Genetic Algorithms for Predicting the Egyptian Stock Market

The purpose of this paper is to discover a semi-optimal set of trading rules and to investigate its effectiveness as applied to Egyptian Stocks. The aim is to mix different categories of technical trading rules and let an automatic evolution process decide which rules are to be used for particular time series. This difficult task can be achieved by using Genetic Algorithms (GA's), they permit the creation of artificial experts taking their decisions from an optimal subset of the a given set of trading rules. The GA's based on the survival of the fittest, do not guarantee a global optimum but they are known to constitute an effective approach in optimizing non-linear functions. Selected Liquid Stocks are tested and GA Trading rules were compared with other Conventional and well known Technical Analysis Rules. The Proposed GA system showed clear better average profit and in the same High Sharpe ratio, which indicates not only good profitability but also better risk-reward trade-off.