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Hedging without sweat: a genetic programming approach

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  • Terje Lensberg
  • Klaus Reiner Schenk-Hopp\'e

Abstract

Hedging in the presence of transaction costs leads to complex optimization problems. These problems typically lack closed-form solutions, and their implementation relies on numerical methods that provide hedging strategies for specific parameter values. In this paper we use a genetic programming algorithm to derive explicit formulas for near-optimal hedging strategies under nonlinear transaction costs. The strategies are valid over a large range of parameter values and require no information about the structure of the optimal hedging strategy.

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File URL: http://arxiv.org/pdf/1305.6762
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Paper provided by arXiv.org in its series Papers with number 1305.6762.

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Date of creation: May 2013
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Handle: RePEc:arx:papers:1305.6762

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Web page: http://arxiv.org/

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  1. Monoyios, Michael, 2004. "Option pricing with transaction costs using a Markov chain approximation," Journal of Economic Dynamics and Control, Elsevier, vol. 28(5), pages 889-913, February.
  2. Umut Çetin & L. C. G. Rogers, 2007. "Modeling Liquidity Effects In Discrete Time," Mathematical Finance, Wiley Blackwell, vol. 17(1), pages 15-29.
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