Journal of Applied Finance & Banking

Minimization of Value at Risk of Financial Assets Portfolio using Genetic Algorithms and Neural Networks

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  • Abstract

    In this paper we have proposed an approach for minimization of a shares portfolio invested in a market which the fluctuations follow a normal distribution based in amathematical explicit formulae for calculating Value at Risk (VaR) for portfolios of linear financial assets invested using the Black-Scholes stochastic process and assuming that the portfolio structure remains constant over the considered time horizon. We minimize this Value at Risk using neural networks and genetic algorithms.