In this paper, we study a dynamic Gaussian financial market model in which the traders form higher-order expectations about the fundamental value of a single risky asset. Rational uninformed traders are introduced into an otherwise standard differential information economy to investigate the...

This paper examines to what extent stock market anomalies are driven by firm fundamentals in an investment-based asset pricing framework. Using Bayesian Markov Chain Monte Carlo (MCMC), we estimate a two-capital q-model to match firm-level stock returns, instead of matching portfolio-level...

This paper finds that price inefficiency in individual stocks contributes to expected idiosyncratic volatility. If idiosyncratic risk is priced, greater price inefficiency could be associated with higher expected returns. Consistent with this hypothesis, this paper then finds a positive relation...

Asset returns change with fundamentals and other factors, such as technical information and sentiment over time. In modeling time-varying expected returns, this article focuses on the out-of-sample predictability of the aggregate stock market return via extensions of the conventional predictive...

On financial markets, information is a highly demanded resource and processing it to (potentially) generate excess returns drives the activities of many market participants. Not surprisingly, this high relevance of information in markets culminates in a high research interest focusing on how...

Systematic mispricing primarily affects speculative stocks and predominantly results in overpricing, predicting lower average returns. Because speculative stocks overlap with stocks deemed risky by rational models, failing to control for exposure to systematic mispricing can bias tests of...

We develop a four-factor model intended to capture size, value, and credit rating transition patterns in excess returns for a panel of predominantly mid- and large-cap entities. Using credit transition matrices and rating histories from 48 US issuers, we provide evidence to support a...

We build an equilibrium model to explain why stock return predictability concentrates in bad times. The key feature is that investors use different forecasting models, and hence assess uncertainty differently. As economic conditions deteriorate, uncertainty rises and investors' opinions...

We propose a parsimonious measure based solely on daily stock returns to characterize the severity of microstructure frictions at the individual stock level and assess the impact of frictions on the cross section of stock returns. Stocks with the largest frictions command a value-weighted return...

We provide the first large-scale study of the performance of expected-return proxies (ERPs) internationally. Analyst-forecast-based ICCs are sparsely populated and not robustly associated with future returns. Earnings-model-forecast-based ICCs are well-populated, but are unreliable outside the...