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dc.contributor.authorZhang, Lequn
dc.contributor.supervisorHonglei Xuen_US
dc.contributor.supervisorSong Wangen_US
dc.contributor.supervisorQuanxi Shaoen_US

Value at Risk (VaR) is one of the key risk measures for quantitative financial risk management. VaR measures extreme risk, which has a small probability but a significant consequence to financial institutions. This thesis develops methods based on an extended extreme value approach to improve the forecast skill of VaR. The proposed methods improve the forecasting accuracy, robustness, efficiency and outperform the existing methods in the literature.

dc.publisherCurtin Universityen_US
dc.titleExtreme Risk Forecast for Quantitative Financial Risk Managementen_US
curtin.departmentSchool of Electrical Engineering, Computing and Mathematical Sciencesen_US
curtin.accessStatusOpen accessen_US
curtin.facultyScience and Engineeringen_US
curtin.contributor.orcidZhang, Lequn [0000-0001-8453-8454]en_US

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