The Origin of Risk Aversion2014
Risk aversion is one of the most basic assumptions of economic behavior, but few studies have addressed the question of where risk preferences come from and why they differ from one individual to the next. Here, we propose an evolutionary explanation for the origin of risk aversion. In the context of a simple binary-choice model, we show that risk aversion emerges by natural selection if reproductive risk is systematic (i.e., correlated across individuals in a given generation). In contrast, risk neutrality emerges if reproductive risk is idiosyncratic (i.e., uncorrelated across each given generation). More generally, our framework implies that the degree of risk aversion is determined by the stochastic nature of reproductive rates, and we show that different statistical properties lead to different utility functions. The simplicity and generality of our model suggest that these implications are primitive and cut across species, physiology, and genetic origins.
Dynamic Loss Probabilities and Implications for Financial Regulation2014
Much of financial regulation and supervision is devoted to ensuring the safety and soundness of financial institutions. Such micro- and macroprudential policies are almost always formulated as capital requirements, leverage constraints, and other statutory restrictions designed to limit the probability of extreme financial loss to some small but acceptable threshold. However, if the risks of a financial institution's assets vary over time and across circumstances, then the efficacy of financial regulations necessarily varies in lockstep unless the regulations are adaptive. We illustrate this principle with empirical examples drawn from the financial industry, and show how the interaction of certain regulations with dynamic loss probabilities can have the unintended consequence of amplifying financial losses. We propose an ambitious research agenda in which legal scholars and financial economists collaborate to develop optimally adaptive regulations that anticipate the endogeneity of risk-taking behavior.
Group Selection as Behavioral Adaptation to Systematic Risk2014
Despite many compelling applications in economics, sociobiology, and evolutionary psychology, group selection is still one of the most hotly contested ideas in evolutionary biology. Here we propose a simple evolutionary model of behavior and show that what appears to be group selection may, in fact, simply be the consequence of natural selection occurring in stochastic environments with reproductive risks that are correlated across individuals. Those individuals with highly correlated risks will appear to form “groups”, even if their actions are, in fact, totally autonomous, mindless, and, prior to selection, uniformly randomly distributed in the population. This framework implies that a separate theory of group selection is not strictly necessary to explain observed phenomena such as altruism and cooperation. At the same time, it shows that the notion of group selection does captures a unique aspect of evolution—selection with correlated reproductive risk–that may be sufficiently widespread to warrant a separate term for the phenomenon.
When Do Stop-Loss Rules Stop Losses?2014
We propose a simple analytical framework to measure the value added or subtracted by stoploss rules—predetermined policies that reduce a portfolio’s exposure after reaching a certain threshold of cumulative losses—on the expected return and volatility of an arbitrary portfolio strategy. Using daily futures price data, we provide an empirical analysis of stop-loss policies applied to a buy-and-hold strategy using index futures contracts. At longer sampling frequencies, certain stop-loss policies can increase expected return while substantially reducing volatility, consistent with their objectives in practical applications.
Fear, Greed, and Financial Crises: A Cognitive Neurosciences Perspective2013
Abstract Historical accounts of financial crises suggest that fear and greed are the common denominators of these disruptive events: periods of unchecked greed eventually lead to excessive leverage and unsustainable asset-price levels, and the inevitable collapse results in unbridled fear, which must subside before any recovery is possible. The cognitive neurosciences may provide some new insights into this boom/bust pattern through a deeper understanding of the dynamics of emotion and human behavior. In this chapter, I describe some recent research from the neurosciences literature on fear and reward learning, mirror neurons, theory of mind, and the link between emotion and rational behavior. By exploring the neuroscientific basis of cognition and behavior, we may be able to identify more fundamental drivers of financial crises, and improve our models and methods for dealing with them.
The Origin of Bounded Rationality and Intelligence2013
Rational economic behavior in which individuals maximize their own self-interest is only one of many possible types of behavior that arise from natural selection. Given an initial population of individuals, each assigned a purely arbitrary behavior with respect to a binary choice problem, and assuming that offspring behave identically to their parents, only those behaviors linked to reproductive success will survive, and less successful behaviors will disappear exponentially fast. This framework yields a single evolutionary explanation for the origin of several behaviors that have been observed in organisms ranging from bacteria to humans, including risk-sensitive foraging, risk aversion, loss aversion, probability matching, randomization, and diversification. The key to understanding which types of behavior are more likely to survive is how behavior affects reproductive success in a given population's environment. From this perspective, intelligence is naturally defined as behavior that increases the likelihood of reproductive success, and bounds on rationality are determined by physiological and environmental constraints.
