A number of delta-hedged equity option strategies exhibit very large average returns. We show that much of the profitability of these strategies can be explained by an IPCA factor model. The economic magnitude of the return-adjustment produced by IPCA is impressive: even before transaction costs, the average IPCA alpha of 46 long-short trading strategies constructed on previously discovered signals, is close to zero and contrasts with average realized returns of over 80 basis points per month. Our IPCA model can be used as a benchmark for assessing the performance of other option portfolios.

When firms can issue debt at discrete dates only, debt maturity becomes an effective tool to constrain investment and debt policies. In the absence of other frictions, single-period debt restores first-best investment. With market freezes, long-maturity debt amplifies underinvestment and the leverage ratchet effect, while short maturity mitigates these distortions. Calibrating the model to U.S. nonfinancial firms shows that choosing the optimal debt maturity can reduce the cost of commitment problems and market frictions by up to 4% of firm value. A decomposition of the equilibrium credit spread reveals that the component associated with time-inconsistent debt and investment policies is largest when leverage and default risk are low, and is substantially reduced by shorter debt maturities.

In almost every area of empirical finance, researchers confront multiple tests. One high-profile example is the identification of outperforming investment managers, many of whom beat their benchmarks purely by luck. Multiple testing methods are designed to control for luck. Factor selection is another glaring case in which multiple tests are performed, but numerous other applications do not receive as much attention. One important example is a simple regression model testing five variables. In this case, because five variables are tried, a t-statistic of 2.0 is not enough to establish significance. Our paper provides a guide to various multiple testing methods and details a number of applications. We provide simulation evidence on the relative performance of different methods across a variety of testing environments. The goal of our paper is to provide a menu that researchers can choose from to improve inference in financial economics.

We use information from over 2 million trading strategies randomly generated using real data and from strategies that survive the publication process to infer the statistical properties of the set of strategies that could have been studied by researchers. Using this set, we compute t-statistic thresholds that control for multiple hypothesis testing, when searching for anomalies, at 3.8 and 3.4 for time-series and cross-sectional regressions, respectively. We estimate the expected proportion of false rejections that researchers would produce if they failed to account for multiple hypothesis testing to be about 45%.