Abstract
Abstract This paper described the volatility characteristic of the rate of return of financial asset by using QR-GARCH model, through introducing EVT model and constructing the extreme risk measure model based on QR-GARCH-EVT. In this paper, HS300 index data test was applied to show that under 5% significance level, and QR-GARCH-EVT model can effectively measure the risk value of the sample, but under 1% significance level. QR-GARCH-EVT model will underestimate the risk value of the sample to a certain degree, but generally speaking, compared with other models, the risk value measured by QR-GARCH-EVT model has a higher accuracy to enhance effectiveness.
Highlights
In order to cope with financial market crisis such as the stock market crash of the Wall Street in 1987 and the monetary system breakdown of Europe in 1992, risk value (VaR) emerged in 1990s
This paper firstly used the fractile self-regression method proposed by Xiao and Koenker [22] to estimate global parameter and potential volatility, used EVT to simulate the tail of unknown innovation distribution, when borrowing the information of adjacent fractile to estimate limit fractile, semiparametric setting imposes minimum restrictive hypothesis on the innovation distribution using EVT, this paper firstly used QRGARCH based on the model to fit the stylized fact characteristics of financial return, and based on obtained residuum series, use EVT model to build the model of residuum series, further build QR-GARCH-EVT based on financial risk measure model, and use HS300 index data to demonstrate and test the effectiveness of the model
Considering the excellent property of fractile regression model not needing to assume the shape and parameter of distribution, this paper firstly used QR-GARCH model to fit financial asset return characteristics, on the basis of obtaining the volatility and residuum, this paper introduced EVT model and constructed QR-GARCHEVT based on extreme risk measure model eventually
Summary
In order to cope with financial market crisis such as the stock market crash of the Wall Street in 1987 and the monetary system breakdown of Europe in 1992, risk value (VaR) emerged in 1990s. Existing researches on financial risk mostly are based on measuring VaR value by combining fractile method and GARCH family models, with something negotiable. This paper firstly used the fractile self-regression method proposed by Xiao and Koenker [22] to estimate global parameter and potential volatility, used EVT to simulate the tail of unknown innovation distribution, when borrowing the information of adjacent fractile to estimate limit fractile, semiparametric setting imposes minimum restrictive hypothesis on the innovation distribution using EVT, this paper firstly used QRGARCH based on the model to fit the stylized fact characteristics of financial return, and based on obtained residuum series, use EVT model to build the model of residuum series, further build QR-GARCH-EVT based on financial risk measure model, and use HS300 index data to demonstrate and test the effectiveness of the model
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
