Using monthly data from 01/1985 to 12/2012, we find that the accounting valuation-based predictor introduced in Lee, Myers, and Swaminathan (1999) has excellent in-sample and out-of-sample predictive performance. Our finding suggests that the accounting valuation-based predictor does not suffer...

We extend Merton’s 1976 asset return analysis which relied on intraday trade data to estimate volatility by introducing drift estimation and equity premium dynamics leading to predictability of short run daily returns under appropriate conditions. We find empirical support for the...

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...

In this paper we investigate the predictive power of cross-sectional volatility, skewness and kurtosis for future stock returns. Adding to the work of Maio (2016), who finds cross-sectional volatility to forecast a decline in the equity premium with high predictive power in-sample as well as...

This paper examines the relationship between idiosyncratic risk and stock returns in BRICS (Brazil, Russia, India, China, and South Africa) countries by applying parametric and nonparametric approaches. It also explores the idiosyncratic risk puzzle by dividing firms into groups based on...

The performance of analysts’ forecasts has attracted increasing attention in recent years. However, as yet, no empirical study has investigated the nexus between the analyst forecast dispersion (AFD) and excess returns surrounding stock market crashes in any depth. This paper attempts to fill...

Measures of a firm's financial strength forecast stock returns. The relation between financial condition and future returns, however, is consistent with two explanations: (1) changes in investors' expectations are impounded gradually over time and, (2) riskier firms - with higher discount rates...

We examine whether option prices correct for predictable bias in stock prices associated with accounting anomalies. Evidence from put-call parity violations suggests that they do not. Rather, option prices accurately track contemporaneous stock prices. Further analysis suggests that high costs...

In this study, we examine the predictability of firm-specific stock price crashes using modern machine learning techniques and develop a crash prediction model that utilizes both financial ratios and textual data from the Management Discussion and Analysis (MD&A) of 10-K files. We show that...

We compare several representative sophisticated model averaging and variable selection techniques of forecasting stock returns. When estimated traditionally, our results confirm that the simple combination of individual predictors is superior. However, sophisticated models improve dramatically...