market friction

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

Many financial intermediaries and investors became forced sellers as market frictions prevented them and other investors from taking advantage of good deals or nearly riskless arbitrage opportunities. Opportunities that appeared compelling over the long horizon could not be taken due to the possibility that further de-levering and related mark-to-market volatility would make the investment positions unsustainable over the short run. A diverse literature on market frictions explains why asset prices might deviate from fair values or respond sluggishly to new information. However, few asset-pricing models relate asset risk premia to market frictions such as funding and liquidity constraints.

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• Market segmentation effects may be even more pronounced across countries given that the liberalization of foreign capital flows is incomplete. The full integration of all countries into global markets is a hoped-for outcome, not a reality. Market frictions and illiquidity premia The impact of supply–demand factors—and of investor irrationalities—on asset prices is made possible by market frictions. Frictions related to illiquidity, funding constraints, and trading costs, as well as counterparty risk, agency concerns, and other information problems can be first-order important, as the 2008 experience shows. Bearish expectations, elevated risk, and risk aversion do not alone explain the distressed price levels of securitized bonds and other assets.

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The long bull trend in emerging market assets amidst a gradual improvement in emerging market fundamentals is another example where data are consistent with investor irrationality as well as rational learning. Peso problems and learning stories help in interpreting past return predictability but contain no lessons about future profit opportunities. Market frictions Most academic predictability evidence is presented without taking into account trading costs and other market frictions. It is not surprising, then, that paper profits tend to be most consistent in illiquid assets (e.g., small-cap stocks) or in trading styles that involve high turnover (e.g., short-term reversal). Faced with evidence of profitable trading strategies, it is always reasonable to question whether trading cost estimates (including both direct costs and market impact) have been understated.

The Inner Lives of Markets: How People Shape Them—And They Shape Us
by Tim Sullivan
Published 6 Jun 2016

Airbnb is an epic leap forward when compared to the epic leap of faith involved in renting a room via its predecessors, the classified ads or Craigslist. But let’s not confuse a set of groundbreaking market innovations with the end of market frictions. Yes, there are entire websites devoted to Airbnb horror stories—the trashed homes, the tenant-turned-squatter. There’s an equal number of angry rants directed at Uber. Neither of us rents our idle real estate assets when we’re out of town and not because we’re old-fashioned. We’ve also experienced market frictions of a more mundane variety. In writing this book we went to Washington to interview George Akerlof of market-for-lemons fame. As a bit of add-on market research, one of us, Ray, decided to rent an apartment for the night via Airbnb.

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But to get your $60 billion valuation, you need to create as many frictions as possible for everyone else. Although proponents of the sharing economy tout its ability to reduce market frictions, the only way they’re going to make the kinds of profits they (and their investors) want is to create new ones. That’s something they’re not interested in talking about to the public at large, or to their representatives in government. This leaves a bit of a paradox in the techno-utopian free-market narrative. A great entrepreneur will use technology to create a fantastic new market, then will use technology to set up market frictions to protect it. As entrepreneur and venture capitalist Peter Thiel wrote in the Wall Street Journal, “Competition Is for Losers.”12 Don’t get us wrong.

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If friction—informational, transactional, contractual—is all that stands between textbook economic models and the functioning of our real economy, then there is a vocal contingent out there (“there” being mostly Silicon Valley) that sees technology as the solution. When viewed through the lens of market frictions, the much-hyped notion of the sharing economy can be seen as an effort to bring free-market salvation to bricks, mortars, and automobiles. If you’ve ever tried to hail a taxi in San Francisco or rent a room in Washington, DC, you know the frictions of which we speak. The Bay Area’s sprawl, combined with strict regulations on the cab and livery businesses, used to leave you at the mercy of the two thousand or so taxi medallion holders that covered San Francisco’s 230 square miles.

Ghost Work: How to Stop Silicon Valley From Building a New Global Underclass
by Mary L. Gray and Siddharth Suri
Published 6 May 2019

In Proceedings of the 25th International Conference on World Wide Web, WWW ’16, pages 1293–1303, Republic and Canton of Geneva, Switzerland, 2016. © International World Wide Web Conference Committee. Used with permission. All rights reserved. Sara Constance Kingsley, Mary L. Gray, and Siddharth Suri. “Accounting for Market Frictions and Power Asymmetries in Online Labor Markets.” Policy & Internet, 7(4):383–400, 2015. © 2015 Policy Studies Organization. Used with permission by Wiley Periodicals, Inc. All rights reserved. hmhbooks.com Library of Congress Cataloging-in-Publication Data Names: Gray, Mary L., author. | Suri, Siddharth, author.

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Nobel laureate Ronald Coase, a key contributor to modern economic theory, popularized the notion of transaction costs, though he did not coin the phrase itself. His seminal 1937 article “The Nature of the Firm” was published only two years after Wagner passed the National Labor Relations Act. In it, Coase argued that businesses had to coordinate their operations, such as finding, hiring, and training workers, to reduce market frictions. The only route to lower costs and to turning a profit hinged on making businesses run as smoothly as possible. In essence, he was the first economist to theorize how to produce at scale through modern private enterprise and profit from a well-oiled org chart. Ghost work economies sell themselves as software that can eliminate the expensive frictions of searching, matching, training, communicating with, and retaining workers.

