Advances in Decision Sciences
Volume 2007 (2007), Article ID 39460, 15 pages
doi:10.1155/2007/39460
Computational exploration of the biological basis of Black-Scholes expected utility function
Sukanto Bhattacharya1
and Kuldeep Kumar2
1Department of Business Administration, Alaska Pacific University, Anchorage 99508, AK, USA
2School of Business, Bond University, Australia
Abstract
It has often been argued that there exists an underlying biological basis of utility functions. Taking this line of argument a step further in this paper, we have aimed to computationally demonstrate the biological basis of the Black-Scholes functional form as applied to classical option pricing and hedging theory. The evolutionary optimality of the classical Black-Scholes function has been computationally established by means of a haploid genetic algorithm model. The objective was to minimize the dynamic hedging error for a portfolio of assets that is built to replicate the payoff from a European multi-asset option. The functional form that is seen to evolve over successive generations which best attains this optimization objective is the classical Black-Scholes function extended to a multiasset scenario.