Time series momentum (TSM) refers to the predictability of the past 12-month return on the next one-month return and is the focus of several recent influential studies. This paper shows that asset-by-asset time series regressions reveal little evidence of TSM, both in- and out-of-sample. While...

In this paper, we propose two asymmetry measures for stock returns. Unlike the popular skewness measure, our measures are based on the distribution function of the data rather than just the third central moment. We present empirical evidence that greater upside asymmetries calculated using our...

We propose an employee sentiment index, which complements investor sentiment and manager sentiment indices, and find that high employee sentiment predicts a subsequent low market return, significant both in- and out-of-sample. The predictability of the employee sentiment index can also deliver...

We analyze the daily predictability of investor sentiment across four major asset classes and compare sentiment measures based on news and social media with those based on trade information. For the majority of assets, trade-based sentiment measures outperform their text-based equivalents for...

We propose a novel measure of the ex-ante commodity downside-risk premium (CDP) for each commodity based on a term structure model of commodity futures. Our theory-based CDP, capturing forward-looking information in the futures markets, outperforms well-known characteristics in explaining the...

We investigate the effect of ETF ownership on stock market anomalies and market efficiency. We find that low ETF ownership stocks exhibit higher returns, greater Sharpe ratios, and highly significant alphas in comparison to high ETF ownership stocks. We show that high ETF ownership stocks...

We examine the relation between firms’ environmental, social, and governance (ESG) performance and aggregate stock market returns. Based on 38 ESG scores, we construct a market-level ESG index and find its strong positive predictive power on the market returns both in- and out-of-sample, and...