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“The Rise and Nature of Alternative Work Arrangements in the United States, 1995–2015.” NBER Working Paper Series, no. 22667, National Bureau of Economic Research, Cambridge, MA, September 2016. https://doi.org/10.3386/w22667. Kingsley, Sara Constance, Mary L. Gray, and Siddharth Suri. “Accounting for Market Frictions and Power Asymmetries in Online Labor Markets.” Policy & Internet 7, no. 4 (December 1, 2015): 383–400. https://doi.org/10.1002/poi3.111. Kuehn, Kathleen, and Thomas F. Corrigan. “Hope Labor: The Role of Employment Prospects in Online Social Production.” Political Economy of Communication 1, no. 1 (May 16, 2013). http://www.polecom.org/index.php/polecom/article/view/9.

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

One driver of investment is how low the real interest rate is, which depends in part on the inflation risk premium (i.e., stable inflation is best) and the rule of law. Also, supply shocks can arise from changes in labor-market frictions (sticky wages, search frictions, and rigid labor laws), product-market frictions (sticky prices and anticompetitive corporate measures), and capital-market frictions (market and funding illiquidity) leading to unemployment and lower capital utilization. For instance, a systemic banking crisis slows growth because the ability to finance projects is a driver of investment. In the long run, output depends on supply factors such as technological progress and population growth. 11.4.

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Investors are willing to bear these costs and fees when they are outweighed by the profits that the manager is expected to extract from the efficiently inefficient market. How close are prices and returns to their fully efficient values in an efficiently inefficient market? Well, because of competition, securities’ returns net of all the relevant market frictions—transaction costs, liquidity risk, and funding costs—are very close to their fully efficient levels in the sense that consistently beating the market is extremely difficult. However, despite returns being nearly efficient, prices can deviate substantially from the present value of future cash flows.

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The Law of One Price breaks down when arbitrage opportunities arise in currency markets (defying the covered interest rate parity), credit markets (the CDS-bond basis), convertible bond markets, equity markets (Siamese twin stock spreads), and option markets. Investors exercise call options and convert convertible bonds before maturity and dividend payments when they need to free up cash or face large short sale costs (defying Merton’s Rule). The financial market frictions influence the real economy, and unconventional monetary policy, such as central banks’ lending facility, can be important in addressing liquidity draughts.4 TABLE I.1. PRINCIPLES OF NEOCLASSICAL FINANCE AND ECONOMICS VS. THOSE IN AN EFFICIENTLY INEFFICIENT MARKET Neoclassical Finance and Economics Efficiently Inefficient Markets Modigliani–Miller Irrelevance of capital structure Capital structure matters because of funding frictions Two-Fund Separation Everyone buys portfolios of market and cash Investors choose different portfolios depending on their individual funding constraints Capital Asset Pricing Model Expected return proportional to market risk Liquidity risk and funding constraints influence expected returns Law of One Price and Black–Scholes No arbitrage, implied derivative prices Arbitrage opportunities arise as demand pressure affects derivative prices Merton’s Rule Never exercise a call option and never convert a convertible, except at maturity/dividends Optimal early exercise and conversion free up cash, save on short sale costs, and limit transaction costs Real Business Cycles and Ricardian Equivalence Macroeconomic irrelevance of policy and finance Credit cycles and liquidity spirals driven by the interaction of macro, asset prices, and funding constraints Taylor Rule Monetary focus on interest rate policy Two monetary tools are interest rate (the cost of loans) and collateral policy (the size of loans) II.

Matchmakers: The New Economics of Multisided Platforms
by David S. Evans and Richard Schmalensee
Published 23 May 2016

Multisided Platforms In 1998, this important type of business didn’t have a name. That’s surprising, in retrospect. Many businesses had been built to reduce these sorts of market frictions, which economists tend to call transaction costs. Their basic business model had been around for thousands of years. But business schools didn’t teach classes on how to start or run businesses that help different parties get together to exchange value. Economists didn’t have a clue how these businesses worked. In fact, the companies that reduced these market frictions charged prices and adopted other strategies that economic textbooks insisted no sensible business would do.

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The bigger the friction, the greater the value the platform can potentially provide, the greater the opportunity for getting participants on board, and the greater the chance for the platform to make money. Knowing which type of participants benefits the most from eliminating that friction can guide decisions on ignition strategies as well as on pricing. Sometimes, as with OpenTable, the platform drastically reduces a clear market friction, and the issue is whether the friction is big enough to enable the platform to earn adequate revenue to cover all the costs of launching and running the platform. In other cases, the platform pioneer has identified a new way for participants to interact—one that no one recognized because there was no way to do it.

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Less than ten years later, in 2014, more than 84 percent of Kenyan mobile phone users, including many of the very poor, were able to use their mobile phones to transfer money to each other, to pay their bills, and to pay at stores.7 People can now also use new financial services available through their mobile money accounts to save money and take out loans, and many do.8 Increasingly, stores are accepting mobile money for payment. The way this happened in Kenya is a remarkable story of how a company figured out how to ignite a multisided platform in trying circumstances, to massively reduce important market frictions, and to provide financial services to millions of impoverished people. And it is a story of how multisided platforms—M-PESA and other mobile money schemes that have started in Kenya and elsewhere—are leapfrogging traditional industries. Kenyans don’t need to rely on banks for many financial services.

