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Robust Decision Support System for Asset Assessment and Management
Stockholm University, Faculty of Social Sciences, Stockholm Business School.
Number of Authors: 12017 (English)In: IEEE Systems Journal, ISSN 1932-8184, E-ISSN 1937-9234, Vol. 11, no 3, p. 1486-1491Article in journal (Refereed) Published
Abstract [en]

We address asset classification and portfolio selection in this paper. Surprisingly, money managers find that the market volatility becomes more frequent as more advanced innovations are applied in the financial system. For example, the high-frequency trading may amplify the deviation on U.S. stock market [1], [2]. Therefore, a reliable method to appraise the asset performance is extremely important to portfolio managers, regulators, and individual investors. One alternative approach to achieve this goal is data envelopment analysis (DEA). Asset performance was ranked from both self-and peer-evaluation perspectives. Specifically, we extended the cross-efficiency analysis in DEA that uses row and column means to portfolio selection and identify different types of asset set. This classification process can help investors to construct a more robust portfolio. Numerical experiments based on S&P500 showed that the portfolio with cross-efficiency analysis can generate better Sharpe ratios during the period of financial crisis in 2008.

Place, publisher, year, edition, pages
2017. Vol. 11, no 3, p. 1486-1491
Keywords [en]
Cross-efficiency analysis, data envelopment analysis (DEA), portfolio selection, uncertainty
National Category
Computer and Information Sciences Electrical Engineering, Electronic Engineering, Information Engineering Economics and Business
Identifiers
URN: urn:nbn:se:su:diva-151016DOI: 10.1109/JSYST.2016.2565264ISI: 000417373200030OAI: oai:DiVA.org:su-151016DiVA, id: diva2:1172597
Available from: 2018-01-10 Created: 2018-01-10 Last updated: 2018-01-13Bibliographically approved

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