We propose a general GARCH framework that allows the predict volatility using returns sampled at a higher frequency than the prediction horizon. We call the class of models High FrequencY Data-Based PRojectIon-Driven GARCH, or HYBRID-GARCH models, as the volatility dynamics are driven by what we...

We investigate the impact of China's economic policy uncertainty (EPU) on the time series variation of Chinese stock market expected returns. Using the news based measure in Baker, Bloom, and Davis (2016), we find that EPU predicts negatively future stock market return at various horizons. This...

This paper investigates the effects of U.S. economic variables on the time variation of Chinese stock market volatility. We find that several U.S. economic variables such as the dividend price ratio, dividend yield and industrial production strongly forecast the future monthly volatilities 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...

This paper proposes a novel way of pricing S&P500 index options in the presence of jump risk. Our analysis is built upon an equilibrium option pricing rule for a representative agent economy. In particular, we use the weighted utility's certainty equivalent to specify agent's risk preference,...