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

I remember making ample use of hyperbolic tangent functions to represent the value of information without having to worry about my estimates of expected returns getting too far above the bid or below the offer. Modeling stocks in a microstructure framework, for the purpose of earning a profit, is all about modeling market frictions. Bid/offer spreads are a market friction; so is the fact that markets have to open and close and that you cannot trade in unlimited size. This was hardly sexy stuff in the early 1990s, when all the rage was customized curvature in the form of structured derivative products or over-the-counter options. At that time, quantitative finance was all about improving upon Black-Scholes.

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Everything I had seen in the finance literature up to this point searched for market anomalies using closing prices or assumed continuous, single-price processes. And yet, this was not the way the world worked, I thought. Stocks trade in a double-auction framework. A trade results from someone hitting a bid, taking an offer, or two sides agreeing in the middle. So looking at how stocks moved short-term meant studying market frictions and the discreteness of how stocks moved from bid/offer to bid/offer. As far as I could tell, no one had studied this before. There was no box; so thinking out of it was all one could do. It was then I figured out how I wanted to make my mark. JWPR007-Lindsey April 30, 2007 16:14 Andrew J.

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See Schulman “Beating the Foreign Exchange Markets” (Sweeney), 190 Beder, Tanya Styblo, 285–294 Bedriftsøkonomusik Institutt (BI), 153–154 “Behavior of Stock Prices, The” (Fama), 266 Berman, Gregg E., 49–66 Bermudan Monte Carlo techniques, 174 Bernstein Fabozzi/Jacobs Levy Award, 192 Best practices, analysis (absence), 128 Bid/offer spreads, market friction, 325 381 Binary options (pricing), call spreads (usage), 122 Binomial trees, trinomial tree extension, 124 Blacher, Guillamume, 167 Black, Fischer, 11, 88, 172, 224 analytic software, development, 23 input, 217 Kahn visit, 44–45 Leinweber, meeting, 23 predecessor, 228 Black boxes, usage, 209 Black-Scholes and Beyond (Chriss), 124–125, 132 Black-Scholes-Merton option pricing formula, 278 Bloom, Norman, 25 Bloomberg, Mike (employ).

Reinventing the Bazaar: A Natural History of Markets
by John McMillan
Published 1 Jan 2002

The Nobel laureates’ critique has now been addressed. Modern economics has a lot to say about the workings of markets. Theorists have opened up the black box of supply and demand and peered inside. Game theory has been brought to bear on the processes of exchange. Examining markets up close, the new economics emphasizes market frictions and how they are kept in check. In 2001, this work received recognition with the award of the Nobel Prize in economics to George Akerlof, Michael Spence, and Joseph Stiglitz for laying the foundation, as the Nobel citation said, “for a general theory of markets with asymmetric information.” Expressed in mathematics and impenetrable jargon, these new ideas reside obscurely in the technical journals.

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Big effects can come from small transaction costs. Today’s economics has the problem of information at its core. The “biggest new concept in economics in the last thirty years,” Kenneth Arrow said in 2000, “is the development of the importance of information, along with the dispersion of information.”4 Two kinds of market frictions arise from the uneven supply of information. There are search costs: the time, effort, and money spent learning what is available where for how much. And there are evaluation costs, arising from the difficulties buyers have in assessing quality. A successful market has mechanisms that hold down the costs of transacting that come from the dispersion of information.

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Firms that contract out some of their production—buying rather than making—place their trust in the market mechanism. If markets achieve such impressive efficiencies, why are so many transactions deliberately taken out of the market and put into the planned sub-economies that are firms? Why isn’t everyone an independent contractor instead of a hired employee? The answer is that firms exist as a response to market frictions. Sometimes it is less expensive to run a hierarchy than to use the market. Whether a firm produces its inputs in-house or procures them from other firms depends on the relative costs of each form of transaction. One of the factors affecting this comparison, as Ronald Coase wrote in 1937, is the efficiency with which markets work.

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

Tough market conditions, an unexpected change in regulation, or terrorist events can destroy credible public companies overnight. r Transaction costs may wipe out all the profitability of stat-arb trading, particularly for investors deploying high leverage or limited capital. r The bid-ask spread may be wide enough to cancel any gains obtained from the strategy. r Finally, the pair’s performance may be determined by the sizes of the chosen stocks along with other market frictions—for example, price jumps in response to earnings announcements. Careful measurement and management of risks, however, can deliver high stat-arb profitability. Gatev, Goetzmann, and Rouwenhorst (2006) document that the out-of-sample back tests conducted on the daily equity data from 1967 to 1997 using their stat-arb strategy delivered Sharpe ratios well in excess of 4.

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Miller and P. Sandas, 2004. “Empirical Analysis of Limit Order Markets.” Review of Economic Studies 71, 1027–1063. Horner, Melchior R., 1988. “The Value of the Corporate Voting Right: Evidence from Switzerland,” Journal of Banking and Finance 12 (1), 69–84. Hou, K. and T.J. Moskowitz, 2005. “Market Frictions, Price Delay, and the CrossSection of Expected Returns.” Review of Financial Studies 18, 981–1020. References 315 Howell, M.J., 2001. “Fund Age and Performance,” Journal of Alternative Investments 4. No. 2, 57–60. Huang, R. and H. Stoll, 1997. “The Components of the Bid-ask Spread: A General Approach.”

