Research on the Volatility of China's Stock Market Based on MCMC Algorithm

摘要

Financial time series contains information on market changes and investment risk fluctuations. This paper aims to study the volatility of China's stock market by analyzing the time series of Chinese stock market returns. We choose the closing price of the Shanghai and Shenzhen close index as a sample. To analyze the statistical characteristics of the time series, we choose the SV-MN model in the SV model family by MCMC algorithm based on Gibbs sampling to estimate the basic characteristics of the stock market volatility. Through research, we find that China's stock market has the characteristics of agglomeration, volatility persistence and Leptokurtosis. We analyze these characteristics and specific market reasons to provide financial and securities service industries with relevant recommendations to stabilizing the market.