What Do Humans Perceive in Asset Returns?2019
In this article, the authors run experiments to test if and how human subjects can differentiate time series of actual asset returns from time series that are generated synthetically via various processes, including AR1. In contrast with previous anecdotal evidence, they find that subjects can distinguish between the two. These results show that temporal charts of asset prices convey to investors information that cannot be reproduced by summary statistics. They also provide a first refutation based on human perception of a strong form of the efficient-market hypothesis. Their experiments are implemented via an online video game (http://arora.ccs.neu.edu). The authors also link the subjects’ performance to statistical properties of the data and investigate whether subjects improve performance while playing.
This two-volume set brings together a unique collection of key publications at the intersection of biology and economics, two disciplines that share a common subject: Homo sapiens. Beginning with Thomas Malthus–whose dire predictions of mass starvation due to population growth influenced Charles Darwin–economists have routinely used biological arguments in their models and methods. This collection summarizes the most important of these developments, including articles in sociobiology, evolutionary psychology, behavioral ecology, behavioral economics and finance, neuroeconomics, and behavioral genomics. Together with an original introduction by the editors, this important research collection will appeal to economists, biologists, and practitioners looking to develop a deeper understanding of the limits of Homo Economicus.
All the News that’s Fit to Print2018
The information revolution has transformed everyday life for billions of people throughout the world. For example, according to mobile phone research group GSMA Intelligence, there are currently over 5 billion unique mobile phone subscribers, out of an estimated global population of 7.6 billion. This is the equivalent of a mobile phone for every person on the planet between the ages of 15 and 65.
Is Smaller Better? A Proposal to Use Bacteria for Neuroscientific Modeling2018
Bacteria are easily characterizable model organisms with an impressively complicated set of abilities. Among them is quorum sensing, a cell-cell signaling system that may have a common evolutionary origin with eukaryotic cell-cell signaling. The two systems are behaviorally similar, but quorum sensing in bacteria is more easily studied in depth than cell-cell signaling in eukaryotes. Because of this comparative ease of study, bacterial dynamics are also more suited to direct interpretation than eukaryotic dynamics, e.g., those of the neuron. Here we review literature on neuron-like qualities of bacterial colonies and biofilms, including ion-based and hormonal signaling, and a phenomenon similar to the graded action potential. This suggests that bacteria could be used to help create more accurate and detailed biological models in neuroscientific research. More speculatively, bacterial systems may be considered an analog for neurons in biologically based computational research, allowing models to better harness the tremendous ability of biological organisms to process information and make decisions.
Variety Is the Spice of Life: Irrational Behavior as Adaptation to Stochastic Environments2018
The debate between rational models of behavior and their systematic deviations, often referred to as “irrational behavior”, has attracted an enormous amount of research. Here, we reconcile the debate by proposing an evolutionary explanation for irrational behavior. In the context of a simple binary choice model, we show that irrational behaviors are necessary for evolution in stochastic environments. Furthermore, there is an optimal degree of irrationality in the population depending on the degree of environmental randomness. In this process, mutation provides the important link between rational and irrational behaviors, and hence the variety in evolution. Our results yield widespread implications for financial markets, corporate behavior, and disciplines beyond finance.
Half of all Americans have money in the stock market, yet economists can't agree on whether investors and markets are rational and efficient, as modern financial theory assumes, or irrational and inefficient, as behavioral economists believe—and as financial bubbles, crashes, and crises suggest. This is one of the biggest debates in economics and the value or futility of investment management and financial regulation hang on the outcome. In this groundbreaking book, Andrew Lo cuts through this debate with a new framework, the Adaptive Markets Hypothesis, in which rationality and irrationality coexist.
Drawing on psychology, evolutionary biology, neuroscience, artificial intelligence, and other fields, Adaptive Markets shows that the theory of market efficiency isn't wrong but merely incomplete. When markets are unstable, investors react instinctively, creating inefficiencies for others to exploit. Lo's new paradigm explains how evolution shapes behavior and markets at the speed of thought—a fact revealed by swings between stability and crisis, profit and loss, and innovation and regulation.
A fascinating intellectual journey filled with compelling stories, Adaptive Markets starts with the origins of market efficiency and its failures, turns to the foundations of investor behavior, and concludes with practical implications—including how hedge funds have become the Galápagos Islands of finance, what really happened in the 2008 meltdown, and how we might avoid future crises.
This is Your Brain on Stocks2017
Ever since I was a graduate student in economics, I’ve been struggling with the uncomfortable observation that economic theories often don’t seem to work in practice. That goes for that most influential economic theory, the Efficient Markets Hypothesis, which holds that investors are rational decision makers and market prices fully reflect all available information, that is, the “wisdom of crowds.”