Topics in Market Microstructure
by Ilija I. Zovko
Published 1 Nov 2008

Schwartz, editors, Market Making and the Changing Structure of the Securities Industry. Rowman & Littlefield, Lanham, 1985. T. E. Copeland and D. Galai. Information effects on the bid-ask spread. Journal of Finance, 38(5):1457–69, 1983. M. G. Daniels, J. D. Farmer, G. Iori, and E. Smith. Quantitative model of price diffusion and market friction based on trading as a mechanistic random process. Physical Review Letters, 90(10): Article no. 108102, 2003. H. Demsetz. The cost of transacting. The Quarterly Journal of Economics, 82:33–53, 1968. P. M. Dixon, J. Weiner, T. Mitchell-Olds, and R. Woodley. Bootstrapping the gini coefficient of inequality.

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

The last one is a crucial force limiting arbitrage. Even the “unconstrained” arbitrageur is limited from fully exploiting the available opportunities, especially assets/strategies with low natural volatility or highly diversified composites. Sometimes, these limits are even viewed as the original reason for certain regularities. Market frictions, such as prevalent investor constraints, can both cause a regularity (recall leverage constraints causing the low-beta factor) and prevent its undoing by arbitrage (the latter aspect applies to all long/short factors).3 Overall, for most premia it seems likely that both risk-based and behavioral explanations matter, and we can just debate their relative roles.

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Clearly, many investors care about portfolio characteristics beyond mean and variance. Other important preferences may include leverage, liquidity, ESG, and higher moments (e.g. skewness and tail risk). Moreover, a one-period, one-factor model in frictionless markets is hardly realistic; yet multi-period or multi-factor models add complexity, as do market frictions such as trading costs and taxes.13 The biggest error may be to deal with the wrong question or consider a too narrow investment opportunity set. Instead of doing an assets-only optimization, a pension plan could broaden its problem to include pension liabilities and optimize the asset-liability surplus.

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

.  (10.29) It follows that the MSE of the Fourier estimator does not diverge, and it is not significantly affected by microstructure noise; in fact, by conveniently choosing N , we obtain that MSEF and MSEFm differ by the positive constant term (Eq. 10.29). We conclude that the Fourier estimator needs no correction in order to be asymptotically unbiased and robust to market frictions of MA(1)-type, that is, the microstructure noise is represented by independent identically distributed random variables. The result is generalized to noise correlated with the efficient returns in Mancino and Sanfelici (2008). 10.3.2 MONTE CARLO ANALYSIS The theoretical results above can be reproduced by simulating discrete data from a continuous time stochastic volatility model with microstructure noise as in Mancino and Sanfelici (2008).

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Barndorff-Nielsen OE, Graversen SE, Jacod J, Shephard N. Limit theorems for bipower variation in financial econometrics. Economet Theor 2006;22(4):677–719. Barndorff-Nielsen OE, Hansen PR, Lunde A, Shephard N. Realized kernels can consistently estimate integrated variance: correcting realized variance for the effect of market frictions. Working paper, 2005. Barndorff-Nielsen OE, Hansen PR, Lunde A, Shephard N. Designing realized kernels to measure the ex-post variation of equity prices in the presence of noise. Econometrica 2008;76/6:1481–1536. Barndorff-Nielsen OE, Hansen PR, Lunde A, Shephard N. Multivariate realized kernels: consistent positive semi-definite estimators of the covariation of equity prices with noise and non-synchronous trading.

Trading and Exchanges: Market Microstructure for Practitioners
by Larry Harris
Published 2 Jan 2003

Regulators like liquidity because liquid markets are often less volatile than illiquid ones. * * * ▶ Market Frictions Economists like liquid markets—securities markets, contract markets, product markets, and labor markets—because their models work better when they do not have to consider how transaction costs affect economic decisions. When confronted with transaction costs, people trade less often. If the costs are high enough, they do not trade at all. Transaction costs in an economic system therefore are like frictions in a mechanical system. They both slow things down and can ultimately stop all activity. Economists therefore call transaction costs market frictions. ◀ * * * Everyone in the markets has some affect on liquidity.

