We introduce uncertainty into Holmstrom and Milgrom (1987) to study optimal long-term contracting with learning. In a dynamic relationship, the agent's shirking not only reduces current performance, but also increases the agent's information rent due to the persistent belief manipulation effect. We characterize the optimal contract using the dynamic programming technique in which information rent is the unique state variable. In the optimal contract, the optimal effort is front-loaded and stochastically decreases over time. Furthermore, the optimal contract exhibits an option-like feature in that incentives increase after good performance. Implications about managerial incentives and asset management compensations are discussed.

We hypothesize that cognitive limitation may be manifested in a disproportionately large volume of limit orders submitted at round-number prices if investors use these numbers as cognitive shortcuts. Using detailed limit order data in the Taiwan Futures Exchange, we find that investors with lower cognitive abilities, defined as higher limit order submission ratios at round numbers, suffer greater losses in their round-numbered and non-round-numbered limit orders, market orders, and round-trip trades. The positive correlation between cognitive ability and investment performance is monotonic and robust across futures and options markets. In addition, past trading experience helps mitigate cognitive limitation.

[We find a positive association between short selling and accruals during 1988—2009, and that asymmetry between the up- and downsides of the accrual anomaly is stronger when constraints on short arbitrage are more severe (low availability of loanable shares as proxied by institutional holdings). Short arbitrage occurs primarily among firms in the top accrual decile. Asymmetry is present only on NASDAQ. Thus, there is short arbitrage of the accrual anomaly, but short-sale constraints limit its effectiveness.]

[We have developed Bayesian Markov chain Monte Carlo (MCMC) methods for inferences of continuous-time models with stochastic volatility and infinite-activity Lévy jumps using discretely sampled data. Simulation studies show that (i) our methods provide accurate joint identification of diffusion, stochastic volatility, and Lévy jumps, and (ii) the affine jump-diffusion (AJD) models fail to adequately approximate the behavior of infinite-activity jumps. In particular, the AJD models fail to capture the "infinitely many" small Lévy jumps, which are too big for Brownian motion to model and too small for compound Poisson process to capture. Empirical studies show that infinite-activity Lévy jumps are essential for modeling the S&P 500 index returns.]

On August 12–13, 2005, the department of finance at the Kelley School of Business, Indiana University, collaborated with the Review of Financial Studies to host a conference titled “The Causes and Consequences of Recent Financial Market Bubbles.” This article begins with our overview of the themes and findings of the conference, and it ends with the questions that the literature has yet to answer.

Buying is easier than shorting for many equity investors. Combining this arbitrage asymmetry with the arbitrage risk represented by idiosyncratic volatility (IVOL) explains the negative relation between IVOL and average return. The IVOL‐return relation is negative among overpriced stocks but positive among underpriced stocks, with mispricing determined by combining 11 return anomalies. Consistent with arbitrage asymmetry, the negative relation among overpriced stocks is stronger, especially for stocks less easily shorted, so the overall IVOL‐return relation is negative. Further supporting our explanation, high investor sentiment weakens the positive relation among underpriced stocks and, especially, strengthens the negative relation among overpriced stocks.

We explore the link between open-market share repurchases (OMRs) and asymmetric information based on financial reporting quality and find that opaque firms experience positive abnormal returns of twice the magnitude of those of transparent firms. These significant differences remain after controlling for governance, earnings management, and firm characteristics. We document significantly positive long-run postannouncement returns for opaque firms, but not for transparent firms. We find that takeover activity and premiums rise with repurchase activity by opaque firms, which may explain some of the wealth effects. Our results suggest that asymmetric information plays an important role in the wealth effects around OMRs.

We use a unique quasi-experiment–spillovers from the imposition of purchase restrictions on local housing to nearby unregulated cities–to study the effects of out-of-town housing demand on house prices and consumer spending. While these restrictions effectively stymied the surge in local house prices, they induced capital flight and sharp abnormal increases in house prices in nearby unregulated cities. The effect of the house price increases on consumer spending is positive in the aggregate, but echoing Favilukis and Van Nieuwerburgh (2021), is redistributive, that is, negative for renters and positive for homeowners.

We document five novel facts about the role of search effort in forming trading relationships among firms by combining a variety of micro and macro datasets. These facts strongly suggest the presence of search complementarities. To study the implications of these facts for aggregate fluctuations, we build a dynamic general equilibrium model, disciplined by our new firm-level evidence on search effort. The model matches key aspects of the macro and micro data that have remained unaccounted for by standard models, including the time-varying bimodal distribution of output and the strong, nonlinear propagation of shocks. Also, changes to the volatility of shocks have nonlinear effects on macroeconomic fluctuations that advance a novel interpretation of the Great Moderation. Finally, we provide a new account of the state-dependent effects of fiscal policy.

This paper analyses a model of strategic exploration in which competing players independently explore a set of alternatives. The model features a multiple-player multiple-armed bandit problem and captures a strategic trade-off between pre-emption—covert exploration of alternatives that the opponent will explore in the future—and prioritization—exploration of the most promising alternatives. Our results explain how the strategic trade-off shapes equilibrium behaviours and outcomes, for example, in technology races between superpowers and R&D competitions between firms. We show that players compete on the same set of alternatives, leading to duplicated exploration from start to finish, and they explore alternatives that are a priori less promising before more promising ones are exhausted. The model also predicts that competition induces players to implement unreliable technologies too early, even though they should wait for the technologies to mature. Coordinated exploration is impossible even if the alternatives are equally promising, but it can emerge in equilibrium following a phase of pre-emptive competition if there is a short deadline. With asymmetric capacities of exploration, the weak player conducts extensive instead of intensive exploration—exploring as many alternatives as the strong player does but never fully exploring any.