Barras, Scaillet, and Wermers propose the false discovery rate (FDR) to separate skill (alpha) from luck in fund performance. Using simulations with parameters informed by the data, we find that this methodology is conservative and underestimates the proportion of nonzero‐alpha funds. For example, 65% of funds with economically large alphas of are misclassified as zero alpha. This bias arises from the low signal‐to‐noise ratio in fund returns and the resulting low statistical power. Our results question FDR's applicability in performance evaluation and other domains with low power, and can materially change the conclusion that most funds have zero alpha.

The 30‐year U.S. swap spreads have been negative since September 2008. We offer a novel explanation for this persistent anomaly. Through an illustrative model, we show that underfunded pension plans optimally use swaps for duration hedging. Combined with dealer banks' balance sheet constraints, this demand can drive swap spreads to become negative. Empirically, we construct a measure of the aggregate funding status of defined benefit pension plans and show that this measure helps explain 30‐year swap spreads. We find a similar link between pension funds' underfunding and swap spreads for two other regions.

We study the effect of subjective mortality beliefs on life‐cycle behavior. With new survey evidence, we document that survival is underestimated (overestimated) by the young (old). We calibrate a canonical life‐cycle model to elicited beliefs. Relative to calibrations using actuarial probabilities, the young undersave by 26%, and retirees draw down their assets 27% slower, while the model's fit to consumption data improves by 88%. Cross‐sectional regressions support the model's predictions: Distorted mortality beliefs correlate with savings behavior while controlling for risk preferences, cognitive, and socioeconomic factors. Overweighting the likelihood of rare events contributes to mortality belief distortions.

We derive a formula for the expected return on a stock in terms of the risk‐neutral variance of the market and the stock's excess risk‐neutral variance relative to that of the average stock. These quantities can be computed from index and stock option prices; the formula has no free parameters. The theory performs well empirically both in and out of sample. Our results suggest that there is considerably more variation in expected returns, over time and across stocks, than has previously been acknowledged.

A risk‐averse entrepreneur with access to a profitable venture needs to raise funds from investors. She cannot indefinitely commit her human capital to the venture, which limits the firm's debt capacity, distorts investment and compensation, and constrains the entrepreneur's risk sharing. This puts dynamic liquidity and state‐contingent risk allocation at the center of corporate financial management. The firm balances mean‐variance investment efficiency and the preservation of financial slack. We show that in general the entrepreneur's net worth is overexposed to idiosyncratic risk and underexposed to systematic risk. These distortions are greater the closer the firm is to exhausting its debt capacity.

We incorporate trading fees into a dynamic, multiagent general‐equilibrium model in which traders optimally decide when to trade. For that purpose, we propose an innovative algorithm that synchronizes the traders. Securities prices are not so much affected by the payment of the fees itself, but rather by the trade‐off that the traders face between smoothing consumption and smoothing holdings. In calibrated examples, the interest rate and welfare decline with trading fees, while risk premia and volatilities increase. Liquidity risk and expected liquidity are priced, leading to deviations from the consumption‐CAPM. With trading fees, capital is slow‐moving, generating slow price reversal.

We model a financial market where some traders of a risky asset do not fully appreciate what prices convey about others' private information. Markets comprising solely such “cursed” traders generate more trade than those comprising solely rationals. Because rationals arbitrage away distortions caused by cursed traders, mixed markets can generate even more trade. Per‐trader volume in cursed markets increases with market size; volume may instead disappear when traders infer others' information from prices, even when they dismiss it as noisier than their own. Making private information public raises rational and “dismissive” volume, but reduces cursed volume given moderate noninformational trading motives.

We propose a theoretical measure of income hedging demand and show that it affects asset prices. We focus on the value factor and first demonstrate that our demand estimates are correlated with the actual demands of retail and mutual fund investors. We then show that the aggregate high‐minus‐low (HML) demand predicts HML returns. Exploiting the state‐level variation in income risk, we demonstrate that state‐level hedging demands predict state‐level HML returns. A long‐short portfolio that exploits this hedging‐induced predictability earns an annualized risk‐adjusted return of 6%.

Liquidity suppliers lean against the wind. We analyze whether high‐frequency traders (HFTs) lean against large institutional orders that execute through a series of child orders. The alternative is HFTs trading with the wind, that is, in the same direction. We find that HFTs initially lean against these orders but eventually change direction and take positions in the same direction for the most informed institutional orders. Our empirical findings are consistent with investors trading strategically on their information. When deciding trade intensity, they seem to trade off higher speculative profits against higher risk of being detected and preyed on by HFTs.

We develop a continuous‐time model of liquidity provision in which hedgers can trade multiple risky assets with arbitrageurs. Arbitrageurs have constant relative risk‐aversion (CRRA) utility, while hedgers' asset demand is independent of wealth. An increase in hedgers' risk aversion can make arbitrageurs endogenously more risk‐averse. Because arbitrageurs generate endogenous risk, an increase in their wealth or a reduction in their CRRA coefficient can raise risk premia despite Sharpe ratios declining. Arbitrageur wealth is a priced risk factor because assets held by arbitrageurs offer high expected returns but suffer the most when wealth drops. Aggregate illiquidity, which declines in wealth, captures that factor.