GARCH Processes with Non-parametric Innovations for Market Risk Estimation

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• 作者：Jos¨¦ Miguel Hern¨¢ndez-Lobato ; Daniel Hern¨¢ndez-Lobato ; Alberto Su¨¢rez
• 刊名：Lecture Notes in Computer Science
• 出版年：2007
• 出版时间：2007
• 年：2007
• 卷：4669
• 期：1
• 页码：718-727
• 全文大小：465 KB

文摘

A procedure to estimate the parameters of GARCH processes with non-parametric innovations is proposed. We also design an improved technique to estimate the density of heavy-tailed distributions with real support from empirical data. The performance of GARCH processes with non-parametric innovations is evaluated in a series of experiments on the daily log-returns of IBM stocks. These experiments demonstrate the capacity of the improved estimator to yield a precise quantification of market risk.