We propose a new measure, active fundamental performance (AFP), to identify skilled mutual fund managers. AFP evaluates fund investment skills conditioned on the release of firms’ fundamental information. For each fund, we examine the covariance between deviations of its portfolio weights from a benchmark portfolio and the underlying stock performance on days when firms publicize fundamental information. Because asset prices on these information days better reflect firm fundamentals, AFP can more effectively identify investment skills. From 1984 to 2014, funds in the top decile of high AFP subsequently outperformed those in the bottom decile by 2% to 3% per year. Received August 25, 2016; editorial decision December 17, 2017 by Editor Andrew Karolyi.

Recent winners have temporarily higher loadings than recent losers on the growth rate of industrial production. The loading spread derives mostly from the positive loadings of winners. The growth rate of industrial production is a priced risk factor in standard asset pricing tests. In many specifications, this macroeconomic risk factor explains more than half of momentum profits. We conclude that risk plays an important role in driving momentum profits. The Author 2008. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please email: [email protected]., Oxford University Press.

We examine the informativeness of fund risk disclosure by combining fund returns and textual data. We develop a novel measure, INF, to capture the explanatory power of disclosed risks for fund returns. Average INF is 55% after controlling for market risk and remains 26–29% after excluding risks related to fund name or strategy. We explain variations in INF through disclosure costs and benefits: (1) Funds with less informative disclosures face SEC comment letters and reduced flow, (2) informative disclosures attract institutional flows, and (3) performance concerns may disincentivize disclosure. Overall, funds face trade-offs between transparency and maintaining their competitive advantage.

Our paper analyzes the geographical preferences of hedge fund investors and the implication of these preferences for hedge fund performance. We find that funds of hedge funds overweigh their investments in hedge funds located in the same geographical areas and that funds with a stronger local bias exhibit superior performance. Local bias also gives rise to excess flow comovement and extreme return clustering within geographic areas. Overall, our results suggest that while funds of funds benefit from local advantages, their local bias also creates market segmentation that can destabilize the underlying hedge funds.

Most anomalies fail to hold up to currently acceptable standards for empirical finance. With microcaps mitigated via NYSE breakpoints and value-weighted returns, 65% of the 452 anomalies in our extensive data library, including 96% of the trading frictions category, cannot clear the single test hurdle of the absolute t-value of 1.96. Imposing the higher multiple test hurdle of 2.78 at the 5% significance level raises the failure rate to 82%. Even for replicated anomalies, their economic magnitudes are much smaller than originally reported. In all, capital markets are more efficient than previously recognized. Received June 12, 2017; editorial decision October 29, 2018 by Editor Stijn Van Nieuwerburgh.

This paper is a new incarnation of the defunct work previously circulated under the titles "Neoclassical Factors," "An equilibrium three-factor model," "Production-based factors," "A better three-factor model that explains more anomalies," and "An alternative three-factor model." We are extremely grateful to Robert Novy-Marx

A new methodology for equity valuation arises from the perspective of managers' supply of capital assets. Under q-theory, managers optimally adjust the supply of assets to changes in their market value. The first-order condition of investment then provides a valuation equation that infers asset prices from managers' costs of supplying the assets. This equation fits well the Tobin's q levels across many testing assets, including portfolios formed on q. With current investment-to-capital as the only input, the supply approach does not require cash flow forecasts or discount rate estimates, both of which are notoriously difficult to obtain in practice.

An investment factor, long in low-investment stocks and short in high-investment stocks, helps explain the new issues puzzle. Adding the investment factor into standard factor regressions reduces the SEO underperformance by about 75%, the IPO underperformance by 80%, the underperformance following convertible debt offerings by 50%, and Daniel and Titman's (2006) composite issuance effect by 40%. The reason is that issuers invest more than nonissuers, and the investment factor earns a significantly positive average return of 0.57% per month.

A detailed treatment of aggregation and capital heterogeneity substantially improves the performance of the investment CAPM. Firm-level predicted returns are constructed from firm-level accounting variables and aggregated to the portfolio level to match with portfolio-level stock returns. Working capital forms a separate productive input besides physical capital. The model simultaneously fits the value, momentum, investment, and profitability premiums and partially explains positive stock-fundamental return correlations, the procyclical and short-term dynamics of the momentum and profitability premiums, and the countercyclical and long-term dynamics of the value and investment premiums. However, the model falls short in explaining momentum crashes. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online..

We use a production-based asset pricing model to investigate whether financing constraints are quantitatively important for the cross-section of returns. Specifically, we use GMM to explore the stochastic Euler equation imposed on returns by optimal investment. Our methods can identify the impact of financial frictions on the stochastic discount factor with cyclical variations in cost of external funds. We find that financing frictions provide a common factor that improves the pricing of cross-sectional returns. Moreover, the shadow cost of external funds exhibits strong procyclical variation, so that financial frictions are more important in relatively good economic conditions.