This paper investigates the significance of dynamic conditional beta in predicting the cross-sectional variation in expected stock returns. The results indicate that the time-varying conditional beta is alive and well in the cross-section of daily stock returns. Portfolio-level analyses and...

This paper estimates hedge fund and mutual fund exposure to newly proposed measures of macroeconomic risk that are interpreted as measures of economic uncertainty. We find that the resulting uncertainty betas explain a significant proportion of the cross-sectional dispersion in hedge fund...

A conditional asset pricing model with risk and uncertainty implies that the time-varying exposures of equity portfolios to the market and uncertainty factors carry positive risk premiums. The empirical results from the size, book-to-market, and industry portfolios as well as individual stocks...

This paper investigates the significance of dynamic conditional beta in predicting the cross-sectional variation in expected stock returns. The results indicate that the time-varying conditional beta is alive and well in the cross-section of daily stock returns. Portfolio-level analyses and...

A conditional asset pricing model with risk and uncertainty implies that the time-varying exposures of equity portfolios to the market and uncertainty factors carry positive risk premiums. The empirical results from the size, book-to-market, and industry portfolios as well as individual stocks...

This paper investigates the significance of dynamic conditional beta in predicting the cross-sectional variation in expected stock returns. The results indicate that the time-varying conditional beta is alive and well in the cross-section of daily stock returns. Portfolio-level analyses and...

The WRDS Corporate Bond Database, introduced in April 2017, offers a clean and publicly accessible dataset for corporate bond research. In this article, we construct and replicate the Bai, Bali, and Wen (2019, BBW) factors using the WRDS bond returns with the SAS codes in the appendix. Using the...

We propose a statistical model of differences in beliefs in which heterogeneous investors are represented as different machine learning model specifications. Each investor forms return forecasts from their own specific model using data inputs that are available to all investors. We measure...

This paper examines the cross-sectional relation between idiosyncratic volatility and expected stock returns. The results indicate that (i) data frequency used to estimate idiosyncratic volatility, (ii) weighting scheme used to compute average portfolio returns, (iii) breakpoints utilized to...

This paper investigates the role of skewness preference in cross-sectional pricing of NYSE, AMEX, and NASDAQ stocks over the long sample period of January 1926-December 2005 as well as two subsamples. Portfolio-level analyses and the firm-level cross-sectional regressions indicate a negative and...