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Hedging without sweat : a genetic programming approach

Lensberg, Terje; Schenk-Hoppé, Klaus Reiner
Working paper
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URI
http://hdl.handle.net/11250/170377
Date
2013
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  • Working papers (FIN) [10]
Abstract
Hedging in the presence of transaction costs leads to complex op-

timization problems. These problems typically lack closed-form so-

lutions, and their implementation relies on numerical methods that

provide hedging strategies for speci c 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.
Publisher
Norwegian School of Economics. Department of Finance
Series
Working paper;2013:5

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