Computational Exploration of the Biological Basis of Black-Scholes Expected Utility Function (Erratum)
Author(s) -
Sukanto Bhattacharya,
Kuldeep Kumar
Publication year - 2007
Publication title -
journal of applied mathematics and decision sciences
Language(s) - English
Resource type - Journals
eISSN - 1532-7612
pISSN - 1173-9126
DOI - 10.1155/2007/36729
Subject(s) - basis (linear algebra) , function (biology) , black–scholes model , computational finance , computer science , mathematics , econometrics , biology , statistics , evolutionary biology , volatility (finance) , geometry
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.
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