A Study On Risk Measurement Of Chinese Stock Market Based On Extreme Value Heory

In recent years, financial fragility inherently has become increasingly more serious in some emerging, or even mature market economies, instead of being weakened with the rapid development of the financial sector, which has resulted in the more frequent crisis. Financial risks are also systematic, likely to bring national, regional or worldwide economic system disorders, recession or even collapse such as the Subprime Mortgage Crisis which broke out in U.S. in 2007 and have been raging economic system worldwidely.In view of the endogenous and systematic of financial risks, undoubtedly, to resist and prevent financial risks is of great significance to the economy of one country. The foundation and core of effective resistance and prevention is the accurate measurement of financial risks, which has become a very important issue in the research of financial theory. At present, as internationally the most important tool of measuring risks, VaR describes the most possible loss in the future given a certain degree of confidence. VaR measures risk through measuring profit and loss by introducing the concept of confidence level, it combines expected loss and its probability, and directly measures the value of portfolio's risk. However, different from other types of assets, the sequence of returns on most financial assets practically bares significant characteristics of the fat-tail, which means that there exists a flawed assumption of the normal distribution of assets'returns, and that the tail extreme risk is underestimated because of the ignorance of rare events.Though the probability of the occurrence of extreme risk is very low, the occurrence will definitely cause great damage, and the consequences are often disastrous. Therefore, in order to manage financial risks, events of extreme value are particularly worthy of our attention. J.B.Philippe (2000) also pointed out that in financial sector what should be concerned is nothing but extreme risks, and what should firstly be controlled are also extreme risks. In recent years, the international regulators of financial industry have kept trying to develop a number of provisions to restrict banks to be exposed to these extreme risks.Extreme Value Theory (Extreme Value Theory, EVT) is the modeling technique focusing on the distribution and characteristics of the extreme value of random processes, the most prominent feature of which is that the flat-tail in random processes could be better solved, and in the case of population distribution unknown, the changing nature of population's extreme value could be deduced from sample data, which could overcome the limitations of traditional statistical methods which cannot make analysis beyond sample data. Applying EVT to financial risk management can make up for the lack of VaR methodology, therefore could estimate the financial extreme events caused by the extreme risk more accurately.In addition, China is in the socio-economic transition period. Though the commercial financial system has been initially established with the subject of state-owned commercial banks, the reform of financial system market is still lagging far behind other sectors of the economy. The industry as a whole is more influenced by policies. The market operating mechanism frequently changes. Risks in financial system continue to accumulate instead of lowering. Financial market vibrates, such as the frequent great fluctuations recently. Thus, how to accurately measure the extreme risk of financial market based on EVT has become an urgent task for the financial sector experiencing the socio-economic transformation.Focusing the measurement of financial risk of extreme, this study empirically investigated the extreme risks of Chinese stock market based the theoretical researches of extreme value and relevant conclusions.This dissertation made an in-depth study on the type and nature of the asymptotic distribution of extreme value. It studied BMM and POT model based on GEV and GPD separately, and introduced the two models into the estimation of tail high quantile. It examined the impact of the correlation of financial time series on EVT model and its eliminating disposal. It also studied standards of selection and validation of Back Testing techniques of EVT model. Particularly, in the BMM model, it took into account the relationship between the distribution of the extreme value limit of subinterval and that of sequence, and measured the extreme value of VaR affected by the length of the subinterval. In POT model, it used the technique of parameter estimator stability, making up for the limits of the currently popularly-used Mean Excess Function e (u ), and the threshold quantitatively selected by Kurtosis Method has also been achieved, and solving the problem the illustration method couldn't be applied to. It also discussed other quantitative methods, such as Exponential Regression Model Method, Subsample Bootstrap Method, Sequential Method and so on.Taking into account the factor of raising limit in Chinese stock markets, we sub-selected data of composite indices of returns on days between benchmark day to December 26, 1996, and December 26, 1996 to March 12, 2008, measured and compared the extreme risk in Chinese stock markets before and after the raising limit. In the empirical part, we particularly investigated the impact of raising limit on the distribution of tail sequence of returns data from Chinese stock markets, that is, the inhibit effect of raising limit on the heterogeneity of data with extreme value, as well as the efficiency of results of EVT Model and the effective indicators of extreme risk.Based on EVT, this dissertation focused on the measurement of extreme financial risks, the academic and practical significance of which is to provide both theoretical and methodological support for financial market investors and market regulators to guard against extreme financial risks.