Title :
Searching co-integrated portfolios by a genetic algorithm
Author :
Kriplani, Pravesh ; Troiano, Luigi
Author_Institution :
Quantitative Strategy Group, Brics Securities Lmt., Mumbai, India
Abstract :
Searching for portfolios co-integrated with an index offers new opportunities in designing robust investment strategies. The problem of finding optimal index co-integrated portfolios that are maximally stationary is combinatorial. Indeed, given a basket of equities, the portfolio/index co-integration cannot be simply expressed in terms of equity/index co-integration. In this paper we investigate the application of simple genetic algorithms in finding optimal portfolios.
Keywords :
genetic algorithms; investment; co-integrated portfolio search; equity-index co-integration; genetic algorithm; portfolio-index co-integration; Design engineering; Genetic algorithms; Globalization; Instruments; Investments; Portfolios; Robust control; Robustness; Security; Stochastic processes;
Conference_Titel :
Nature & Biologically Inspired Computing, 2009. NaBIC 2009. World Congress on
Conference_Location :
Coimbatore
Print_ISBN :
978-1-4244-5053-4
DOI :
10.1109/NABIC.2009.5393522