Hedging of options in the presence of jump clustering

Donatien Hainaut () and Franck Moraux ()
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Donatien Hainaut: ESC [Rennes] - ESC Rennes School of Business

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Abstract: This paper analyzes the efficiency of hedging strategies for stock options in the presence of jump clustering. In the proposed model, the asset is ruled by a jump-diffusion process, wherein the arrival of jumps is correlated to the amplitude of past shocks. This feature adds feedback effects and time heterogeneity to the initial jump diffusion. After a presentation of the main properties of the process, a numerical method for options pricing is proposed. Next, we develop four hedging policies, minimizing the variance of the final wealth. These strategies are based on first- and second-order approximations of option prices. The hedging instrument is either the underlying asset or another option. The performance of these hedges is measured by simulations for put and call options, with a model fitted to the Standard & Poor's 500.

Keywords: quadratic hedges; jump risk; jump clustering (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (6)

Published in The Journal of Computational Finance, 2018, 22 (3), pp.1-35. ⟨10.21314/jcf.2018.354⟩

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Related works:
Working Paper: Hedging of options in presence of jump clustering (2018)
Working Paper: Hedging of options in presence of jump clustering (2017)
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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:halshs-02024279

DOI: 10.21314/jcf.2018.354

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