基于EVT-POT-SVt模型的风险度量研究

Facing with the fat-tail proceeds and the heteroskedasticity characteristics of volatility from financial assets return, the article uses Markov chain Monte Carlo method to estimate the parameters of the Standard SV model. At the same time, it transfers return series into standard residuals and uses EVT-POT method to capture the fat tails of standard residuals. Then, the paper constructs a new dynamic VaR risk measure based on EVT-POT-SV and applies it to daily returns of composite index of Shanghai stock market. The empirical analysis indicates that the risk measure can describe index return's dynamic VaR risk more exactly and reasonably.