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See minimum price increment ticker symbols, 27, 99–101 ticker tapes, 98, 498 tick-sensitive orders, 81, 87 tight spread, 280 time, 309 time-delayed services, 98 time precedence rules, 113–14, 117, 537 Time Slicing, 290 time travel, 180 timing of market, 450 timing option, 307, 308, 506 Tokyo Stock Exchange, 92 tolls, 209 tomato forward contract, 41 top of the book, 101, 504 Toronto Stock Exchange, 35, 99, 389 totalizator system, 91 total return, 445 total volatility, 414 touch, 70 touch price, 80 toxic waste, 41 T + 3 settlement, 36 tracking errors, 486 trade prices, 70 trade pricing rules, 90, 94, 112, 115–16, 120 traders accuracy in oral communications, 107–9 aggressive, 246, 423 in brokered markets, 95 clean up after hours, 92 clearing and settlement among, 141 contrarian, 79, 429 credit checks, 142 definition of, 32 in order-driven markets, 95 orders, 68–88 profit-motivated, 177, 194–97, 198 risks of standing limit orders, 77 self-regulatory associations, 64 taxonomy of types, 199 untrustworthy, 324, 326 See also informed traders; trader surplus; trades and trading; specific types of traders, e.g., utilitarian traders traders of last resort, 497 trader surplus definition of, 123 examples of, 123, 125 measuring, 124 in single price auction, 122–2 5 trader timing, 437 trades and trading cash commodity and futures market, 22–26 with dealers, 281–82 facilitators, 34–36, 38, 248 foreign exchange, 29–30 free entry and exit, 7–8 futures market, 22–26, 39, 46 industry, 32–67 information asymmetries, 7 institutional in Nasdaq stock, 19–20 institutional in NYSE stock, 15–19 magnitude of, 45–47 markets, 44–59 overview of, 5–6 players in, 32–34, 145 private benefits of, 205 profits, 4, 7 public benefits of, 206 reasons for, 176–201, 252 retail in Nasdaq stock, 14–15 retail in NYSE stock, 11–14 rules, 7, 94, 95, 112, 113 straddle, 37 structure of, 31–174 and technology, 524–26 very large stock block, 20–22 See also bond(s); option(s); traders; trading instruments trading floors, 24–25, 90, 116 trading forums, 90 trading halts, 572, 573–75, 578 trading hours, 92 trading instruments definition of, 38 derivative contracts, 41–42 financial assets, 39–41 gambling contracts, 43 hybrid contracts, 43–44 insurance contracts, 43 real assets, 39 trading pits, 24–25, 90, 116 Trading Places (movie), 242 trading posts, 90, 116 trading sessions, 89, 90–92 Trading System View (TSV), 48, 51 trading window, 588 tranches, 41 Transaction Auditing Group, 424, 519 transaction costs, 4 and active managers, 488 components, 421–22 definition of, 180, 421 econometric estimation methods, 422, 423, 432, 434 estimation methods, 422–23 estimator biases, 428–31 gaming problem, 430–31 and hedging, 188 implicit, 432, 434 intelligent management, 439–40 as market frictions, 394 measurment, 420–41 missed trade opportunity costs, 434, 436–38 and paying the spread, 71 prediction, 438–39 properties of price benchmark estimators, 427–32, 433 and public benefits of exchange, 214 specified price benchmark methods, 422, 423–27 trade timing issues, 427–28 transaction cost spread component, 299 transaction fees, 494 transaction taxes, 572, 575–76 transitory exchange for physical, 334 transitory price changes, 299 transitory price effect, 435 transitory spread component.

Capitalism and Freedom
by Milton Friedman
Published 1 Jan 1962

The potential gains, particularly to early entrants, are so great that it would be worth incurring extremely heavy administrative costs.10 Whatever the reason, an imperfection of the market has led to underinvestment in human capital. Government intervention might therefore be rationalized on grounds both of “technical monopoly,” insofar as the obstacle to the development of such investment has been administrative costs, and of improving the operation of the market, insofar as it has been simply market frictions and rigidities. If government does intervene, how should it do so? One obvious form of intervention, and the only form that has so far been taken, is outright government subsidy of vocational or professional schooling financed out of general revenues. This form seems clearly inappropriate. Investment should be carried to the point at which the extra return repays the investment and yields the market rate of interest on it.

Empirical Market Microstructure: The Institutions, Economics and Econometrics of Securities Trading
by Joel Hasbrouck
Published 4 Jan 2007

Each of the other 99 customers will perceive an opportunity cost of $10 (=$110 − $100) and may well attribute this to sloth on the part of their brokers or their systems. Thus, the aggregate opportunity cost is $990, for an aggregate implementation shortfall of $991. It is nonsensical, of course, to suggest that aggregate welfare could be enhanced by this amount if market frictions or broker ineptitude were eliminated. The problem is that the benchmark price of π0 = $100 does not come close, given the new information, to clearing the market. The profits realized by the lucky first trader are akin to lottery winnings. Individual traders might attempt to gain advantage by increasing the speed of their order submission linkages, but because only one trader can arrive first, the situation is fundamentally a tournament (in the economic sense). 14.2.1 The Implementation Cost for Liquidity Suppliers Is implementation cost a useful criterion for liquidity suppliers?

Humans as a Service: The Promise and Perils of Work in the Gig Economy
by Jeremias Prassl
Published 7 May 2018

Through technological innovation, from location tracking and user ratings, to sophisticated algorithms that match consumers and workers, whether purely online or in the real world, platforms have drastically reduced this friction: using Amazon’s MTurk, an economist in Australia can quickly find a student in the United States to help her to organize data in a large spreadsheet. Even better, matching isn’t the only market friction removed by the platform. In an open-market transaction with an independent entrepreneur, consumers would have to spend significant amounts of time and effort to find out information about the service provider’s background and experi- ence, control the quality of the work, and negotiate prices.

