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Calculation Of VaR Of Financial Garch Models And Its Application In Financial Markets

Posted on:2012-01-07Degree:MasterType:Thesis
Country:ChinaCandidate:P C YuFull Text:PDF
GTID:2120330335987211Subject:Applied Mathematics
Abstract/Summary:PDF Full Text Request
VaR(Value-at-Risk) is an assessment method of measuring the risk of financial market, combining with knowledge of Statistics, which can quickly, accurately and comprehensively understand and further quantify the risk of market. Since the new century, especially the world financial crisis in 2008, the international and domestic financial markets have undergone profound changes, and the financial risk has significantly increased. Measuring financial volatility and analyzing the characteristics of financial volatility, are of great significance both for investment and regulatory.VaR has been done extensive theoretical research and a large number of empirical analyses abroad, and has been widely used by investors, commercial banks, investment banks and market regulators. China scholars have also done a lot of research work, but there is still a gap between the actual situation of China financial and securities markets, so we have to speed up exploring the risk measurement method, and provide reference for macro-economic adjustment.This article is divided into five chapters, in the first chapter the background, development process and the latest research progress of VaR are comprehensively described; in the second chapter we introduce the theory ideas and the basic calculation methods of VaR; in the third chapter, combining with the nature of general auto-regressive conditional hetero scedasticity model, the empirical likelihood is introduced into the calculation of VaR; in the fourth chapter we make the earnings of Shanghai stock market as research object, and carry out empirical research. The empirical research shows that there is "fat tail" nature in financial markets, which can be effectively described by GARCH type models, and that VaR has good maneuverability and accuracy in measuring the financial market risks; in the fifth chapter we summarize and improve VaR, and provide some recommendations for the healthy development of China's financial market.
Keywords/Search Tags:The risk of financial market, General auto-regressive conditional hetero scedasticity model, Empirical likelihood, Value-at-Risk
PDF Full Text Request
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