Data-Driven Risk Measurement by SV-GARCH-EVT Model

This paper aims to more effectively manage and mitigate stock market risks by accurately characterizing financial market returns and volatility. We enhance the Stochastic Volatility (SV) model by incorporating fat-tailed distributions and leverage effects, estimating model parameters using Markov Chain Monte Carlo (MCMC) methods. By integrating extreme value theory (EVT) to fit the tail distribution of standard residuals, we develop the SV-EVT-VaR-based dynamic model. Our empirical analysis, usi...