Knowledge that Transforms

We investigate the portfolio choices of mean-variance-optimizing investors who use sample evidence to update prior beliefs centered on either risk-based or characteristic-based pricing models. With dogmatic beliefs in such models and an unconstrained ratio of position size to capital, optimal portfolios can differ across models to economically significant degrees. The differences are substantially reduced by modest uncertainty about the models’ pricing abilities. When the ratio of position size to capital is subject to realistic constraints, the differences in portfolios across models become even less important and are nonexistent in some cases.

In this paper, I develop a theory of bid–ask quotes provided by foreign exchange dealers in the inter-bank market based on their beliefs and their inventory positions. I then build an agent-based model of the inter-dealer market where dealers learn in a Bayesian manner from quotes from other dealers. Using simulations, I find that the resulting intra-day spreads and between-quote returns largely conform to the empirically observed intra-day U-shaped pattern – a feature that has not been satisfactorily explained in the literature. I also study the factors that determine this U-shape.

Stock prices move together more in poor economies than in rich economies. This finding is not due to market size and is only partially explained by higher fundamentals correlation in low-income economies. However, measures of property rights do explain this difference. The systematic component of returns variation is large in emerging markets, and appears unrelated to fundamentals co-movement, consistent with noise trader risk. Among developed economy stock markets, higher firm-specific returns variation is associated with stronger public investor property rights. We propose that strong property rights promote informed arbitrage, which capitalizes detailed firm-specific information.

We examine the practice of resetting the terms of previously-issued executive stock options. We identify properties of reset options, develop a model for valuing resettable options, and characterize the firms that have reset options. We find the vast majority of options are reset at-the-money, resulting, on average, in the strike price dropping 40%. Our valuation model suggests that resetting has only a small impact on the ex-ante value of an option award, but the ex-post gain can be substantial. Finally, we find resetting has a strong negative relation with firm performance even after correcting for industry performance.

In 1982, Dimensional Fund Advisors launched a mutual fund intended to capture the returns of small-cap stocks. The ‘9–10 Fund’ is based on the CRSP 9–10 Index, an index of small-cap stocks constituting the ninth and tenth deciles of NYSE market capitalization, although the 9–10 Fund incorporates investment rules and a trading strategy that are aimed at minimizing the potentially excessive trade costs associated with such illiquid stocks. As a result, the 9–10 Fund provided a 2.2% annual premium over the 9–10 Index for the 1982–1995 period. We show that both the investment rules and the trade strategy components of the Fund’s design contribute significantly to this return difference.

This paper tests models of mutual fund market timing that allow the manager's payoff function to depend on returns in excess of a benchmark, and distinguish timing based on publicly available information from timing based on finer information. We simultaneously estimate parameters which describe the public information environment, the manager's risk aversion, and the precision of the fund's market-timing signal. Using a sample of more than 400 U.S. mutual funds for 1976–94, our findings suggest that mutual funds behave as highly risk averse, benchmark investors. Conditioning on public information improves the model specification. After controlling for the public information, we find no evidence that funds have significant market-timing ability.

We simulate standard tests of performance persistence using alternative return-generating processes, survival criteria, and test methodologies. When survival depends on performance over several periods, survivorship bias induces spurious reversals, despite the presence of cross-sectional heteroskedasticity in performance. Look-ahead biased methodologies and missing final returns typical of U.S. mutual fund datasets can also materially affect persistence measures. Our results reinforce previous findings that U.S. mutual fund performance is truly persistent. When fund performance is truly persistent, fund attrition affects persistence measures, even when the sample includes all nonsurvivor returns. We also examine the specification and power of the various persistence tests.

When a rate of return is regressed on a lagged stochastic regressor, such as a dividend yield, the regression disturbance is correlated with the regressor's innovation. The OLS estimator's finite-sample properties, derived here, can depart substantially from the standard regression setting. Bayesian posterior distributions for the regression parameters are obtained under specifications that differ with respect to (i) prior beliefs about the autocorrelation of the regressor and (ii) whether the initial observation of the regressor is specified as fixed or stochastic. The posteriors differ across such specifications, and asset allocations in the presence of estimation risk exhibit sensitivity to those differences.

We use a genetic algorithm to learn technical trading rules for the S&P 500 index using daily prices from 1928 to 1995. After transaction costs, the rules do not earn consistent excess returns over a simple buy-and-hold strategy in the out-of-sample test periods. The rules are able to identify periods to be in the index when daily returns are positive and volatility is low and out when the reverse is true. These latter results can largely be explained by low-order serial correlation in stock index returns.

This paper finds that discounts and premiums of closed-end funds reflect the market's assessment of anticipated managerial performance. Using single and multiple benchmarks, we present evidence that there is a significant and positive relation between stock fund premiums and future net asset value performance over the following year. The relation is not caused by the anticipation of future expenses. We also find that bond closed-end funds show no such relation between premium and asset value performance.