Risk minimization in stochastic volatility models: model risk and empirical performance

Poulsen, R., Schenk-Hoppe, K.-R. and Ewald, C.-O. (2009) Risk minimization in stochastic volatility models: model risk and empirical performance. Quantitative Finance, 9(6), pp. 693-704. (doi:10.1080/14697680902852738)

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In this paper the performance of locally risk-minimizing delta 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 these risk-minimizing hedges are robust with respect to uncertainty and misconceptions about the underlying data generating process. The empirical study, which includes the US sub-prime crisis period, documents that in equity markets risk-minimizing delta hedges consistently outperform usual delta hedges by approximately halving the standard deviation of the profit-and-loss ratio.

Item Type:Articles
Glasgow Author(s) Enlighten ID:Ewald, Professor Christian
Authors: Poulsen, R., Schenk-Hoppe, K.-R., and Ewald, C.-O.
College/School:College of Social Sciences > Adam Smith Business School > Economics
Journal Name:Quantitative Finance
ISSN (Online):1469-7696
Published Online:24 August 2009

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