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Quantile Regression And Financial Risk

Posted on:2012-08-22Degree:MasterType:Thesis
Country:ChinaCandidate:Y L HaoFull Text:PDF
GTID:2219330338951089Subject:Statistics
Abstract/Summary:PDF Full Text Request
China formally joined the WTO in 2001 year, in recent years, as the global economic integration, a country's financial asset price volatility often lead to a chain reaction around the world, especially when a country's financial crisis, will bring serious consequences to the global economy, in such a background, research on the financial risk has become more and more important. In order to reflect the proceeds of assets timely in financial markets the extent of losses to avoid the risk betterly, VaR has become widely used by monetary authorities and various financial institutions risk management tools, it can portfolio some time in the future may be subject to a maximum loss to quantify. In 1996, the Basel Committee's Risk Capital Agreement which expressly provides for use of VaR models to quantify the risk. But there is no single authoritative method of calculating VaR, so how accurate VaR measure in order to make better use of VaR for risk management appears to be very theoretical and practical significance. According to the characteristics of VaR itself, will be applied to the calculation of the quantile regression process of VaR, trying to find a new method of calculating VaR. The main content and innovation can be summarized as the following two aspects:First, highlight the combination of VaR and quantile regression; Based on conclused the application of quantile regression for financial risk measurement methods, highlighted the method of combine VaR and quantile regression method- CAViaR method; then use the CAViaR method analysed the Chinese futures market risk, and compared with several other VaR calculation methods on this basic.Second, for product's trading volume and yields have very close relationship in the financial markets, therefore we try to added volume of the variable to the CAViaR model and used it to have an empirical study on the basis of the futures market in China, and obtained lots of satisfactory conclusion.
Keywords/Search Tags:Risk Management, CAViaR, Quantile
PDF Full Text Request
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