This paper investigates empirically the dynamics of investors' beliefs and Bayesian uncertainty about the state of the economy as state variables that describe the time-variation in investment opportunities. Using measures of uncertainty constructed from the state probabilities estimated from...

We discuss the finding that cross-sectional characteristic based models have yielded portfolios with higher excess monthly returns but lower risk than their arbitrage pricing theory counterparts in an analysis of equity returns of stocks listed on the JSE. Under the assumption of general...

We develop a model in which investors have heterogeneous beliefs about both the mean and the risk of future signals and the final stock payoff. As investors who perceive the lowest risk vary across different periods, the overall perception of the market risk is reduced in an economy with dynamic...

We provide strong evidence that the dispersion of individual stock options trading volume across moneynesses (IDISP) contains valuable information about future stock returns. Stocks with high IDISP consistently underperform those with low IDISP by more than 1% per month. In line with the idea...

Deep learning methods, which can accommodate wide ranges of various stock characteristics to identify optimal investment portfolio or stochastic discount factor (SDF), have been criticized for extracting their superior performances from difficult to arbitrage stocks, high limits-to-arbitrage...

We identify model-free mispricing factors and relate them to global stock prices and investor beliefs. The factors measure variation in the relative mispricing of closed-end funds and their underlying assets. We design three factors to reflect the beliefs and capital flows of important...

Using a very large data set with more than 9,700 stocks listed on NYSE, AMEX and NASDAQ, we analyze overnight price jumps and report short-term investor overreaction to information shocks and document return reversal and predictability up to five days. For negative and positive overnight jumps,...

We show theoretically that when Bayesian investors face time-series uncertainty about assets' risk exposures, differences in their priors affect the pricing of risk in the cross-section: different priors for the same asset can generate differences in perceived risk exposures, and thereby...

We propose a model, which is a modification of the Salomon Smith Barney model for cost of capital determination. The model reflects the following characteristics: (1) the degree of diversification of the particular investor (imperfectly diversified); (2) the systematic country risk; (3) firm...

Our paper makes two empirical contributions on REITs' asset pricing over three sequential and mutually exclusive time periods. The first yields the beta estimates of (i) assets, (ii) growth options and (iii) assets-in-place, embedded in the valuations of REITs. We develop a new approach to...