The fact that derivative securities are equivalent to specific dynamic trading strategies in complete markets suggests the possibility of constructing buy-and-hold portfolios of options that mimic certain dynamic investment policies, e.g., asset-allocation rules. We explore this possibility by solving the following problem: given an optimal dynamic investment policy, find a set of options at the start of the investment horizon which will come closest to the optimal dynamic investment policy. We solve this problem for several combinations of preferences, return dynamics, and optimality criteria, and show that under certain conditions, a portfolio consisting of just a few options is an excellent substitute for considerably more complex dynamic investment policies.

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.

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.

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.

We establish a link between illiquidity and positive autocorrelation in asset returns among a sample of hedge funds, mutual funds, and various equity portfolios. For hedge funds, this link can be confirmed by comparing the return autocorrelations of funds with shorter vs. longer redemption-notice periods. We also document significant positive return-autocorrelation in portfolios of securities that are generally considered less liquid, e.g., small-cap stocks, corporate bonds, mortgage-backed securities, and emerging-market investments.

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.

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.

We document the empirical properties of a sample of 1,765 funds in the TASS Hedge Fund database from 1994 to 2004 that are no longer active. The TASS sample shows that attrition rates differ significantly across investment styles, from a low of 5.2% per year on average for convertible arbitrage funds to a high of 14.4% per year on average for managed futures funds. We relate a number of factors to these attrition rates, including past performance, volatility, and investment style, and also document differences in illiquidity risk between active and liquidated funds. We conclude with a proposal for the U.S. Securities and Exchange Commission to play a new role in promoting greater transparency and stability in the hedge-fund industry.

Identifying winning new product concepts can be a challenging process that requires insight into private consumer preferences. To measure consumer preferences for new product concepts, the authors apply a 'securities of trading of concepts,' or STOC, approach, in which new product concepts are traded as financial securities. The authors apply this method because market prices are known to efficiently collect and aggregate private information regarding the economic value of goods, sevices, and firms, particularly when trading financial securities. This research compares the STOC approach against stated-choice, conjoint, constant-sum, and longitudinal revealed-preference data. The authors also place STOC in the context of previous research on prediction markets and experimental economics. The authors conduct a series of experiments in multiple product categories to test whether STOC (1) is more cost efficient than other methods, (2) passes validity tests, (3) measures expectations of others, and (4) reveals individual preferences, not just those of the crowd. The results also show that traders exhibit bias on the basis of self-preferences when trading. Ultimately, STOC offers two key advantages over traditional market research methods: cost efficiency and scalability. For new product development teams deciding how to invest resources, this scalability may be especially important in the Web 2.0 world, in which customers are constantly interacting with firms and one another in suggesting numerous product design possibilities that need to be screened.

We propose the National Transportation Safety Board (NTSB) as a model organization for addressing systemic risk in industries and contexts other than transportation. When adopted by regulatory agencies and the transportation industry, the safety recommendations of the NTSB have been remarkably effective in reducing the number of fatalities in various modes of transportation since the NTSB’s inception in 1967 as an independent agency. The NTSB has no regulatory authority and is solely focused on conducting forensic investigations of transportation accidents and proposing safety recommendations. With only 400 full-time employees, the NTSB has a much larger network of experts drawn from other government agencies and the private sector who are on call to assist in accident investigations on an as-needed basis. By allowing the participation in its investigations of all interested parties who can provide technical assistance to the investigations, the NTSB produces definitive analyses of even the most complex accidents and provides actionable measures for reducing the chances of future accidents. It is possible to create more efficient and effective systemic-risk management processes in many other industries, including financial services, by studying the organizational structure and functions of the NTSB.