We develop a model to explore the asset pricing implications of firms being buyers of last resort for their own stocks. Those with more ability to repurchase shares when prices drop far below fundamental value (i.e., less financially constrained firms) should have lower short-horizon return variances (controlling for fundamental variance) than other firms. Using standard proxies for financing constraints such as past repurchases and firm age, we find strong support for this predicted relation. We also find that this relation is stronger in the U.S. after 1982 when regulatory reforms lowered the legal cost of conducting repurchases as well as in countries where share repurchases are legally easier to execute.

We model the welfare consequences of mandates that restrict investors to hold firms with net-zero carbon emissions. To qualify for these mandates, value-maximizing firms have to accumulate decarbonization capital. Qualification lowers a firm’s required return by its decarbonization investments divided by Tobin’s q, that is, the greenium or the dividend yield shareholders forgo to address the global-warming externality. The welfare-maximizing mandate approximates the first-best solution, yielding welfare gains compared to laissez-faire by mitigating the weather disaster risks resulting from carbon emissions. Our model generates optimal transition paths for decarbonization that we use to evaluate proposed net-zero targets.

We study the asset pricing implications of learning in an environment in which the true model of the world is a multivariate one, but agents update only over the class of simple univariate models. Thus, if a particular simple model does a poor job of forecasting over a period of time, it is discarded in favor of an alternative simple model. The theory yields a number of distinctive predictions for stock returns, generating forecastable variation in the magnitude of the value‐glamour return differential, in volatility, and in the skewness of returns. We validate several of these predictions empirically.

We investigate the effect of scale on performance in the active money management industry. We first document that fund returns, both before and after fees and expenses, decline with lagged fund size, even after accounting for various performance benchmarks. We then explore a number of potential explanations for this relationship. This association is most pronounced among funds that have to invest in small and illiquid stocks, suggesting that these adverse scale effects are related to liquidity. Controlling for its size, a fund's return does not deteriorate with the size of the family that it belongs to, indicating that scale need not be bad for performance depending on how the fund is organized. Finally, using data on whether funds are solo-managed or team-managed and the composition of fund investments, we explore the idea that scale erodes fund performance because of the interaction of liquidity and organizational diseconomies.

We investigate the effects of managerial outsourcing on the performance and incentives of mutual funds. Fund families outsource the management of a large fraction of their funds to advisory firms. These funds underperform those run internally by about 52 basis points per year. After instrumenting for a fund's outsourcing status, the estimated underperformance is three times larger. We hypothesize that contractual externalities due to firm boundaries make it difficult to extract performance from an outsourced relationship. Consistent with this view, outsourced funds face higher powered incentives; they are more likely to be closed after poor performance and excessive risk‐taking.

There is causal evidence that mortgage credit expansions increase house prices. Does an expansion of margin lending increase stock prices? Because unconstrained arbitrageurs are more important for pricing stocks than homes, the impact is not obvious. Tests are limited because sizable shocks to margin lending are rare. We examine a major Chinese margin-lending expansion between 2010 and 2015. Institutional holding, regression discontinuity, and event study evidence—exploiting the rollout of margin lending across stocks—shows that arbitrageurs anticipated and bought in advance of a significant causal effect of credit. We develop a model to rationalize our findings. Our estimates suggest that margin debt contributes to stock market fluctuations.

We show that Keeping-Up-with-the-Joneses preferences can explain several puzzling retail investor behaviors, including the excessive trading of small local stocks. Status concerns lead households, especially those living in affluent areas, to demand these stocks to track their neighbors' wealth. This demand varies procyclically with the stock market's value and generates household trading. Using Chinese data on local stock turnover, stock message boards, and brokerage account trading, we test and confirm this hypothesis by exploiting the uneven rise of affluence across Chinese cities between 1998 and 2012.

Event studies of market efficiency measure earnings surprises using the consensus error ( CE ), given as actual earnings minus the average professional forecast. If a subset of forecasts can be biased, the ideal but difficult to estimate parameter‐dependent alternative to CE is a nonlinear filter of individual errors that adjusts for bias. We show that CE is a poor parameter‐free approximation of this ideal measure. The fraction of misses on the same side ( FOM ), which discards the magnitude of misses, offers a far better approximation. FOM performs particularly well against CE in predicting the returns of U.S. stocks, where bias is potentially large.