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Gains from diversification on convex combinations: A majorization and stochastic dominance approach

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  • Egozcue, Martin
  • Wong, Wing-Keung

Abstract

By incorporating both majorization theory and stochastic dominance theory, this paper presents a general theory and a unifying framework for determining the diversification preferences of risk-averse investors and conditions under which they would unanimously judge a particular asset to be superior. In particular, we develop a theory for comparing the preferences of different convex combinations of assets that characterize a portfolio to give higher expected utility by second-order stochastic dominance. Our findings also provide an additional methodology for determining the second-order stochastic dominance efficient set.

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Bibliographic Info

Article provided by Elsevier in its journal European Journal of Operational Research.

Volume (Year): 200 (2010)
Issue (Month): 3 (February)
Pages: 893-900

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Handle: RePEc:eee:ejores:v:200:y:2010:i:3:p:893-900

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Web page: http://www.elsevier.com/locate/eor

Related research

Keywords: Majorization Stochastic dominance Portfolio selection Expected utility Diversification;

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Citations

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Cited by:
  1. Hooi Hooi Lean & Michael McAleer & Wing-Keung Wong, 2010. "Investor Preferences for Oil Spot and Futures Based on Mean-Variance and Stochastic Dominance," CARF F-Series CARF-F-220, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
  2. Leung, Pui-Lam & Ng, Hon-Yip & Wong, Wing-Keung, 2012. "An improved estimation to make Markowitz’s portfolio optimization theory users friendly and estimation accurate with application on the US stock market investment," European Journal of Operational Research, Elsevier, vol. 222(1), pages 85-95.
  3. Guorui Bian & Michael McAleer & Wing-Keung Wong, 2013. "Robust Estimation and Forecasting of the Capital Asset Pricing Model," Tinbergen Institute Discussion Papers 13-036/III, Tinbergen Institute.
  4. Bai, Zhidong & Phoon, Kok Fai & Wang, Keyan & Wong, Wing-Keung, 2013. "The performance of commodity trading advisors: A mean-variance-ratio test approach," The North American Journal of Economics and Finance, Elsevier, vol. 25(C), pages 188-201.
  5. Hooi Hooi Lean & Michael McAleer & Wing-Keung Wong, 2010. "Market Efficiency of Oil Spot and Futures: A Mean-Variance and Stochastic Dominance Approach," Working Papers in Economics 10/18, University of Canterbury, Department of Economics and Finance.
  6. Zhidong Bai & Hua Li & Michael McAleer & Wing-Keung Wong, 2012. "Stochastic Dominance Statistics for Risk Averters and Risk Seekers: An Analysis of Stock Preferences for USA and China," Documentos de Trabajo del ICAE 2012-13, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
  7. Bai, Zhidong & Wang, Keyan & Wong, Wing-Keung, 2011. "The mean-variance ratio test--A complement to the coefficient of variation test and the Sharpe ratio test," Statistics & Probability Letters, Elsevier, vol. 81(8), pages 1078-1085, August.
  8. Alessandra Cillo & Philippe Delquié, 2013. "Mean-Risk Analysis with Enhanced Behavioral Content," Working Papers 498, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
  9. Guo, Xu & Lam, Kin & Wong, Wing-Keung & Zhu, Lixing, 2012. "A New Pseudo-Bayesian Model of Investors' Behavior in Financial Crises," MPRA Paper 42535, University Library of Munich, Germany.
  10. Bai, Zhidong & Li, Hua & Wong, Wing-Keung, 2013. "The best estimation for high-dimensional Markowitz mean-variance optimization," MPRA Paper 43862, University Library of Munich, Germany.
  11. Eric S. Fung & Kin Lam & Tak-Kuen Siu & Wing-Keung Wong, 2011. "A Pseudo-Bayesian Model for Stock Returns In Financial Crises," Journal of Risk and Financial Management, MDPI, Open Access Journal, vol. 4(1), pages 43-73, December.
  12. Broll, Udo & Wong, Wing-Keung & Wu, Mojia, 2013. "Banking Firm and Two-Moment Decision Making," MPRA Paper 51687, University Library of Munich, Germany.

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