The Growth of Relative Wealth and the Kelly Criterion2017
We propose an evolutionary framework for optimal portfolio growth theory in which investors subject to environmental pressures allocate their wealth between two assets. By considering both absolute wealth and relative wealth between investors, we show that different investor behaviors survive in different environments. When investors maximize their relative wealth, the Kelly criterion is optimal only under certain conditions, which are identified. The initial relative wealth plays a critical role in determining the deviation of optimal behavior from the Kelly criterion regardless of whether the investor is myopic across a single time period or maximizing wealth over an infinite horizon. We relate these results to population genetics, and discuss testable consequences of these findings using experimental evolution.
Stop-loss Strategies with Serial Correlation, Regime Switching, and Transaction Costs2017
Stop-loss strategies are commonly used by investors to reduce their holdings in risky assets if prices or total wealth breach certain pre- specified thresholds. We derive closed-form expressions for the impact of stop-loss strategies on asset returns that are serially correlated, regime switching, and subject to transaction costs. When applied to a large sample of individual U.S. stocks, we show that tight stop-loss strategies tend to under-perform the buy-and-hold policy in a mean-variance frame work due to excessive trading costs. Outperformance is possible for stocks with sufficiently high serial correlation in returns. Certain strategies succeed at reducing downside risk, but not substantially.
Hedge Fund Holdings and Stock Market Efficiency2017
We examine the relation between changes in hedge fund equity holdings and measures of informational efficiency of stock prices derived from intraday transactions as well as daily data. On average, hedge fund ownership of stocks leads to greater improvements in price efficiency than mutual fund or bank ownership, especially for stocks held by hedge funds with high portfolio turnover and superior security selection skills. However, stocks held by hedge funds experienced large declines in price efficiency in the last quarter of 2008, particularly if the funds were connected to Lehman Brothers as a prime broker and used leverage in combination with lenient redemption terms.
What Can Mother Nature Teach Us About Managing Financial Systems?2016
During a half-hour interval on May 6, 2010, stock prices for some of the largest companies in the world dropped precipitously, some to just pennies a share. Then, just as suddenly and inexplicably, shares recovered to their pre-crash prices. This unprecedented event, burned into the memories of investors and regulators alike, is now known as the Flash Crash. Since that day, financial markets have seen flash crashes in US Treasury securities, foreign currencies, and exchange-traded funds (ETFs). Other puzzling, system-wide glitches are becoming more frequent as well. Without a doubt, our financial systems are complex and often unpredictable, and when they swing out of control they remind us how much we still have to learn about how they work and how inadequate our traditional methods of controlling them are.
What Is An Index?2016
Technological advances in telecommunications, securities exchanges, and algorithmic trading have facilitated a host of new investment products that resemble theme-based passive indexes but which depart from traditional market-cap-weighted portfolios. I propose broadening the definition of an index using a functional perspective—any portfolio strategy that satisfies three properties should be considered an index: (1) it is completely transparent; (2) it is investable; and (3) it is systematic, i.e., it is entirely rules-based and contains no judgment or unique investment skill. Portfolios satisfying these properties that are not market-cap-weighted are given a new name: “dynamic indexes.” This functional definition widens the universe of possibilities and, most importantly, decouples risk management from alpha generation. Passive strategies can and should be actively risk managed, and I provide a simple example of how this can be achieved. Dynamic indexes also create new challenges of which the most significant is backtest bias, and I conclude with a proposal for managing this risk.
The Gordon Gekko Effect: The Role of Culture in the Financial Industry2016
Culture is a potent force in shaping individual and group behavior, yet it has received scant attention in the context of financial risk management and the recent financial crisis. I present a brief overview of the role of culture according to psychologists, sociologists, and economists, and then present a specific framework for analyzing culture in the context of financial practices and institutions in which three questions are answered: (1) What is culture?; (2) Does it matter?; and (3) Can it be changed? I illustrate the utility of this framework by applying it to five concrete situations—Long Term Capital Management; AIG Financial Products; Lehman Brothers and Repo 105; Société Générale’s rogue trader; and the SEC and the Madoff Ponzi scheme—and conclude with a proposal to change culture via “behavioral risk management.”
The Wisdom of Crowds Vs. the Madness of Mobs2015
Intelligence does not arise only in individual brains; it also arises in groups of individuals. This is collective intelligence: groups of individuals acting collectively in ways that seem intelligent. In recent years, a new kind of collective intelligence has emerged: interconnected groups of people and computers, collectively doing intelligent things. Today these groups are engaged in tasks that range from writing software to predicting the results of presidential elections. This volume reports on the latest research in the study of collective intelligence, laying out a shared set of research challenges from a variety of disciplinary and methodological perspectives. Taken together, these essays—by leading researchers from such fields as computer science, biology, economics, and psychology—lay the foundation for a new multidisciplinary field.
Macroeconomic Modeling and Financial Stability: Lessons from the Crisis2014
The dynamic stochastic general equilibrium model (DSGE) marked a major milestone by capturing the dynamic change of economic variables over time. However, many DSGE models were exposed as having omitted critical structural linkages relevant to the financial crisis. To address these deficiencies, existing DSGE models should be enhanced to better incorporate the role of the financial sector and financial markets. In addition, these models should reexamine key micro-foundations of the model and consider behavioral components.