Evaluating Value at Risk Using a Hybrid Model of Support Vector Machine Based and the GARCH

• Main Authors: Saeed Fallahpoor, malihe tabasi
• Format: Article
• Language: fas
• Published: Alzahra University 2013-06-01
• Series: راهبرد مدیریت مالی
• Subjects: Volatility; Value at Risk; Support Vector Machine
• Online Access: http://jfm.alzahra.ac.ir/article_958_b069982d21711d5f9bb5b22748203a01.pdf

One of the main subjects of financial management is risk management. Risk management involves recognizing, measuring and monitoring risk. So measuring risk is very important part of the risk management. One of the most recognized and applied way of measuring risk, is evaluating value at risk that is the main subject of this research. In this research, we forecast volatility of TEPIX index and TSE-50 index, using the hybrid model of support vector machine based and the GARCH, then we calculate Value at Risk by Variance-Covariance approach and finally we compare its result with the traditional models including: Risk Metrics, GARCH and EGARCH by LOPEZ’s back testing and back testing based of expected shortfall. The result of this research has shown that the hybrid model significantly outperform the competing models.