Title: Portfolio analysis and asset management: simple genetic algorithm approach
Author: Mohd Khoshnevisan
Address: College of Business Administration, Prince Sultan University, Riyadh, Saudi Arabia
Journal: J. for Global Business Advancement, 2012 Vol.5, No.1, pp.1 - 6
Abstract: The aim of this paper is to derive a modified computationally efficient genetic learning algorithm to derive the optimal rebalancing weights to engineer a structured portfolio out of different assets. The stochastic target function is formulated as an expected squared cost of hedging error, which is assumed to be partly and harmonically dependent on the governing Markovian process underlying the individual asset returns and partly on randomness. A simple haploid genetic algorithm is developed as an alternative numerical scheme, which is deemed to be computationally more efficient than numerically deriving an explicit solution to the formulated optimisation model.
Keywords: portfolio analysis; asset management; haploid genetic algorithms; option writer.