This paper attempts to find an aggregate leading indicator to predict the spreads observed for high-yield (HY) bond indices. Using a vector error correction (VEC) specification for quarterly data, we establish a long-term equilibrium relationship between the HY market spreads and its...

We use intraday data to compute weekly realized variance, skewness, and kurtosis for equity returns and study the realized moments' time-series and cross-sectional properties. We investigate if this week's realized moments are informative for the cross-section of next week's stock returns. We...

This paper examines whether deep/machine learning can help find any statistical and/or economic evidence of out-of-sample bond return predictability when real-time, instead of fully-revised, macro variables are taken as predictors. First, when using pure real-time macro information alone, we...

Motivated by existing evidence of a preference among investors for stocks with high maximum daily returns, we document that lottery-like payoffs measured by maximum daily returns are almost entirely idiosyncratic. Firm-level cross-sectional regressions and portfolio-sort analyses prove that...

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...

We examine the informational efficiency of market ambiguity in predicting market excess returns and the equity premium internationally. Empirical results show a strong predictive ability of option-implied, and sentiment-based, ambiguity for U.S. stock market returns for up to three years. We...

This paper demonstrates that the forecasted CAPM beta of momentum portfolios explains a large portion of the return, ranging from 40% to 60% for stock level momentum, and 30% to 50% for industry level momentum. Beta forecasts are from a realized beta estimator using daily returns over the prior...

We identify all return leader-follower pairs among individual stocks using Granger causality regressions. Thus-identified leaders can reliably predict their followers' returns out of sample, and the return predictability works at the level of individual stocks rather than industries. Our results...

This article comprehensively reviews the predictability of six equity factors. These factors are the market excess return, size, value, momentum, low beta and quality. I find predictability for the low beta factor and moderate predictability for the size factor. The results for other factors are...

There is limited evidence of intraday predictability both in the cross-section of US stock returns (see Heston et al., 2010) and in the time-series of the aggregate stock market (see Gao et al., 2015). I find that statistical time-series predictability does not imply economic profitability,...