Measurement And Prediction Of Stock Volatility In A-shares

Volatility is the core factor that determines financial modeling,option pricing,risk hedging,and model calibration.Without a reasonable volatility model,we will not be able to price derivatives and hedge them.From the perspective of derivatives trading,the possible gains and losses are derived from the gap between the traders' estimation of the future volatility and the estimate of the options market.From the perspective of risk hedging,the risk of holding derivatives is the actual volatility,so the correct risk hedging can only be built.It is based on the correct understanding of the volatility.This paper focuses on the measurement and prediction of stock volatility.In the second chapter,the paper briefly introduces the method of measuring the high frequency price data of volatility(the rate of volatility)and the daily frequency price measurement of volatility,and compares the advantages and disadvantages of the traditional Volatility Measurement Method in the empirical part and gives the optimal sampling frequency of the realized volatility.In the third chapter,we take Guizhou Moutai as an example to derive an empirical stochastic volatility model,and get the time evolution of random volatility and describe the probability distribution of random volatility in the future.In the last chapter,this paper introduces and compares two forecasting methods that surpass the GARCH model family,the HAR-RV model and the MIDAS model,in which the HAR-RV model has shown good performance in the estimation and prediction of the volatility in Guizhou Moutai.