Genetic Algorithm Approach for Building Trading Decision Support Indicators in Financial Markets

oleksiyshylakhovyy.jpgOleksiy Shylakhovyy graduated from Kharkiv National University of Radio Electronics (KNURE), Ukraine, and has recently passed his MPhil viva at Wessex Institute of Technology with a thesis entitled “Genetic algorithm approach for building trading decision support indicators in financial markets”.  His external examiner was Prof Paolo Coletti from the Free University of Bolzano, Italy, and his internal examiner was Prof Viktor Popov.

The main aim of this work was to develop a method for building technical indicators for supporting trading decisions in the financial market. Technical indicators, also known as filters, were investigated as well as the markets they are applied to. Special emphasis was put on the Forex currency market. The Simple Moving Average, taken as a base filter for the research, was modified in order to improve its performance. The possibility of configuring the filter using neural networks and genetic algorithms was examined. A new filter was developed especially for the case of automatic optimization using genetic algorithms. The work dealt with the combination of the filter and the optimization method that extends some common trader limits. A software tool was developed in order to implement the method of configuring the filter with the use of historical currency data. Optimization tests using the developed software and alternative software with common optimization methods were carried out. Unambiguous results were obtained leading to the conclusion that Moving Average functions had undiscovered potential when used on financial markets and genetic algorithms were suitable for tuning the trading strategy based on the Moving Average function.

As a result of his research, both examiners recommended that Oleksiy be awarded the degree of Master of Philosophy.

Grateful acknowledgement is given to the Foreign and Commonwealth Office for their support.