Computational exploration of the biological basis of black-scholes expected utility function

Sukanto Bhattacharya, Kuldeep Kumar

Research output: Contribution to journalArticleResearchpeer-review

1 Citation (Scopus)


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.

Original languageEnglish
Article number39460
Number of pages15
JournalJournal of Applied Mathematics and Decision Sciences
Publication statusPublished - 2007


Dive into the research topics of 'Computational exploration of the biological basis of black-scholes expected utility function'. Together they form a unique fingerprint.

Cite this