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Stock Portfolio Selection with Full-Scale Optimization and Differential Evolution
Stockholm University, Faculty of Social Sciences. Stockholm University, Faculty of Social Sciences, School of Business. (Finance)
Aston Business School. (Economic Department)
2009 (English)In: Applied Financial Economics, ISSN 0960-3107, E-ISSN 1466-4305, Vol. 19, 1559-1571 p.Article in journal (Refereed) Published
Abstract [en]

Full-Scale Optimization (FSO) is a utility maximization approach to portfolio choice problems that has theoretical appeal but that suffers from computational burden in large scale problems. We apply the heuristic technique differential evolution to solve FSO-type asset selection problems of 97 assets under complex utility functions rendering rough utility search surfaces. We show that this problem is computationally feasible and that solutions retrieved with random starting values are converging to one optimum. Furthermore, the study constitutes the first FSO application to stock portfolio optimization. The results indicate that when investors are loss averse, FSO improves stock portfolio performance compared to Mean Variance (MV) portfolios. This finding widens the scope of applicability of FSO, but it is also stressed that out-of-sample success will always be dependent on the forecasting ability of the input return distributions.

Place, publisher, year, edition, pages
2009. Vol. 19, 1559-1571 p.
National Category
Business Administration
Research subject
Business Administration
URN: urn:nbn:se:su:diva-43256DOI: 10.1080/09603100903018778OAI: diva2:355085
Available from: 2010-10-05 Created: 2010-10-05 Last updated: 2010-10-15Bibliographically approved

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Hagströmer, Björn
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