Where Does Money Come From?: A Guide to the UK Monetary & Banking System
by Josh Ryan-Collins , Tony Greenham , Richard Werner and Andrew Jackson
Published 14 Apr 2012

Since the rate charged on the loans is the Monetary Policy Committee’s policy rate, and the demand for reserves is met by the supply from the central bank, traded rates in the money market tend to be close to the policy rate. However, in some instances market rates can deviate from the policy rate. This is usually due to some kind of market friction or loss of confidence, or could result from a bank being short of reserves and unable to meet its commitments in the interbank market. If the central bank believes there is merit in supplying extra liquidity in the interbank market – normally indicated by the interbank rate (LIBOR or the actual rate paid by banks which may be known to the Bank of England) going significantly above the policy rate – it can make additional loans to the banks, collateralised by government securities, or it can engage in outright asset purchases.

What's Wrong With Economics: A Primer for the Perplexed
by Robert Skidelsky
Published 3 Mar 2020

But Walrasian equilibrium requires contracts for future delivery of goods and services at prices which can only be guessed at. A great deal of trading in actual markets therefore takes place at the ‘wrong’, or disequilibrium, prices. This means that equilibrium cannot be proved to be the result of a myriad of voluntary transactions in markets. Frictions in the social world are much more severe than those in physics, because they are caused by the human beings whose behaviour we are trying to explain. Thus the existence of frictions such as ‘sticky wages’ might explain persisting unemployment. To the fervent globalist, nations are frictions to the more perfect integration of markets.

The Road to Somewhere: The Populist Revolt and the Future of Politics
by David Goodhart
Published 7 Jan 2017

Global villagers, who generally regard the nation state as a hindrance to desirable economic and social outcomes, have had too loud a voice in the globalisation story in the past generation. It was their choices that led to hyperglobalisation, including at the regional level with the attempt to create a single fiscal and economic space within the European Union. Under the banner of free global trade and European integration they battled against the market ‘frictions’ which many people regard as vital national interests. As Rodrik points out, the US, Japan and Europe have all grown rich with very different histories and institutional arrangements governing labour markets, corporate governance, welfare systems and approaches to regulation. ‘That these nations have managed to generate comparable amounts of wealth under different rules is an important reminder that there is not a single blueprint for economic success.’

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

David, 184 Mean reversion: of higher moments, 118–119 at longer horizons, 115–117 and momentum, 73, 77–82 for value investors, 180 Mean-variance optimization: CAPM derived from, 7 debate over, 211 full-scale optimization vs., 198, 203–207 modified versions of, 204–207 peer group risk constraint with, 210 problems with, 203–204 “Mean-Variance Versus Full-Scale Optimisation” (Kritzman and Adler), 204 Merton, Robert C., 127–128, 187 Michaud, Richard, 208 Miller, Merton, 7 “The Mismeasurement of Risk” (Kritzman and Rich), 168–169 Modern Portfolio Theory and Investment Analysis (Elton and Gruber), 6 Moments, 118 (See also Higher moments) Momentum, 69–82, 179–180, 256 for bonds, 75–76 and diversification, 130 and mean reversion, 73, 77–82 and overreaction, 73–75 and time horizons, 71–73, 75–76 and valuation, 61, 70–82 Monetary easing, 17 Moreira, Alan, 100, 106–107 Morillo, Daniel, 236 Mortgage-backed securities, 127 Moskowitz, Toby, 182 Mossin, Jan, 6 Moussawi, Rabih, 237 MSCI World Index, 218 Mueller, Mark, 85–86 Muir, Tyler, 100, 106–107 Multivariate distance, 205 “The Myth of Diversification” (Chua, Kritzman, and Page), 122–123, 127 Naik, Narayan Y., 128 Naik, Vasant, 14, 59, 67, 132 Nallareddy, Suresh, 236–237 Negative skewness, 103, 104, 112 and exposure to loss, 144 frequency of, 118 positive skewness vs., 207 of volatility risk premium, 106 Nielsen, Lars N., 102 Nonnormal returns, 9 Northern Trust, 14 Novy-Marx, Robert, 181 Nowobilski, Andrew, 59 O’Connell, Paul, 31 “Optimal Hedge Fund Allocations” (Cremers, Kritzman, and Page), 204 “Optimal Portfolio in Good Times and Bad” (Chow et al.), 204–206 Option writing, Volatility Index and, 109 Outliers, 148 Overfitting, 183 Page, Jean-Paul (JPP), 265–269 on abnormal profits, 231 on accounting for risk, 217 on asset allocation, 247 on beta, 175 on efficiency of markets, 93 on finance, 61, 83, 265, 271–272 on financial analysis, 45 on hypotheses behind models, 1 on interest rates, 5 on market frictions, 69 on measuring risk, 89 on models, 197 on Modern Portfolio Theory, 173 on normal distributions, 147 on quality of models, 121 on standard deviation, 111 on theoretical foundations of asset allocation, 271–274 on utility theory, 185 on valuation, 25 Panariello, Rob: and correlations, 140 and diversification, 122–125, 127–129 on fear, 234 and persistence of volatility, 113–114 and public vs. private equity, 228 and stock picking, 233 Park, James, 102–104 Passive investments, 269 active investments vs., 226, 231–243, 269 and blend portfolios, 233 mispricings and abnormal correlations with, 236 and stock picking, 243 “The P/B-ROE Valuation Model” (Wilcox), 28–29 Pedersen, Lasse Heje, 180, 182 Pedersen, Niels, 15–16, 59, 129, 132 Peer group risk constraint, 210 Pelizzon, Loriana, 128 Pension funds, 128, 219 “The Performance of Private Equity Funds” (Phalippou and Gottschlag), 222–224 Persistence in risk measures, 113, 148 and data frequency, 114–115 higher moments, 117–119 mean reversion at longer horizons, 115–117 volatility, 113–114, 156 Personal finance, 186–188 Phalippou, Ludovic, 222–224 PIMCO, 14, 27 Pioneering Portfolio Management (Swensen), 129 Pontiff, Jeffrey, 184 Poon, Ser-Huang, 90–91 Portfolio construction, 173–174, 268, 273 active vs. passive investments in, 231–243 with alternative assets, 229–230 asset class allocation in, 185–195 asset classes in, 173–184 full-sample correlations in, 134 private assets in, 217–229 rules of thumb for, 243–244 simplifying problem of, 203–207 single-period portfolio optimization, 197–215 stocks vs. bonds in, 185–195 strategic asset allocations for, 247–263 target-date funds in, 190–195 utility maximization in, 199–203 “The Portfolio Flows of International Investors” (Froot, O’Connell, and Seasholes), 31 Portfolio optimization, 173 allocation of stocks vs. bonds for, 193–194 mean-variance, 198, 203–207 methodologies for, 134 risk factors models in, 178–179 single-period, 194–195, 197–215 at T.

