%0 Conference Paper %1 Keber:2002:gecco %A Keber, Christian %A Schuster, Matthias G. %B GECCO 2002: Proceedings of the Genetic and Evolutionary Computation Conference %C New York %D 2002 %E Langdon, W. B. %E Cantú-Paz, E. %E Mathias, K. %E Roy, R. %E Davis, D. %E Poli, R. %E Balakrishnan, K. %E Honavar, V. %E Rudolph, G. %E Wegener, J. %E Bull, L. %E Potter, M. A. %E Schultz, A. C. %E Miller, J. F. %E Burke, E. %E Jonoska, N. %I Morgan Kaufmann Publishers %K adaptive agents, algorithm, algorithms, ant artificial behavior, colony genetic life, optimization, option programming, regression symbolic valuation, %P 74--81 %T Option Valuation With Generalized Ant Programming %U ftp://cs.ucl.ac.uk/genetic/papers/gecco2002/gecco-2002-01.pdf %X For the valuation of American put options exact pricing formulas haven't as yet been derived We therefore determine analytical approximations for pricing such options by introducing the Generalised Ant Programming (GAP) approach applicable to all problems in which the search space of feasible solutions consists of computer programs. GAP is a new method inspired by Genetic Programming as well as by Ant Algorithms. Applying our GAP-approximations for the valuation of American put options on non-dividend paying stocks to experimental data as well as huge validation data sets we can show that our formulas deliver accurate results and outperform other formulas presented in the literature. %@ 1-55860-878-8

@inproceedings{Keber:2002:gecco, abstract = {For the valuation of American put options exact pricing formulas haven't as yet been derived We therefore determine analytical approximations for pricing such options by introducing the Generalised Ant Programming (GAP) approach applicable to all problems in which the search space of feasible solutions consists of computer programs. GAP is a new method inspired by Genetic Programming as well as by Ant Algorithms. Applying our GAP-approximations for the valuation of American put options on non-dividend paying stocks to experimental data as well as huge validation data sets we can show that our formulas deliver accurate results and outperform other formulas presented in the literature.}, added-at = {2008-06-19T17:35:00.000+0200}, address = {New York}, author = {Keber, Christian and Schuster, Matthias G.}, biburl = {https://www.bibsonomy.org/bibtex/284b6437dcd045bd62cedef018f301586/brazovayeye}, booktitle = {GECCO 2002: Proceedings of the Genetic and Evolutionary Computation Conference}, editor = {Langdon, W. B. and Cant{\'u}-Paz, E. and Mathias, K. and Roy, R. and Davis, D. and Poli, R. and Balakrishnan, K. and Honavar, V. and Rudolph, G. and Wegener, J. and Bull, L. and Potter, M. A. and Schultz, A. C. and Miller, J. F. and Burke, E. and Jonoska, N.}, interhash = {ef0a79450b0694d9d0e43acd97c318e5}, intrahash = {84b6437dcd045bd62cedef018f301586}, isbn = {1-55860-878-8}, keywords = {adaptive agents, algorithm, algorithms, ant artificial behavior, colony genetic life, optimization, option programming, regression symbolic valuation,}, month = {9-13 July}, notes = {GECCO-2002. A joint meeting of the eleventh International Conference on Genetic Algorithms (ICGA-2002) and the seventh Annual Genetic Programming Conference (GP-2002)}, pages = {74--81}, publisher = {Morgan Kaufmann Publishers}, publisher_address = {San Francisco, CA 94104, USA}, timestamp = {2008-06-19T17:43:00.000+0200}, title = {Option Valuation With Generalized Ant Programming}, url = {ftp://cs.ucl.ac.uk/genetic/papers/gecco2002/gecco-2002-01.pdf}, year = 2002 }