부산대학교 도서관

This paper introduces a stock scanner evaluator for stocks and options. In the presented work the scanner picks from thousands of stocks the most suitable stocks for an options or stocks investor. The proposed stocks scanner evaluator suggests the stocks that have the largest positive near future change (for purchasing stocks or calls) and the stocks that have the largest negative near future change (for purchasing puts). The scanner uses a neural network to rank the stocks and the neural network is trained using parallel genetic algorithm. Related work is provided as well as model framework, neural network and parallel genetic algorithm, results testing and evaluation together with future work.