with Jasmina Hasanhodzic, Journal of Investment Management 5 (2007), 5–45.
In contrast to traditional investments such as stocks and bonds, hedge-fund returns have more complex risk exposures that yield additional and complementary sources of risk premia. This raises the possibility of creating passive replicating portfolios or "clones" using liquid exchange-traded instruments that provide similar risk exposures at lower cost and with greater transparency. Using monthly returns data for 1,610 hedge funds in the TASS database from 1986 to 2005, we estimate linear factor models for individual hedge funds using six common factors, and measure the proportion of the funds' expected returns and volatility that are attributable to such factors. For certain hedge-fund style categories, we find that a significant fraction of both can be captured by common factors corresponding to liquid exchange-traded instruments. While the performance of linear clones is often inferior to their hedge-fund counterparts, they perform well enough to warrant serious consideration as passive, transparent, scalable, and lower-cost alternatives to hedge funds.
Journal of Investment Management 5 (2007), 29-78.
During the week of August 6, 2007, a number of quantitative long/short equity hedge funds experienced unprecedented losses. Based on TASS hedge-fund data and simulations of a specific long/short equity strategy, we hypothesize that the losses were initiated by the rapid "unwind" of one or more sizable quantitative equity market-neutral portfolios. Given the speed and price impact with which this occurred, it was likely the result of a forced liquidation by a multi-strategy fund or proprietary-trading desk, possibly due to a margin call or a risk reduction. These initial losses then put pressure on a broader set of long/short and long-only equity portfolios, causing further losses by triggering stop/loss and de-leveraging policies. A significant rebound of these strategies occurred on August 10th, which is also consistent with the unwind hypothesis. This dislocation was apparently caused by forces outside the long/short equity sector—in a completely unrelated set of markets and instruments—suggesting that systemic risk in the hedge-fund industry may have increased in recent years.
with Jasmina Hasanhodzic, Alpha Magazine
Hedge funds are considered by many investors to be an attractive investment, thanks in large part to their diversification benefits and distinctive risk profiles. The major drawbacks are their high fees and lack of transparency. Research by Jasmina Hasanhodzic and Andrew W. Lo of the Massachusetts Institute of Technology raises the possibility of creating passive portfolios that provide similar risk exposures to those of hedge funds at lower costs and with greater transparency. Hasanhodzic and Lo find that for certain hedge fund strategies, these hedge fund “clones” perform well enough to warrant serious consideration.
Harvard Business Review
In financial markets, as in many human endeavors, there’s a battle between reason and madness. On one side are the disciples of the efficient-markets hypothesis: the notion that markets fully, accurately, and instantaneously incorporate all relevant information into prices. These adherents assume that market participants are rational, always acting in their own interest and making mathematically optimal decisions. On the other side are the champions of behavioral economics: a younger discipline that points to bubbles, crashes, panics, manias, and other distinctly unreasonable phenomena as evidence of irrationality.
It’s hard to deny that investors act irrationally from time to time, yet behavioralists have so far failed to offer an alternative to supplant the efficient-markets hypothesis, which does brilliantly explain many economic occurrences and has had an enormous impact on modern financial theory and practice. Both approaches seem to have compelling explanatory power in their own right, yet they have opposing premises: rationality versus human psychology. How can the efficient-markets hypothesis and behavioral economics ever be reconciled? Perhaps by looking to Charles Darwin instead of Adam Smith.
with Nicholas Chan, Mila Getmansky, and Shane M. Haas, Federal Reserve Bank of Atlanta Economic Review 2006:Q4, 49–80.
In this article, we attempt to quantify the potential impact of hedge funds on systemic risk by developing a number of new risk measures for hedge funds and applying them to individual and aggregate hedge-fund returns data. These measures include: illiquidity risk exposure, nonlinear factor models for hedge-fund and banking-sector indexes, logistic regression analysis of hedge-fund liquidation probabilities, and aggregate measures of volatility and distress based on regime-switching models. Our preliminary findings suggest that the hedge-fund industry may be heading into a challenging period of lower expected returns, and that systemic risk is currently on the rise.
This is a redacted version of our paper "Systemic Risk and Hedge Funds".
with Jiang Wang, Journal of Finance 61 (2006), 2805–2840.
