 77, 79, 157, 208, 214, 237, 251, 299 on rent seeking, 39, 115, 212–14, 215, 274, 395 Right’s view of, 216 state, 74 on wealthy, 5, 38, 42–43, 62, 71–73, 74, 76, 77, 84, 86, 87–88, 114, 115, 116, 138, 142, 159, 167, 208, 209, 211, 212, 214–15, 218, 221, 223, 224, 225, 226, 256, 274, 275, 294, 312, 335, 344, 360, 383, 394 technology: bubble in, 85, 87, 88, 89, 211, 243, 391, 396 economic impact of, 30, 79, 80 government investment in, 15, 93, 115, 155, 174, 217, 267, 281, 283 idea-shaping and, 156 labor demand and, 53, 54–56, 63, 79, 80, 277, 280, 283, 334 monopolies in, 42, 44, 45–46, 96 and stock trading, 165 telecommunications: government auction of, 50 monopolization in, 44, 97, 98 see also technology TEPCO, 189 Thaler, Richard, 161 Thatcher, Margaret, 316 Thucydides, 29 Tingbergen, 392 T-Mobile, 44, 203 tobacco industry, xviii, 151, 160, 354, 357 Tocqueville, Alexis de, 288 Townes, Charles, 41 Toxic Asset Relief Program (TARP), 362 trade: agreements on, 140, 141, 324–25, 326 austerity and, 231 globalization of, 61–64, 144, 324–25, 326 imbalances in, 279–80, 396 Treasury bills, 177, 208, 217, 396 Treasury Department, U.S., 61, 246, 253, 258, 353, 369 Tremonti, Giulio, 389 trust, 115, 120, 121–26, 134, 346 Turing, Alan, 41 Turkey, 22, 23 unemployment, xii, xv, 11–12, 13, 74, 89, 91, 179, 207, 393 extent of, 1, 10–11, 15, 75, 301, 302 macroeconomic policies affecting, 38, 61, 62, 64, 82, 85, 86, 230, 231, 236, 237, 238, 239, 240, 241, 242, 251, 259, 260, 261, 262, 263, 379 in manufacturing, 54, 56, 57, 232–33, 285, 321 political importance of, 251–52 stimulus package’s effect on, 232, 236 underreporting of, 11, 15, 291, 304–5 of youth, x, xviii–xix, 12, 265 unemployment insurance, xv, 11–12, 16, 23, 74, 210, 211, 218, 229, 242, 276, 291, 301, 355, 381, 384, 385 Unequal Democracy: The Political Economy of the New Gilded Age (Bartel), xxiv Union Carbide, 189 United Automobile Workers (UAW), 57 United Kingdom, 21, 129, 214 austerity in, 220, 231 economic mobility in, 18, 19 financial crisis response in, 171, 362–63 privatization in, 176, 316, 364 United Nations Development Program (UNDP), 22 United States: alternative futures of, 289 average tax rate in, 72–73 battle of ideas in, 154–55, 157–59, 162–86 changing social patterns in, 14–15 class distinctions in, xvi–xvii, 20, 180, 292 consumption in, 13, 54, 84–85, 86, 89, 104–6, 183, 233, 234, 235, 244, 311, 380, 385 cost of living in, 366 crime in, 15 economic history of, 4–5, 6 economic mobility in, xv, 4, 5, 18–19, 25, 94, 117, 147, 265, 267, 307 educational attainment in, 55 family stresses in, 10, 14, 26, 95, 106, 169–70 global influence of, xii, 137–38, 143–44, 145, 155, 254, 277–78 globalization’s effect in, 62, 63, 64, 184 income inequality in, 2, 3, 4, 7–8, 9, 22, 24, 25, 26, 27, 29, 30, 53, 54, 55, 56, 57, 71, 72, 77, 79–80, 81, 85, 86, 127, 153, 178, 183, 202, 233, 240, 241, 267, 294–95, 296, 297, 298, 299, 300, 311, 328, 332, 335 inequality cycle in, xi, xii, xiv, xx, xxii, 3–4, 18, 31, 76, 77, 82, 86–89, 91, 267 infant and maternal mortality in, 14, 302, 303 international comparisons to, 21–24, 25, 52, 73, 97, 98, 183, 309, 366 labor force polarization in, 8–9, 56, 79, 80, 133, 277 liberty in, 190 life expectancy in, 14, 303 lifetime inequality in, 26, 311 living standards in, xii, 14–15, 16, 24, 25, 26, 95, 98, 99, 183–84, 240, 266, 267, 268 median income in, 22, 295–96, 297, 299, 300 neighborhood segregation in, 75–76 opportunity in, xv, 3, 4, 17–20, 25, 75–76, 94–95, 108, 116, 117, 126, 127, 160, 265, 266, 268, 273, 275, 282, 287, 290 poverty in, 16–17, 26, 27, 38, 84, 298, 305, 306, 311, 332; see also poor value system of, xv, xvii, xx, 144, 187, 266, 288, 289, 292 wealth distribution in, 2, 3, 7, 8, 13–14, 24, 25, 32, 38, 56, 70, 72, 73, 76, 80, 82, 91, 93, 108, 147, 167, 171, 172, 202, 275, 295, 384 see also economy, U.S.; government, U.S.; politics, U.S.

