Despite their strong positive average returns across numerous asset classes, momentum strategies can experience infrequent and persistent strings of negative returns. These momentum crashes are partly forecastable. They occur in panic states, following market declines and when market volatility is high, and are contemporaneous with market rebounds. The low ex ante expected returns in panic states are consistent with a conditionally high premium attached to the option like payoffs of past losers. An implementable dynamic momentum strategy based on forecasts of momentum’s mean and variance approximately doubles the alpha and Sharpe ratio of a static momentum strategy and is not explained by other factors. These results are robust across multiple time periods, international equity markets, and other asset classes.

In this paper, we infer how the estimates of firm value by “optimists” and “pessimists” evolve in response to information shocks. Specifically, we examine returns and disagreement measures for portfolios of short-sale-constrained stocks that have experienced large gains or large losses. Our analysis suggests the presence of two groups, one of which overreacts to new information and remains biased over about 5 years, and a second group, which underreacts and whose expectations are unbiased after about 1 year. Our results have implications for the belief dynamics that underlie the momentum and long-term reversal effect.

We model sequential bidding in a private value English auction when it is costly to submit or revise a bid. We show that, even when bid costs approach zero, bidding occurs in repeated jumps, consistent with certain types of natural auctions such as takeover contests. In contrast with most past models of bids as valuation signals, every bidder has the opportunity to signal and increase the bid by a jump. Jumps communicate bidders’ information rapidly, leading to contests that are completed in a few bids. The model additionally predicts; informative delays in the start of bidding; that the probability of a second bid decreases in, and the jump increases in, the first bid; that objects are sold to the highest valuation bidder; and that revenue and efficiency relationships between different auctions hold asymptotically.

Firm sizes and book-to-market ratios are both highly correlated with the average returns of common stocks. Fama and French (1993) argue that the association between these characteristics and returns arise because the characteristics are proxies for nondiversifiable factor risk. In contrast, the evidence in this article indicates that the return premia on small capitalization and high book-to-market stocks does not arise because of the comovements of these stocks with pervasive factors. It is the characteristics rather than the covariance structure of returns that appear to explain the cross-sectional variation in stock returns.

We solve a portfolio choice problem when expected returns, covariances, and trading costs follow a regime-switching model. The optimal policy trades towards an aim portfolio given by a weighted-average of the conditional mean-variance-efficient portfolios in all future states. The trading speed is higher in more persistent, riskier, and higher-liquidity states. It can be optimal to overweight low Sharpe-ratio assets such as Treasury bonds because they remain liquid even in crisis states. We illustrate our methodology by constructing an optimal US equity market timing portfolio based on an estimated regime-switching model and on trading costs estimated using a large-order institutional trading data set.

We propose a theoretically motivated factor model based on investor psychology and assess its ability to explain the cross-section of U.S. equity returns. Our factor model augments the market factor with two factors that capture long- and short-horizon mispricing. The long-horizon factor exploits the information in managers’ decisions to issue or repurchase equity in response to persistent mispricing. The short-horizon earnings surprise factor, which is motivated by investor inattention and evidence of short-horizon underreaction, captures short-horizon anomalies. This 3-factor risk-and-behavioral model outperforms other proposed models in explaining a broad range of return anomalies.

Using data on individual portfolio holdings and on mutual fund flows, we find that low interest rates lead to significantly higher demand for income‐generating assets such as high‐dividend stocks and high‐yield bonds. We argue that this “reaching‐for‐income” phenomenon is driven by investors who follow the “living off income” rule‐of‐thumb. Our empirical analysis shows that this preference for current income affects both household portfolio choices and the prices of income‐generating assets. In addition, we explore the implications of reaching for income for capital allocation and the effectiveness of monetary policy.

We propose a theory of securities market under‐ and overreactions based on two well‐known psychological biases: investor overconfidence about the precision of private information; and biased self‐attribution, which causes asymmetric shifts in investors' confidence as a function of their investment outcomes. We show that overconfidence implies negative long‐lag autocorrelations, excess volatility, and, when managerial actions are correlated with stock mispricing, public‐event‐based return predictability. Biased self‐attribution adds positive short‐lag autocorrelations (“momentum”), short‐run earnings “drift,” but negative correlation between future returns and long‐term past stock market and accounting performance. The theory also offers several untested implications and implications for corporate financial policy.