What Post-Crisis Changes Does the Economics Discipline Need?: Beware of Theory Envy!2012
This is a pre-conference essay prepared for 'What Post-Crisis Changes Does the Economics Discipline Need?', a conference organized by Diane Coyle and Enlightenment Economics, the Bank of England, and the U.K. Government Economic Service on 7 February 2012. In this essay, I trace the origins of 'theory envy' to Paul Samuelson and the mathematization of economics over the past half century, and consider its implications for how economics should be taught. Although this research program has produced many genuine breakthroughs in economics, any virtue can become a vice when taken to an extreme, and the recent financial crisis has given us an opportunity to reinvent our field. One innovation is to teach economics not from an axiomatic and technique-oriented perspective, but by posing challenges that can only be addressed through economic logic. Instead of starting microeconomics with the consumer’s problem of maximizing utility subject to a budget constraint, begin by challenging students to predict the impact of a gasoline tax on the price of gasoline, or asking them to explain why diamonds are so much more expensive than water, despite the fact that the latter is critical for survival unlike the former. Instead of starting macroeconomics with national income accounts, begin with the question of how to measure and manage the wealth of nations, or why inflation can be so disruptive to economic growth. Without the proper institutional, political, and historical context in which to interpret economic models, constrained optimization methods and fixed-point existence proofs have much less meaning and are more likely to give rise to theory envy. However, when students understand the “why” of their course of study, even the most complex mathematical tools can be mastered and are almost always applied more meaningfully.
Adaptive Markets and the New World Order2012
In the Adaptive Markets Hypothesis (AMH) intelligent but fallible investors learn from and adapt to changing economic environments. This implies that markets are not always efficient, but are usually competitive and adaptive, varying in their degree of efficiency as the environment and investor population change over time. The AMH has several implications including the possibility of negative risk premia, alpha converging to beta, and the importance of macro factors and risk budgeting in asset-allocation policies.
An Evolutionary Model of Bounded Rationality and Intelligence2012
Most economic theories are based on the premise that individuals maximize their own self-interest and correctly incorporate the structure of their environment into all decisions, thanks to human intelligence. The influence of this paradigm goes far beyond academia–it underlies current macroeconomic and monetary policies, and is also an integral part of existing financial regulations. However, there is mounting empirical and experimental evidence, including the recent financial crisis, suggesting that humans do not always behave rationally, but often make seemingly random and suboptimal decisions.
A Computational View of Market Efficiency2011
We propose to study market efficiency from a computational viewpoint. Borrowing from theoretical computer science, we define a market to be efficient with respect to resources S (e.g., time, memory) if no strategy using resources S can make a profit. As a first step, we consider memory-m strategies whose action at time t depends only on the m previous observations at times t - m,...,t - 1. We introduce and study a simple model of market evolution, where strategies impact the market by their decision to buy or sell. We show that the effect of optimal strategies using memory m can lead to "market conditions" that were not present initially, such as (1) market bubbles and (2) the possibility for a strategy using memory m' > m to make a bigger profit than was initially possible. We suggest ours as a framework to rationalize the technological arms race of quantitative trading firms.
The Origin of Behavior2011
We propose a single evolutionary explanation for the origin of several behaviors that have been observed in organisms ranging from ants to human subjects, including risk-sensitive foraging, risk aversion, loss aversion, probability matching, randomization, and diversification. Given an initial population of individuals, each assigned a purely arbitrary behavior with respect to a binary choice problem, and assuming that offspring behave identically to their parents, only those behaviors linked to reproductive success will survive, and less reproductively successful behaviors will disappear at exponential rates. This framework generates a surprisingly rich set of behaviors, and the simplicity and generality of our model suggest that these behaviors are primitive and universal.
Complexity, Concentration and Contagion: A Comment2011
Although the precise origins of the term "complex adaptive system" are unclear, nevertheless, the hackneyed phrase is now firmly ensconced in the lexicon of biologists, physicists, mathematicians, and, most recently, economics. However, as with many important ideas that become cliches, the original meaning is often obscured and diluted by popular usage. But thanks to the fascinating article by Gai, Haldane, and Kapadia, we have a concrete and practical instantiation of a complex adaptive system in economics, one that has real relevance to current policy debates regarding financial reform. Since there is very little to criticize in their compelling article, I will seek to amplify their results and place them in a broader context in my comments.
The Financial Industry Needs its Own Crash Safety Board2010
MIT Sloan Prof. Andrew Lo authored this opinion piece supporting the creation of a “Capital Markets Safety Board’ (CMSB) patterned after the National Transportation Safety Board, dedicated to investigating, reporting, and archiving the ‘accidents’ of the financial industry.”
Lo: The Best Econ Book I’ve Read Recently2010
Andrew Lo, director of the MIT Laboratory for Financial Engineering, posted his commentary on a recent economics book in this online Q&A.
This is Your Brain on Prosperity: Andrew Lo on Fear, Greed, and Crisis Management2009
In this guest post, MIT Sloan Prof. Andrew Lo provides an insightful look at how "extended periods of prosperity act as an anesthetic in the human brain," lulling everyone involved into "a drug-induced stupor that causes us to take risks that we know we should avoid."