We derive an intertemporal capital asset pricing model with multiple assets and heterogeneous investors, and explore its implications for the behavior of trading volume and asset returns. Assets contain two types of risks: market risk and the risk of changing market conditions. We show that investors trade only in two portfolios: the market portfolio, and a hedging portfolio, which allows them to hedge the dynamic risk. This implies that trading volume of individual assets exhibit a two-factor structure, and their factor loadings depend on their weights in the hedging portfolio. This allows us to empirically identify the hedging portfolio using volume data. We then test the two properties of the hedging portfolio: its return provides the best predictor of future market returns and its return together with the return of the market portfolio are the two risk factors determining the cross-section of asset returns.
Journal of Investment Consulting 7 (2005), 21–44.
The battle between proponents of the Efficient Markets Hypothesis and champions of behavioral finance has never been more pitched, and there is little consensus as to which side is winning or what the implications are for investment management and consulting. In this article, I review the case for and against the Efficient Markets Hypothesis, and describe a new framework—the Adaptive Markets Hypothesis—in which the traditional models of modern financial economics can co-exist alongside behavioral models in an intellectually consistent manner. Based on evolutionary principles, the Adaptive Markets Hypothesis implies that the degree of market efficiency is related to environmental factors characterizing market ecology such as the number of competitors in the market, the magnitude of profit opportunities available, and the adaptability of the market participants. Many of the examples that behavioralists cite as violations of rationality that are inconsistent with market efficiency—loss aversion, overconfidence, overreaction, mental accounting, and other behavioral biases—are, in fact, consistent with an evolutionary model of individuals adapting to a changing environment via simple heuristics. Despite the qualitative nature of this new paradigm, I show that the Adaptive Markets Hypothesis yields a number of surprisingly concrete applications for both investment managers and consultants.
with Dmitry V. Repin and Brett N. Steenbarger, American Economic Review 95 (2005), 352–359.
We investigate several possible links between psychological factors and trading performance in a sample of 80 anonymous day-traders. Using daily emotional-state surveys over a five-week period as well as personality inventory surveys, we construct measures of personality traits and emotional states for each subject and correlate these measures with daily normalized profits-and-losses records. We find that subjects whose emotional reaction to monetary gains and losses was more intense on both the positive and negative side exhibited significantly worse trading performance. Psychological traits derived from a standardized personality inventory survey do not reveal any specific "trader personality profile", raising the possibility that trading skills may not necessarily be innate, and that different personality types may be able to perform trading functions equally well after proper instruction and practice.
Journal of Portfolio Management 30 (2004), 15–29.
One of the most influential ideas in the past 30 years of the Journal of Portfolio Management is the Efficient Markets Hypothesis, the idea that market prices incorporate all information rationally and instantaneously. However, the emerging discipline of behavioral economics and finance has challenged this hypothesis, arguing that markets are not rational, but are driven by fear and greed instead. Recent research in the cognitive neurosciences suggests that these two perspectives are opposite sides of the same coin. In this article I propose a new framework that reconciles market efficiency with behavioral alternatives by applying the principles of evolution—competition, adaptation, and natural selection—to financial interactions. By extending Herbert Simon's notion of "satisficing'' with evolutionary dynamics, I argue that much of what behavioralists cite as counterexamples to economic rationality—loss aversion, overconfidence, overreaction, mental accounting, and other behavioral biases—are, in fact, consistent with an evolutionary model of individuals adapting to a changing environment via simple heuristics. Despite the qualitative nature of this new paradigm, the Adaptive Markets Hypothesis offers a number of surprisingly concrete implications for the practice of portfolio management.
with Harry Mamaysky and Jiang Wang, Journal of Political Economy 112 (2004), 1054–1090.
We propose a dynamic equilibrium model of asset prices and trading volume with heterogeneous agents facing fixed transactions costs. We show that even small fixed costs can give rise to large "no-trade" regions for each agent's optimal trading policy and a significant illiquidity discount in asset prices. We perform a calibration exercise to illustrate the empirical relevance of our model for aggregate data. Our model also has implications for the dynamics of order flow, bid/ask spreads, market depth, the allocation of trading costs between buyers and sellers, and other aspects of market microstructure, including a square-root power law between trading volume and fixed costs which we confirm using historical US stock market data from 1993 to 1997.