dc.contributor.author | Lensberg, Terje | |
dc.contributor.author | Schenk-Hoppé, Klaus Reiner | |
dc.date.accessioned | 2014-09-08T07:09:56Z | |
dc.date.accessioned | 2014-09-22T12:42:51Z | |
dc.date.available | 2014-09-08T07:09:56Z | |
dc.date.available | 2014-09-22T12:42:51Z | |
dc.date.issued | 2013-06-26 | |
dc.identifier.citation | Quantitative Finance Letters 2013, 1(1):41-46 | nb_NO |
dc.identifier.issn | 2164-9502 | |
dc.identifier.uri | http://hdl.handle.net/11250/220927 | |
dc.description.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. | nb_NO |
dc.language.iso | eng | nb_NO |
dc.publisher | Taylor & Francis | nb_NO |
dc.rights | Navngivelse-Ikkekommersiell-DelPåSammeVilkår 3.0 Norge | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-sa/3.0/no/ | * |
dc.subject | hedging | nb_NO |
dc.subject | transaction costs | nb_NO |
dc.subject | closed form approximations | nb_NO |
dc.subject | genetic programming | nb_NO |
dc.title | Hedging without sweat: a genetic programming approach | nb_NO |
dc.type | Journal article | nb_NO |
dc.type | Peer reviewed | nb_NO |
dc.date.updated | 2014-09-08T07:09:57Z | |
dc.source.pagenumber | 41-46 | nb_NO |
dc.source.volume | 1 | nb_NO |
dc.source.journal | Quantitative Finance Letters | nb_NO |
dc.source.issue | 1 | nb_NO |
dc.identifier.doi | 10.1080/21649502.2013.813166 | |
dc.identifier.cristin | 1105940 | |