NONLINEARITY AND GENETIC ALGORITHMS IN THE DECISION-MAKING PROCESS

Nizar Hachicha and Abdelfettah Bouri
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Nizar Hachicha: Faculty of Management of Sfax Rte aéreport km 4, Tunisia
Abdelfettah Bouri: Faculty of Management of Sfax Rte aéreport km 4, Tunisia

Chapter 21 in Risk Management and Value:Valuation and Asset Pricing, 2008, pp 541-562 from World Scientific Publishing Co. Pte. Ltd.

Abstract: AbstractThe irruption of the nonlinearity leads to an in-depth transformation of a number of financial fields such as stock exchange decision-making. Nonlinearity leads to a source of infinity of behaviors making, which allows to better understand the phenomena considered complex. Nevertheless, the nonlinear models consider the stocks only by their consequences. Thus, it is proved to be difficult to explain the emergent phenomena due to the interaction of these individual behaviors.For the last two decades, thanks to the advent of the data-processing techniques, many works have followed one another in shedding light on the behaviors of the markets. The sophisticated tools borrowed from biology, such as the genetic algorithms, have been introduced in the field of finance and stock exchange decision-making.In this chapter, we have compared the decision-making based on the nonlinear models and the genetic algorithms on the BVMT. It is true that the nonlinear models had a good capacity of estimation, but they lose their quality in term of stock exchange's decision. However, the genetic algorithms had a better capacity (94%) compared to the nonlinear models in the total of the decisions taken.

Keywords: Risk; Value; Management; Derivatives (search for similar items in EconPapers)
Date: 2008
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