The Volatility Forecasting And Option Risk Hedging In Chinese Stock Market

In this paper,we mainly study volatility in financial market.Based on high-frequency data,we build heterogeneous autoregressive(HAR)models with different specifications to forecast the future realized volatility of stocks in Chinese stock market and apply it in option risk hedging as well.As measurements of liquidity,daily volume of trading and number of transactions are considered into the extended HAR-RV models.In out Empirical test,we perform in-sample forecasting regressions and out-sample prediction.Three different frequencies of data are considered to calculate the realized volatility in our study.We conclude that the explanatory power of long-term volatility in China's A-share market is relatively weak compared with that in the U.S.stock market.We evaluate the accuracy of the built models and find that the 5-mins is the most suitable frequency.Thorough our empirical test,we get that the HAR-RV model has certain prediction efficiency for SSE 50 Index.We also conclude that adding one of liquidity measurements as volume and number of trades into HAR-RV model can improve the performance in volatility forecasting but considering the two variables together will reduce the efficiency.We apply the HAR-RV model to the option risk hedging of stock market in China.We find that the implied volatility adjusted by the HAR-RV model can improve the performance of Delta hedging strategy of 50 ETF options.