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Computational Exploration of the Biological Basis of Black-Scholes Expected Utility Function

机译:Black-Scholes期望效用函数的生物学基础的计算探索

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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 establishedby 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 functionextended to a multiasset scenario.Computational Exploration of the Biological Basis of Black-Scholes Expected Utility Functiondx.doi.org/10.1155/2007/36729
机译:经常有人争辩说,存在效用功能的潜在生物学基础。本文将这一论点更进一步,我们旨在通过计算论证将Black-Scholes函数形式的生物学基础应用于经典期权定价和对冲理论。借助于单倍体遗传算法模型,通过计算确定了经典Black-Scholes函数的演化最优性。目的是最大程度地减少资产组合的动态套期保值误差,该资产组合旨在复制欧洲多资产期权的收益。可以连续实现最佳实现此优化目标的功能形式是扩展到多资产场景的经典Black-Scholes函数。Black-Scholes预期效用的生物学基础的计算探索dx.doi.org/10.1155/2007 / 36729

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