Safety-first portfolio optimization for US investors in emerging global,Asian and Latin American markets |
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| Institution: | 1. Indiana State University, Terre Hante, IN 47809, USA;2. Department of Economics and Finance, University of New Orleans, New Orleans, LA 70148, USA;1. Faculty of Pure and Applied Mathematics, Hugo Steinhaus Center Wroclaw University of Science and Technology, Wybrzeze Wyspianskiego 27, 50-370 Wroclaw, Poland;2. Diagnostics and Vibro-Acoustics Science Laboratory, Wroclaw University of Science and Technology, Wybrzeze Wyspianskiego 27, 50-370 Wroclaw, Poland;3. KGHM CUPRUM sp. z o.o. Centrum Badawczo-Rozwojowe, ul. Gen. Wl. Sikorskiego 2-8, 53-659 Wroclaw, Poland;1. Room 3.12 O''Rahilly Building, Department of Accounting, Finance and Information Systems and Environmental Research Institute, University College Cork, Ireland;2. Environment and Natural Resources, School of Business, University of Iceland, Gimli v/Saemundargata, 101 Reykjavík, Iceland;1. School of Economics and Management, Beihang University, Beijing, China;2. Beijing Key Laboratory of Emergency Support Simulation Technologies for City Operations, Beijing, China;3. Beijing Advanced Innovation Center for Big Data and Brain Computing, Beijing, China |
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| Abstract: | Risk averse US investors with safety-first objectives in portfolio optimization hold small weights (maximum 10%) in emerging markets when constructing portfolios of the Standard and Poor's 500 (SP), and the Emerging Markets Composite Global (CG), Asia (AS) and Latin American (LA) indexes, respectively. The Composite Global and Asia weights are even smaller than their minimum variance weights. Yet, these optimal safety-first portfolios are dominant in terms of risk and return over the global minimum or higher variance portfolios. In contrast, safety-first optimization for Latin America is hardly different from the minimum variance and not clearly dominant over other mean–variance portfolios. Overall, safety-first limits portfolio losses associated with infrequent catastrophic events and otherwise optimize performance. |
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