Emerging markets,downside risk and the asset allocation decision |
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| Affiliation: | 1. School of Economics and Management, Leibniz University Hannover, Koenigsworther Platz 1, D-30167, Hannover, Germany;2. ICMA Centre, Henley Business School, University of Reading, Reading, RG6 6BA, UK;3. Management School, University of Liverpool, L69 7ZH, Liverpool, UK;1. Tecnológico de Monterrey (ITESM), Campus Monterrey, Mexico;2. Central Economics and Mathematics Institute (CEMI), Moscow, Russia;3. Sumy State University, Sumy, Ukraine;4. ICREA-BSC, C/Jordi Girona 29, Barcelona, Spain;5. Universidad Autónoma de Nuevo León (UANL), Monterrey, Mexico;1. Department of Finance and Insurance, Lingnan University, Tuen Mun, Hong Kong;2. Private Enterprise Research Center, Texas A&M University, College Station, TX 77845, USA;1. Department of Agricultural and Consumer Economics, University of Illinois at Urbana-Champaign, USA;2. Department of Agribusiness Economics, Southern Illinois University-Carbondale, USA;3. Department of Agricultural and Resource Economics, University of California-Davis, USA;1. School of International Trade and Economics, University of International Business and Economics, No.10 Huixin East Street, Chaoyang District, Beijing, 100029, PR China;2. Stuart School of Business, Illinois Institute of Technology, 565 W Adams St., Chicago, IL 60661, USA;3. Efficient Capital Management, Adjunct Faculty, Illinois Institute of Technology Stuart School of Business and Edhec Business School, 4355 Weaver Parkway, Warrenville, IL 60555, USA |
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| Abstract: | This study examines the use of downside risk measures in the construction of an optimal international portfolio, with particular reference to the estimated allocations in emerging markets and the out-of-sample performance of the optimal portfolios. The use of downside risk measures is assessed due to the problems of using a conventional mean-variance analysis approach in the presence of the non-normality often found to be present in emerging market data. The data set used consists of the MSCI indices for developed equity markets and the IFC data set on emerging markets. The primary component of the paper consists of the construction of optimal portfolios under both mean-variance and downside risk frameworks. In addition, the use of Bayes–Stein estimators is also assessed, in an attempt to reduce estimation error. The resulting estimated allocations are then used to assess the out-of-sample performance of the optimal portfolios. The results indicate that for risk-averse investors the use of downside risk measures can result in significant improvements in performance. |
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