DocumentCode :
1511535
Title :
Evolutionary computation and the vega risk of American put options
Author :
Keber, Christian ; Schuster, Matthias G.
Author_Institution :
Dept. of Bus. Adm., Wien Univ., Austria
Volume :
12
Issue :
4
fYear :
2001
fDate :
7/1/2001 12:00:00 AM
Firstpage :
704
Lastpage :
715
Abstract :
While European style options and American call options can be priced using analytical exact valuation models, closed-form solutions for the valuation of American puts have not yet been derived. The American put price as well as the corresponding greeks (e.g., delta, gamma, vega) can be calculated using numerical procedures or analytical approximations. We use a parallel implementation of the genetic programming approach and derive analytical approximations for determining the vega of an American put option because calculating vegas numerically requires even more computational effort than determining deltas or gammas. Applying our approximations to experimental data sets we can show that the genetically derived approximations outperform other approximations based on frequently used American put pricing formulas
Keywords :
genetic algorithms; investment; probability; stock markets; American put options; analytical approximations; evolutionary computation; genetic programming approach; vega risk; Analytical models; Closed-form solution; Concurrent computing; Context modeling; Cost accounting; Evolutionary computation; Genetic programming; Lattices; Portfolios; Pricing;
fLanguage :
English
Journal_Title :
Neural Networks, IEEE Transactions on
Publisher :
ieee
ISSN :
1045-9227
Type :
jour
DOI :
10.1109/72.935084
Filename :
935084
Link To Document :
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