Deciphering robust portfolios |
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| Institution: | 1. Department of Industrial and Systems Engineering, Korea Advanced Institute of Science and Technology (KAIST), Yuseong-gu, Daejeon 305-701, Republic of Korea;2. EDHEC Business School, Nice, France;1. National School of Development Peking University;2. Graduate School of Business Administration Fordham University;1. Norges Bank, Financial Stability Research, Bankplassen 2, P.O. Box 1179, Sentrum, Norway;2. BI Norwegian Business School, Nydalsveien 37, 0484 Oslo, Norway;1. DIW Berlin, Department of Macroeconomics, Mohrenstraße 58, 10117 Berlin, Germany;2. Financial Stability Department, Bank of Canada, Ottawa, Ontario K1A 0G9, Canada;3. Technische Universität Berlin, Sek. H 52, Straße des 17. Juni 135, 10623 Berlin, Germany;1. Kent Business School, University of Kent, Canterbury, United Kingdom;2. Department of Mathematical Sciences, University of Essex, United Kingdom |
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| Abstract: | Robust portfolio optimization has been developed to resolve the high sensitivity to inputs of the Markowitz mean–variance model. Although much effort has been put into forming robust portfolios, there have not been many attempts to analyze the characteristics of portfolios formed from robust optimization. We investigate the behavior of robust portfolios by analytically describing how robustness leads to higher dependency on factor movements. Focusing on the robust formulation with an ellipsoidal uncertainty set for expected returns, we show that as the robustness of a portfolio increases, its optimal weights approach the portfolio with variance that is maximally explained by factors. |
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| Keywords: | Robust portfolio optimization Mean–variance model Fundamental factors |
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