dc.contributor.author | Lensberg, Terje | |
dc.contributor.author | Schenk-Hoppé, Klaus Reiner | |
dc.date.accessioned | 2013-06-18T08:00:17Z | |
dc.date.available | 2013-06-18T08:00:17Z | |
dc.date.issued | 2013 | |
dc.identifier.uri | http://hdl.handle.net/11250/170377 | |
dc.description.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. | no_NO |
dc.language.iso | eng | no_NO |
dc.publisher | Norwegian School of Economics. Department of Finance | no_NO |
dc.relation.ispartofseries | Working paper;2013:5 | |
dc.subject | hedging | no_NO |
dc.subject | transaction costs | no_NO |
dc.subject | closed form approximations | no_NO |
dc.subject | genetic programming | no_NO |
dc.title | Hedging without sweat : a genetic programming approach | no_NO |
dc.type | Working paper | no_NO |
dc.subject.nsi | VDP::Social science: 200::Economics: 210::Business: 213 | no_NO |
dc.subject.jel | G13 | |