Radical Markets: Uprooting Capitalism and Democracy for a Just Society
by Eric Posner and E. Weyl
Published 14 May 2018

For example, a controversy raged in 2017 over Google’s role in the firing of a policy researcher critical of their business practices. 30. See Roland Bénabou & Jean Tirole, Intrinsic and Extrinsic Motivation, 70 Review of Economic Studies 489 (2003), for a survey of this literature. 31. Sara Constance Kingsley et al., Accounting for Market Frictions and Power Asymmetries in Online Labor Markets, 7 Policy & Internet 383 (2015). 32. Arindrajit Dube, Jeff Jacobs, Suresh Naidu, & Siddharth Suri, Monopsony in Crowdsourcing Labor Markets (Columbia University Working Paper, 2017). 33. https://www.nytimes.com/2016/05/06/business/facebook-bends-the-rules-of-audience-engagement-to-its-advantage.html?

Green Philosophy: How to Think Seriously About the Planet
by Roger Scruton
Published 30 Apr 2014

One of the great success stories of environmental management is that of smog – the curse of all major cities in the nineteenth and early twentieth centuries, now removed from Europe and America by laws governing household fuel. But the case also illustrates the dangers of regulation, which is apt to replace normal market friction with a regime of zero tolerance. The costs of enforcing clean air regulation in America have been so amplified by the EPA as to produce price distortions that are a serious tax on consumers.184 There are other reasons too for thinking that regulation alone will not prevent major polluters from externalizing their costs.

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

In Section II.5.3.7 we prove that the discrete time version of (I.3.142) is a stationary AR(1) model. I.3.7.3 Stochastic Models for Asset Prices and Returns Time series of asset prices behave quite differently from time series of returns. In efficient markets a time series of prices or log prices will follow a random walk. More generally, even in the presence of market frictions and inefficiencies, prices and log prices of tradable assets are integrated stochastic processes. These are fundamentally different from the associated returns, which are generated by stationary stochastic processes. Figures I.3.28 and I.3.29 illustrate the fact that prices and returns are generated by very different types of stochastic process.

No Slack: The Financial Lives of Low-Income Americans
by Michael S. Barr
Published 20 Mar 2012

The information might improve comparison shopping. Of course, revealing such information would also reduce broker and creditor profit margins. But as the classic market competition model relies on full information and assumes rational behavior based on understanding, this proposal attempts to remove market frictions from information failures and to move market competition more toward its ideal. De-biasing consumers would reduce information asymmetry and lead to better competitive outcomes. Improving Truth in Lending Optimal disclosure will not occur in all markets through competition alone because in some contexts firms have incentives to hide information about products or prices and consumers may not insist on competition based on transparency because they misforecast their own behavior.

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

Short-term price patterns considered here are of two kinds: the pattern could be a form of price drift, where the price continues to move in the same direction, or it could be a price reversal where the 56 Short-Term Price Drift price moves in the opposite direction. These price patterns may be due to market frictions, a result of market inefficiency, or related to information arrival. The earliest documentation of short-term price drift is related to earnings announcements, in which it was found that firms with surprisingly good earnings earn abnormal returns of about 2 percent in the following three months, whereas firms with surprisingly bad earnings lose abnormally.

The Euro: How a Common Currency Threatens the Future of Europe
by Joseph E. Stiglitz and Alex Hyde-White
Published 24 Oct 2016

Since the start of the euro, it continues as what is sometimes called ERM II, a band linking the Danish krone to the euro. 37 Though the basic idea of full employment is clear—that everyone who would like a job can get one at the prevailing wages for those with the individual’s skills and talents—there is some controversy over the precise definition of full employment. The general notion is that the labor market is just sufficiently loose—with job seekers matching employers looking for employees—that there is no inflationary pressure. Because of labor market frictions—it takes time to find a good match between employers and employees—this “natural rate” is greater than zero, normally around 2 to 3 percent. Unemployment might also exist because of rigidities in the adjustment of relative wages—the labor market for skilled labor might be so tight that wages are rising, but there may still be unemployment of unskilled workers.

