The MCMC Of Asis To Study On Multivariate Factor Stochastic Volatility In China’s Stock Market

As a powerful tool to measure the investment risk of financial assets,volatility has been widely used in modern financial field,such as portfolio investment,capital asset pricing,arbitrage pricing and option pricing.There are two main types of models for capturing time-varying volatility in financial markets: ARCH model and SV model.Because of the good performance of SV model in describing the characteristics of financial data and volatility prediction,it has been favored by researchers.Based on the application background of financial time series volatility,this paper points out the practical significance of industry index volatility research,and briefly reviews the literature from the aspects of SV model,multiple SV model and estimation methods.The framework of multivariable factor stochastic volatility model(MF-SV)and the estimation methods of model parameters are described in detail.The advantages of MCMC estimation methods of model and interleaving strategy are described.The estimation methods of MF-SV model are compared on simulation.It shows that the MCMC of Ancillarity-sufficiency interweaving strategy(ASIS)is better than the standard MCMC,and the MCMC of deep interweaving strategy is best.In the empirical part,this paper takes the secondary industry index of Shanghai and Shenzhen A-share market as the research object to study and analyze the volatility characteristics and volatility correlation of the industry index based on the MF-SV model.The main conclusions are as follows:(1)Three common factors can be used to describe the volatility of the stock market.The first factor is the general market factor,among the driving power of which the semiconductor,software and hardware are the largest.The second factor is driven by the banking,energy and capital market industries.The third factor is driven by the pharmaceutical,snack and food industries.(2)As a whole,the A-share market has a highly persistent volatility,with the highest volatility in the commercial sector and the weakest volatility in the telecommunications sector.For volatility variance,thetelecommunication industry is the largest,while the commercial industry is the smallest.For the volatility level,the banking industry is the largest and the capital goods industry is the smallest.Finally,some suggestions are given after summarizing the research,and the limitations of this research and the direction of next research are pointed out.