Application of Bayesian stochastic volatility model in Chinese fund market
MO Yu-ting
LIU Jin-shan
Abstract：By analyzing the statistical structure of the stochastic volatility model, and using the Bayesian theorem, we derive the posterior distribution of model’s parameter. We use the Markov chain Monte Carlo algorithm to estimate model’s parameter, and the FFBS(forward filtering and backward sampling)algorithm to estimate the volatility. We apply the stochastic volatility model to analyze the Shenzhen and Shanghai fund market, and the result indicated that the model can explore the volatility characteristics of fund market.
Keywords：SV modelBayesian inferenceFFBS algorithm
Publication Date：2016-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：6( 5-10 )