Data driven value-at-risk forecasting using a SVR-GARCH-KDE hybrid

• Main Authors: LUX, Marius, HARDLE, Wolfgang Karl, LESSMANN, Stefan
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2020
• Subjects: Value-at-Risk; Support Vector Regression; Kernel Density Estimation; GARCH; Econometrics; Finance; Finance and Financial Management
• Online Access: https://ink.library.smu.edu.sg/skbi/1; https://ink.library.smu.edu.sg/context/skbi/article/1001/viewcontent/Data_driven_Value_at_risk_av.pdf
• Institution: Singapore Management University

Appropriate risk management is crucial to ensure the competitiveness of financial institutions and the stability of the economy. One widely used financial risk measure is value-at-risk (VaR). VaR estimates based on linear and parametric models can lead to biased results or even underestimation of ri...