Study On Markov Regime Switching ARCH Model And VaR Estimation

In recent years, financial market volatility makes the financial institutions and regulatory authorities face enormous challenges. Financial institutions focus on identify and measure financial risk. In the financial markets, the introduction of economic policy, the financial regulatory system change and improve themselves will lead to regime-switching.In order to consider the financial market returns in different states of structural changes, this article will introduce the Markov process under ARCH models. SSE Index as an example is carried out in the empirical study, SW-ARCH model and non-parametric kernel density estimation techniques are used to identify the substantially abnormal fluctuations state of the stock market under the global financial crisis. Then Kupiec test is used for the accuracy of VaR to verify the validity of the model. The emergence of the reasons for the high volatility regime was briefly discussed.The empirical results show that the SW-ARCH model can reflect the different states of the conditional variance and the mean duration of the state, but also reflect the structural changes of the time point of the state, especially in abnormal fluctuations in the market when volatility can improve the prediction capacity. Series of policies and regulations (such as state-owned shares, QFII system, adjustment of stamp duty, etc.) lead to high volatility regime occurs. While interest rate volatility, real estate control policies will lead to the emergence of the high volatility state. In a way that interest rates will lead to the emergence of high volatility state. The only direct credit for housing and housing policy will lead to high volatility to some extent the emergence of the state, but there is a certain lag.