The predictability of stock returns has always been one of the core research questions in finance. This paper attempts to introduce machine learning method to answer whether stock returns are predictable in China. With 108 characteristics data in Chinese stock market from January 1997 to...

We examine aggregate idiosyncratic volatility in 23 developed equity markets, measured using various methodologies, and we find no evidence of upward trends when we extend the sample until 2008. Instead, idiosyncratic volatility appears to be well described by a stationary autoregressive process...

Stocks with recent past high idiosyncratic volatility have low future average returns around the world. Across 23 developed markets, the difference in average returns between the extreme quintile portfolios sorted on idiosyncratic volatility is -1.31% per month, after controlling for world...

We examine international stock return comovements using country-industry and country-style portfolios. We first establish that parsimonious risk-based factor models capture the covariance structure of the data better than the popular Heston-Rouwenhorst (1994) model. We then establish the...

We examine the pricing of aggregate volatility risk in the cross-section of stock returns. Consistent with theory, we find that stocks with high sensitivities to innovations in aggregate volatility have low average returns. In addition, we find that stocks with high idiosyncratic volatility...

We investigate the ability of several international asset pricing models to price the returns on 36 FTSE global industry portfolios. The models are the international capital asset pricing model (ICAPM) the ICAPM with exchange risks, and global two-factor and three-factor Fama-French (1996, 1998)...