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This paper aims to characterize the typical factual characteristics offinancial market returns and volatility and address the problem that the tailcharacteristics of asset returns have been not sufficiently considered, as anattempt to more effectively avoid risks and productively manage stock marketrisks. Thus, in this paper, the fat-tailed distribution and the leverage effectare introduced into the SV model. Next, the model parameters are estimatedthrough MCMC. Subsequently, the fat-tailed distribution of financial marketreturns is comprehensively characterized and then incorporated with extremevalue theory to fit the tail distribution of standard residuals. Afterward, anew financial risk measurement model is built, which is termed theSV-EVT-VaR-based dynamic model. With the use of daily S&P 500 index andsimulated returns, the empirical results are achieved, which reveal that theSV-EVT-based models can outperform other models for out-of-sample data inbacktesting and depicting the fat-tailed property of financial returns andleverage effect.

Dynamic Risk Measurement by EVT based on Stochastic Volatility models via MCMC