Title :
Design of Genetic Algorithm for Knapsack Problem to Perform Stock Portfolio Selection Using Financial Indicators
Author :
Patalia, Tejas P. ; Kulkarni, G.R.
Author_Institution :
V.V.P. Eng. Coll., Singhania Univ., Rajkot, India
Abstract :
In the financial markets, there are different assets, such as stocks, bonds, foreign exchanges, options, commodities, real estates and future contracts, available for trading. The qualities of these assets vary from very good to extremely poor. Usually, it is difficult for investors to find out those good quality assets because of information asymmetry and asset price fluctuations. Therefore, it is not wise to use portfolio theory blindly for optimizing asset allocation among some low quality assets. The suitable way of constructing a portfolio is to select some good quality assets. Markowitz´s portfolio theory only provides a solution to asset selection among the pre-determined assets.
Keywords :
genetic algorithms; investment; knapsack problems; stock markets; asset allocation; asset price fluctuation; bonds; commodities; financial indicator; financial market; foreign exchanges; future contracts; genetic algorithm; good quality assets; information asymmetry; knapsack problem; options; real estates; stock portfolio selection; Biological cells; Companies; Educational institutions; Genetic algorithms; Optimization; Portfolios; Search problems; Chromosomes; Genetic Algorithm; Heuristic methods; Markowitz´s portfolio selection; Mutation;
Conference_Titel :
Computational Intelligence and Communication Networks (CICN), 2011 International Conference on
Conference_Location :
Gwalior
Print_ISBN :
978-1-4577-2033-8
DOI :
10.1109/CICN.2011.60