This study predicts stock market volatility and applies them to the standard problem in finance, namely, asset allocation. Based on machine learning and model averaging approaches, we integrate the drivers’ predictive information to forecast market volatilities. Using various evaluation...

This article studies the risk forecasting properties of three realized volatility models for three Chinese individual stocks, and reveals the important role that jumps can play in risk prediction. I firstly investigate dynamic pattern of jumps in three Chinese stocks, and find that relative to...

This paper challenges the prevailing view that investor sentiment is a contrarian predictor of market returns at nearly all horizons. As an important piece of "out-of-sample" evidence, we document that investor sentiment in China is a reliable momentum signal at monthly frequency. The strong...

While numerous studies have analyzed the asset allocation issue of US stock market from various angles, much less attention has been paid to the asset allocation issue of Chinese stock market. This article investigates the asset allocation in Chinese stock market from a perspective of...

This paper investigates the predictive ability of international volatility risk for the daily aggregate Chinese stock market returns. We employ the innovations in implied volatility indices of seven major international markets as our international volatility risk proxies. We find that...

Recent evidence on the relationship between investor sentiment and subsequent monthly market returns in China shows that investor sentiment is a reliable momentum predictor since an increase (decrease) in investor sentiment leads to higher (lower) future returns. However, we suggest that...

The empirical literature of stock market predictability mainly suffers from model uncertainty and parameter instability. To meet this challenge, we propose a novel approach that combines the documented merits of diffusion indices, regime-switching models, and forecast combination to predict the...

The empirical literature of stock market predictability mainly suffers from model uncertainty and parameter instability. To meet this challenge, we propose a novel approach that combines the documented merits of diffusion indices, regime-switching models, and forecast combination to predict the...

The empirical literature of stock market predictability mainly suffers from model uncertainty and parameter instability. To meet this challenge, we propose a novel approach that combines the documented merits of diffusion indices, regime-switching models, and forecast combination to predict the...

We investigate the stock return predictability for the aggregate Central and Eastern European (CEE) markets from 1998 through the mid-2017. Using the firm-level data we construct country portfolios and sets of component portfolios: 10 industry portfolios, 10 size portfolios, 10 market-to-book...