[Numerous measures have been proposed to gauge the performance of active management. Unfortunately, these measures can be gamed. Our article shows that gaming can have a substantial impact on popular measures even in the presence of high transactions costs. Our article shows there are conditions under which a manipulation-proof measure exists and fully characterizes it. This measure looks like the average of a power utility function, calculated over the return history. The case for using our alternative ranking metric is particularly compelling for hedge funds whose use of derivatives is unconstrained and whose managers' compensation itself induces a nonlinear payoff.]

We test a Wall Street investment strategy, "pairs trading," with daily data over 1962-2002. Stocks are matched into pairs with minimum distance between normalized historical prices. A simple trading rule yields average annualized excess returns of up to 11% for self-financing portfolios of pairs. The profits typically exceed conservative transaction-cost estimates. Bootstrap results suggest that the "pairs" effect differs from previously documented reversal profits. Robustness of the excess returns indicates that pairs trading profits from temporary mispricing of close substitutes. We link the profitability to the presence of a common factor in the returns, different from conventional risk measures.

We use a two-year panel of individual accounts in an S&P 500 index mutual fund to examine the trading and investment behavior of more than 91 thousand investors who have chosen a low-cost, passively managed vehicle for savings.This allows us to characterize investors' heterogeneity in terms of their investment patterns.In particular, we identify positive feedback traders as well as contrarians whose activities are conditional upon preceding day stock market moves.We test the consistency and profitability of these conditional strategies over time.We find that more frequent traders are typically contrarians, while infrequent traders are more typically momentum investors.The dynamics of these investor classes help us to partially examine the question of the marginal investor over the period of our study.We find that the behavior of momentum investors is typically more correlated to changes in the S&P 500 and we trace its dynamics over time.We build up "behavioral factors" based on contrarian and momentum flows and show that they perform well against a benchmark of loadings on latent factors extracted from returns.We also use the behavior of momentum and contrarian investors to build a measure of "market polarization".This captures the dispersion of beliefs among the investors and helps to account for asset pricing better than standard measures of dispersion of beliefs.

We analyze a bias in transaction-based price indexes due to the presence of seller reservation prices. We develop a model in which the ratio of sellers' reservation prices to the market value affects trading volume and biases of observed transaction prices: when trading volume decreases (increases), index returns are estimated with an upward (downward) bias. We propose a new econometric procedure to mitigate the bias, and use simulations to demonstrate the effectiveness of the procedure. We construct a reserve-conditional unbiased index for the Los Angeles housing market, which substantially differs from a traditional repeat sale index.

This study shows that weather-based indicators of mood impact perceptions of mispricing and trading decisions of institutional investors. Using survey and disaggregated trade data, we show that relatively cloudier days increase perceived overpricing in individual stocks and the Dow Jones Industrial Index and increase selling propensities of institutions. We introduce stock-level measures of investor mood; investor optimism positively impacts stock returns among stocks with higher arbitrage costs, and stocks experiencing similar investor mood exhibit return comovement. These findings complement existing studies on how weather impacts stock index returns and identify another channel through which it can manifest.

This paper separates the components of capital appreciation returns in an asset market into fixed and stochastic portions. It proposes a control for the problem of fixed components in the capital appreciation return used in transactions-based return estimates. We find a consistent bias in the index resulting from repeat sales regressions which may be eliminated through simple methods. The sign and magnitude of the bias, as well as its systematic variation across property, suggest that it is caused by incremental home improvements, as well as by price risk. We propose a maximum likelihood method for estimating the first and second moments of the fixed and temporal components of real estate returns that relies upon relatively small samples. Copyright 1995 by MIT Press.

Mutual funds are typically grouped by their investment objectives or the ‘style’ of their managers. We propose a new empirical to the determination of manager ‘style’. This approach is simple to apply, yet it captures nonlinear patterns of returns that result from virtually all active portfolio management styles. Our classifications are superior to common industry classifications in predicting cross-sectional future performance, as well as past performance, and they also outperform classifications based on risk measures and analogue portfolios. Interestingly, ‘growth’ funds typically break down into several categories that differ in composition and strategy.

Alfred Cowles' test of the Dow Theory apparently provides strong evidence against the ability of Wall Street's most famous chartist to forecast the stock market. Cowles (1934) analyzes editorials published by the chief exponent of the Dow Theory, William Peter Hamilton. We review Cowles' evidence and find that it supports the contrary conclusion. Hamilton's timing strategies actually yield high Sharpe ratios and positive alphas for the period 1902 to 1929. Neural net modeling to replicate Hamilton's market calls provides interesting insight into the Dow Theory and allows us to examine the properties of the theory itself out of sample.

[Recent evidence suggests that past mutual fund performance predicts future performance. We analyze the relationship between volatility and returns in a sample that is truncated by survivorship and show that this relationship gives rise to the appearance of predictability. We present some numerical examples to show that this effect can be strong enough to account for the strength of the evidence favoring return predictability.]