In this paper, we conduct a comprehensive study of tests for mean-variance spanning. Under the popular regression framework of Huberman and Kandel (1987), we provide geometric interpretations of three asymptotic tests (likelihood ratio, Wald, and Lagrange multiplier) of mean-variance spanning....

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 construct a lottery factor that aggregates the information of 16 commonly used lottery features. The lottery factor significantly improves the explanatory power of the four-factor q model in Hou, Xue, and Zhang (2015) and explains all but a few major anomaly returns. In assessing the...

We propose a new investor sentiment index that is aligned with the purpose of predicting the aggregate stock market. By eliminating a common noise component in sentiment proxies, the new index has much greater predictive power than existing sentiment indices both in- and out-of-sample, and the...

This paper extends the machine learning methods developed in Han et al. (2019) for forecasting cross-sectional stock returns to a time-series context. The methods use the elastic net to refine the simple combination return forecast from Rapach et al. (2010). In a time-series application focused...

We construct an information factor (INFO) using the informed stock buying of corporate insiders and the informed selling of short sellers and option traders. INFO strongly predicts future stock returns -- a long-short portfolio formed on INFO earns monthly alphas of 1.24%, substantially...

We use machine learning tools to analyze industry return predictability based on theinformation in lagged industry returns from across the entire economy. Controlling forpost-selection inference and multiple testing, we nd significant in-sample evidence ofindustry return predictability. Lagged...

Using time-series trends of a set of firms' major fundamentals, we find that there is a fundamentalmomentum in the stock market. Buying stocks in the top quintile of fundamental trends and selling stocks in the bottom quintile earns a monthly average return of 0.88%, whose magnitude is...

Based on a rational option pricing framework that incorporates short-selling and margin-trading constraints in the stock market, we present evidence that Chinese warrant prices, which are regarded as bubbles in the previous literature, can be explained by a new option pricing model. Based on the...

We apply a reduced-rank approach to reduce a large number of observable factors to a few parsimonious ones. Out of 70 factor proxies, we find that the best five combinations seem adequate and outperform the Fama-French (2015) five factors for pricing industry portfolios as expected. However,...