基于马尔科夫随机波动和极值理论的风险测度

Abstract

Abstract: In order to capture the characteristics of changed, gathered and state transitions of the fluctuations in financial assets in the stock returns data, Markov chain is introduced into the SV model to build the MSSV-t model, then the extreme value theory(EVT) is combined to measure the VaR. Use the Shanghai Composite Index for the empirical analysis. Finally the effect of MSSV-t-EVT model is analyzed with Backtesting, the results shows that the MSSV-t-EVT model can portray the fluctuation characteristics of financial yield effectively, especially the extreme fluctuation characteristics. Backtesting results shows, the application of MSSV-t-EVT model to measure the risk of comprehensive Index is reasonable and effective. In particular the higher the confidence level, the higher the accuracy.These results indicate that MSSV-t-EVT model has a better description and warning functions than the traditional linear risk measurement model. It can be used for the risk control of investment portfolio, and also for the warning of abnormal fluctuations by financial regulators.

Key words: MSSV-t model, extreme value, fluctuation state transition, risk measurement

CLC Number:

F831.5

JI Xin-long, ZHOU Xiao-hua. Risk Measurement Based on Markov Stochastic Volatility and EVT[J]. Chinese Journal of Management Science, 2014, 22(10): 44-51.

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Risk Measurement Based on Markov Stochastic Volatility and EVT

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