Alternative strategies for predicting stock market volatility are examined. In out-of-sample forecasting experiments implied-volatility information, derived from contemporaneously observed option prices or history-based volatility predictors, such as GARCH models, are investigated, to determine if they are more appropriate for predicting future return volatility. Employing German DAX-index retu...

This article develops a real options model to study the interaction of industry structure and takeovers. In an asymmetric industry equilibrium, firms have an endogenous incentive to merge when restructuring decisions are motivated by operating and strategic benefits. The model predicts that (i) merger activities are more likely in more concentrated industries or in industries that are more expo...

Prediction Markets in Theory and Practice Prediction Markets, sometimes referred to as “information markets,” “idea futures” or “event futures”, are markets where participants trade contracts whose payoffs are tied to a future event, thereby yielding prices that can be interpreted as market-aggregated forecasts. This article summarizes the recent literature on prediction markets, highlighting b...

This paper investigates the effects of mortgage-backed securities (MBS) hedging activity on interest-rate volatility and proposes a model that takes these effects into account. An empirical examination suggests that the inclusion of information about MBS considerably improves model performance in pricing interest-rate options and in forecasting future interest-rate volatility. The empirical res...

Contributing to the literature on local bias, we examine how the direct and indirect network ties of financial intermediaries mitigate two types of information problems, the identification of investment opportunities and the evaluation of their quality. In our analysis of the non-domestic IPOs and trade sales exits of European venture capitalbacked companies, we find that direct and indirect ne...

Many economists believe that credit market distortions create a financial accelerator which destabilizes the economy. This paper shows that when credit market distortions arise from adverse selection they sometimes stabilize the economy rather than destabilize it. The stabilizing forces are closely related to forces that cause overinvestment in static models. When investment projects are equity...

We show that firm-level short interest predicts negative returns for individual stocks during economic expansions, while aggregate short interest predicts negative market returns during recessions. Viewing short sellers as informed traders, these findings are consistent with Kacperczyk, Van Nieuwerburgh, and Veldkamp’s (2016) model in which rational yet cognitively constrained traders optimally...

We use mutual fund flows as a measure of individual investor sentiment for different stocks, and find that high sentiment predicts low future returns. Fund flows are dumb money–by reallocating across different mutual funds, retail investors reduce their wealth in the long run. This dumb money effect is related to the value effect: high sentiment stocks tend to be growth stocks. High sentiment a...

A dynamic model of financial markets with learning is demonstrated to produce a selforganized system that displays critical behavior. The price contains private information that traders learn to extract and employ to forecast future value. Since the price reflects the beliefs of the traders, the learning process is self referencing. As the market learns to correctly extract information from the...

This paper demonstrates that an asset pricing model with least-squares learning can lead to bubbles and crashes as endogenous responses to the fundamentals driving asset prices. When agents are risk-averse they generate forecasts of the conditional variance of a stock’s return. Recursive updating of the conditional variance and expected return implies two mechanisms through which learning impac...