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Risk Minimization in Stochastic Volatility Models: Model Risk and Empirical PerformanceRolf PoulsenUniversity of Copenhagen - Department of Statistics and Operations Research Klaus Reiner Schenk-HoppéUniversity of Leeds - Leeds University Business School; University of Leeds - School of Mathematics Christian-Oliver EwaldUniversity of Glasgow; Center for Dynamic Macroeconomic Analysis, University of St. Andrews - School of Economics and Finance September 2007 FINRISK Working Paper No. 361 Swiss Finance Institute Research Paper No. 07-10 Abstract: In this paper the performance of locally risk-minimizing hedge strategies for European options in stochastic volatility models is studied from an experimental as well as from an empirical perspective. These hedge strategies are derived for a large class of diffusion-type stochastic volatility models, and they are as easy to implement as usual delta hedges. Our simulation results on model risk show that the locally risk-minimizing hedges are robust with respect to uncertainty and even misconceptions about the underlying data generating process. The empirical study indicates that locally risk-minimizing hedge strategies consistently produce lower standard deviations of profit-and-loss-ratios than delta hedges (over different time periods as well as in different markets). The more skewed the market and the more out-of-the-money the option, the higher the benefit.
Number of Pages in PDF File: 23 Keywords: Locally risk-minimizing hedge, delta hedge, stochastic volatility, JEL Classification: C90, G13 working papers seriesDate posted: February 23, 2007 ; Last revised: December 4, 2007Suggested CitationContact Information
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