Virtual Competition
by Ariel Ezrachi and Maurice E. Stucke
Published 30 Nov 2016

Another key challenge is the legal and conceptual difficulty emerging from the relationship between man and machine—that is, humans’ con- The Enforcement Toolbox 223 trol (or lack of it) over machines, and their accountability for the algorithms’ activities.7 If algorithms collude or price discriminate, are humans liable? As several computer scientists have observed, “The amoral status of an algorithm does not negate its effects on society.”8 Or as one judge aptly noted, “Automation is effected through a human design.”9 In the context of competition and markets, friction among profit maximization, ethical trading, and consumer welfare exists. Current laws may not always resolve this friction and may fail to incentivize individuals to take responsibility for the actions of an “independent,” self-learning algorithm. When to Intervene and to What Extent Controversy may surround the timing of an intervention, its nature, and its extent.

The Tyranny of Nostalgia: Half a Century of British Economic Decline
by Russell Jones
Published 15 Jan 2023

The arcane Panglossian certainties of new classical theory, which embodied elements of monetarism, the rational expectations hypothesis (REH), real business cycle (RBC) theory and the efficient markets hypothesis (EMH) had been synthesised with new Keynesianism, or the attempt to incorporate certain Keynesian features into micro-founded models, by emphasizing how market ‘frictions’ could cause deviations from the optimal level of output. The stickiness of wages and prices within an REH framework was explained by considerations such as imperfect information and imperfect competition. This meant that markets did not clear instantaneously: they took time to do so. There could therefore be temporary demand shortages that pushed the actual unemployment rate above its ‘natural rate’, and on which macro policy, largely in the form of central bank action on official interest rates, could have an impact.

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

What is more, the dominant theories of world politics originally drew their underlying theoretic foundations from microeconomic models. These political theories, however, certainly did not anticipate what would happen if the security system became linked with a very real market, with all its dynamic shifts and uncertainties.2 THEORY AND THE MILITARY MARKET All markets do not operate perfectly, but instead often experience market friction, interference, and externalities, particularly when their structures are still emerging. With PMFs, the marketization of military services means that international security is complicated by potential market dynamism and disruptions. The "powers" are no longer exclusively sovereign states, but also include "interdependent players caught in a network of transnational transactions."3 169 O IMPLICATIONS In short, the privatized military industry represents alternative patterns of power and authority linked to the global market, rather than limited by the territorial state.

The Volatility Smile
by Emanuel Derman,Michael B.Miller
Published 6 Sep 2016

When the index moves sharply down, short-term implied volatility moves sharply up and the short-term negative skew steepens. Long-term volatility and the long-term skew increase too, but less so (Foresi and Wu, 2005). 6. Implied volatility tends to be greater than realized volatility. This is likely due to market frictions and other factors, including hedging costs, our inability to hedge perfectly, and uncertainty with regard to future volatility. We can think of implied volatility as the market’s expected future volatility plus some premium associated with the cost of these factors. Individual Equities Single-stock smiles tend to be more symmetric than index smiles.

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

The economy is ‘self-healing’. In technical terms, ‘the implication of real-business-cycle models, in their strongest form, is that observed aggregate output movements represent the time-varying Pareto optimum’.67 The New Keynesians preserved the basic framework of the New Classical RBC/DSGE models, but added ‘market frictions’, like monopolistic competition and nominal rigidities, to make the models more applicable to the real world.68 A pp e n di x 7.3: T h e c e n t r a l b a n k r e ac t ion f u nc t ion Pre-crash central bank policy combined New Classical and New Keynesian models. In New Keynesian models, monetary policy still plays a stabilizing role, ‘imperfections’ recreating a space between the short- and long-run.

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

Self-selection is the tendency of companies to split their stocks into lower denominations because of a prolonged rise in their share price, as shown in Exhibit 5.16. As a result, one should expect any sample of companies that 40 R. D. Boehme and B. R. Danielsen report over 6,000 stock splits between 1950 and 2000: “Stock-Split Post-Announcement Returns: Underreaction or Market Friction?” Financial Review 42 (2007): 485–506. D. Ikenberry and S. Ramnath report over 3,000 stock splits between 1988 and 1998: “Underreaction to Self-Selected News Events: The Case of Stock Splits,” Review of Financial Studies 15 (2002): 489–526. 41 There is ample evidence to show that this is not the case: after a split, trading volumes typically decline, and brokerage fees and bid-ask spreads increase, indicating lower liquidity, if anything.

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

We recommend the easy way when repurchases are important. Note also that the second way, which works out nicely in our example, becomes much more difficult to do precisely when repurchases are irregular or unpredictable. Our example illustrates several general points. First, absent tax effects or other market frictions, today’s market capitalization and share price are not affected by how payout is split between dividends and repurchases. Second, shifting payout to repurchases reduces current dividends but produces an offsetting increase in future earnings and dividends per share. Third, when valuing cash flow per share, it is double-counting to include both the forecasted dividends per share and cash received from repurchases.