We examine whether cross-firm return predictability is associated with accounting quality (AQ), and find that stock returns of good AQ firms significantly positively predict one-month-ahead stock returns to industry- and size- matched poor AQ firms. In testing a delayed-information-processing...

An increase in the number of asset pricing models intensifies model uncertainties in assetpricing. While a pure "model selection" (singling out a best model) can result in a loss of usefulinformation, a full “model pooling” may increase the risk of including noisy information.We make a...

According to the dynamic version of the Gordon growth model, the long-run expected return on stocks, stock yield, is the sum of the dividend yield on stocks plus some weighted average of expected future growth rates in dividends. We construct a measure of stock yield as a model-imposed affine...

We investigate the prediction of excess returns and fundamentals by financial ratios – dividend-price ratio, earnings-price ratio, and book-to-market ratio – by decomposing financial ratios into a cyclical component and a stochastic trend component. We find both components predict excess...

The paper examines statistical and economic evidence of out-of-sample bond return predictability for a real-time Bayesian investor who learns about parameters, hidden states, and predictive models over time. We find some statistical evidence using information contained in forward rates. However,...

Many modern macro finance models imply that excess returns on arbitrary assets are predictable via the price-dividend ratio and the variance risk premium of the aggregate stock market. We propose a simple empirical test for the ability of such a model to explain the cross-section of expected...

We use a sample of option prices, and the method of Bakshi, Kapadia and Madan (2003), to estimate the ex ante higher moments of the underlying individual securities' risk-neutral returns distribution. We find that individual securities' volatility, skewness, and kurtosis are strongly related to...

We decompose the quadratic payoff on a stock into its loss and gain components and measure the premia associated with their fluctuations, called the loss and gain quadratic risk premium (QRP) respectively. The loss QRP interprets as the premium paid for downside risk hedging, while the gain QRP...

We decompose the quadratic payoff on a stock into its loss and gain components and measure the premia associated with their fluctuations, called the loss and gain quadratic risk premium (QRP) respectively. The loss QRP interprets as the premium paid for downside risk hedging, while the gain QRP...