Return Persistence and Fund Flows in the Worst Performing Mutual Funds

We document that the observed persistence amongst the worst performing actively managed mutual funds is attributable to funds that have performed poorly both in the current and prior year. We demonstrate that this persistence results from an unwillingness of investors in these funds to respond to bad performance by withdrawing their capital. In contrast, funds that only performed poorly in the current year have a significantly larger (out)flow of funds/return sensitivity and consequently show no evidence of persistence in their returns.

Mutual Fund Flows and Performance in Rational Markets

We develop a simple rational model of active portfolio management that provides a natural benchmark against which to evaluate observed relationship between returns and fund flows. We show that many effects widely regarded as anomalous are consistent with this simple explanation. In the model, investments with active managers do not outperform passive benchmarks because of the competitive market for capital provision, combined with decreasing returns to scale in active portfolio management. Consequently, past performance cannot be used to predict future returns, or to infer the average skill level of active managers. The lack of persistence in active manager returns does not imply that differential ability across managers is nonexistent or unrewarded, that gathering information about performance is socially wasteful, or that chasing performance is pointless. A strong relationship between past performance and the ow of funds exists in our model, indeed this is the market mechanism that ensures that no predictability in performance exists. Calibrating the model to the fund flows and survivorship rates, we nd these features of the data are consistent with the vast majority (80%) of active managers having at least enough skill to make back their fees.

Human Capital, Bankruptcy and Capital Structure

We derive a firm's optimal capital structure and managerial compensation contract when employees are averse to bearing their own human capital risk, while equity holders can diversify this risk away. In the presence of corporate taxes, our model delivers optimal debt levels consistent with those observed in practice. It also makes a number of predictions for the cross-sectional distribution of firm leverage. Consistent with existing empirical evidence, it implies persistent idiosyncratic differences in leverage across firms. An important new empirical prediction of the model is that, ceteris paribus, firms with more leverage should pay higher wages.

Journal of Financial Economics

We propose a new method of testing asset pricing models that relies on quantities rather than just prices or returns. We use the capital flows into and out of mutual funds to infer which risk model investors use. We derive a simple test statistic that allows us to infer, from a set of candidate models, the risk model that is closest to the model that investors use in making their capital allocation decisions. Using our method, we assess the performance of the most commonly used asset pricing models in the literature

Measuring Skill in the Mutual Fund Industry

Using the value that a mutual fund extracts from capital markets as the measure of skill, we find that the average mutual fund has used this skill to generate about $3.2 million per year. Large cross-sectional differences in skill persist for as long as ten years. Investors recognize this skill and reward it by investing more capital with better funds. Better funds earn higher aggregate fees, and a strong positive correlation exists between current compensation and future performance. The cross-sectional distribution of managerial skill is predominantly reflected in the cross-sectional distribution of fund size, not gross alpha

Statistical Discrimination in a Competitive Labor Market

This paper studies the effect of employee job selection in a model of statistical discrimination in a competitive labor market. In an economy in which there are quality differences between groups, a surprisingly strong condition is required to guarantee discrimination against the worse qualified group --- MLRP must hold. In addition, because of the self-selection bias induced by competition, the resulting discrimination is small when compared to the magnitude of the underlying quality differences between groups. In cases in which the discrimination results because employers' ability to measure qualifications differs from one group to another, the conditions under which one group is discriminated against are much weaker. In general, the group employers know least about is always favored. The economic impact of discrimination that is derived from quality differences between groups is shown to be quite different to the economic impact of discrimination that derives from differences in employer familiarity between groups. In the latter case, for a set of equally qualified employees, it is possible for members of the group that is discriminated against to have higher wages. Finally, we show how the results can be used to explain a number of empirical puzzles that are documented in the literature.

Matching Capital and Labor

We establish an important role for the firm by studying capital reallocation decisions of mutual fund firms. The firm\u27s decision to reallocate capital among its mutual fund managers adds at least $474,000 a month, which amounts to over 30% of the total value added of the industry. We provide evidence that this additional value added results from the firm\u27s private information about the skill of its managers. The firm captures this value because investors reward the firm following a capital reallocation decision by allocating additional capital to the firm\u27s funds

Valuation and Return Dynamics of New Ventures

We develop and analyze a model of a multi-stage investment project that captures many features of R&D ventures and start-up companies. An important feature these problems share is that the firm learns about the potential profitability of the project throughout its life, but that research and development effort itself is only resolved through additional investment by the firm. In addition, the risks associated with the ultimate cash flows the firm realizes on completion of the project have a systematic component, while the purely technical risks are idiosyncratic. Our model captures these different sources of risk, and allows us to study their interaction in determining the risk premia earned by the venture during development. Our results show that the systematic risk, and the required risk premium, of the venture are highest early in its life, and decrease as it approaches completion, despite the idiosyncratic nature of the technical risk.

Valuation and Return Dynamics of New Ventures.

We develop and analyze a model of a multi-stage investment project that captures many features of R&D; ventures and start-up companies. An important feature these problems share is that the firm learns about the potential profitability of the project throughout its life, but that "technical uncertainty" about the research and development effort itself is only resolved through additional investment by the firm. In addition, the risks associated with the ultimate cash flows the firm realizes on completion of the project have a systematic component, while the purely technical risks are idiosyncratic. Our model captures these different sources of risk, and allows us to study their interaction in determining the risk premia earned by the venture during development. Our results show that the systematic risk, and the required risk premium, of the venture are highest early in its life, and decrease as it approaches completion, despite the idiosyncratic nature of the technical risk.