Hedging without sweat: a genetic programming approach
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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- 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.
- Umut Cetin & L.C.G. Rogers, 2007.
"Modeling liquidity effects in discrete time,"
LSE Research Online Documents on Economics
2844, London School of Economics and Political Science, LSE Library.
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