The Billionaire's Apprentice: The Rise of the Indian-American Elite and the Fall of the Galleon Hedge Fund
by Anita Raghavan
Published 4 Jun 2013

Their conversations were freewheeling and they kidded each other like brothers. While Rajaratnam and Goel had stayed in touch intermittently during the eighties and nineties, their friendship blossomed after Goel started working at Intel’s Treasury department in January 2000. In 2003, reeling from the aftershocks of the collapse in the technology bubble, Galleon closed its California office. Rajaratnam asked Goel to do him a favor: could he keep an eye out for the happenings in Silicon Valley? He told Goel he was interested in learning about the ups and downs of the real estate market and getting a sense of people’s moods. The questions seemed innocuous enough.

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

See also Special situation investing Static hedging Statistical arbitrage strategy Statistical prediction Sticky businesses Stops Subprime mortgages/bonds Systematic trend-following strategy Systematic value approach TABX index Tangible book value (TBV) Tangible common equity Taylor, Martin Technical Analysis (Edwards and McGee) Technology bubble. See also Dot-com bubble TED spread Thames River Capital Management Thorp, Edward firsts achieved by gambling experiments and strategies option pricing model statistical arbitrage strategy warrant pricing model Time arbitrage Time horizons Time value Trade implementation Traders, hiring Trade size.

Age of Greed: The Triumph of Finance and the Decline of America, 1970 to the Present
by Jeff Madrick
Published 11 Jun 2012

It is worth summarizing the list of such crises we have already discussed: the defaults on Third World debt in 1982; the stock market crash of 1987; the thrifts failures and junk bond collapse culminating in 1989 and 1990; the Mexican debt crisis in 1994; the Asian financial crisis in 1997; the Russian default in 1998; the collapse of Long-Term Capital Management, also in 1998; and the bursting of the high-technology bubble beginning in 2000. Even given this list, the 2008 crisis, as noted, was much worse. Partly it had to do with excess dollars around the world. There was a rapidly rising flow of capital from overseas countries like China, which had increased its reserves of dollars to several trillion dollars, making funds available for borrowing in the United States at low rates.

Reminiscences of a Stock Operator
by Edwin Lefèvre and William J. O'Neil
Published 14 May 1923

Paul and Pacific Railroad. In 1869, he started his own transportation and fuel firm, notable for being the first to bring coal to the St. Paul area. This was period of intense growth for the railroad industry. The promise of a new technology encouraged overinvestment not unlike the Internet technology bubble of the late 1990s. At the time, St. Paul was having its first experience with railroads. It was unsuccessful, with 100 miles of track built “into space which were said to begin and end nowhere,”5 according to one account. After the venture went bankrupt for debts of $30 million and “a few streaks of rust and a right of way” as its only assets, Hill swooped in and acquired the property in 1878 for $100,000.6 So was born the railroad that would eventually become the Great Northern.

The Quest: Energy, Security, and the Remaking of the Modern World
by Daniel Yergin
Published 14 May 2011

Justice Department helped that “undermining” with its far-reaching antitrust cases against both companies.) Others have a different perspective. Robert Metcalfe sees the possibility of a green tech and global-warming bubble that will end with a crash. But from a big-picture perspective, that will accelerate the development of new technologies. “Bubbles accelerate innovation,” said Metcalfe. And one spin-off from innovation is “surprises.”17 Actual experience has been mixed. There have been some strategic sales and some high-profile IPOs that rival Internet or information-technology start-ups. But the general learning for members of the venture community is that energy is a harder road than they had thought from their experience in other sectors.

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

In June 1999, the Federal Reserve embarked on a campaign to raise interest rates in order to quell the rapid pace of economic growth and the rampant pace of speculative fervor building up in the equity market (the Fed did not target the stock market per se, but the market’s impact on economic growth). The Fed continued to raise interest rates for many months, and in early 2000 the Fed’s actions began to work their way into the U.S. financial system, transmitting through a number of channels, causing financial conditions to tighten dramatically. Indeed, the technology bubble of 1999–2000 burst, sending technology stock prices sharply lower and inducing so-called negative wealth effects. This resulted in a weakening of consumer spending. In addition to the stock market decline, the yield spread between corporate bonds and Treasury bonds began to widen sharply, particularly the spread between low-grade corporate bonds and Treasuries.