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Stochastic Dominance Statistics for Risk Averters and Risk Seekers: An Analysis of Stock Preferences for USA and China

  • Zhidong Bai

    (KLASMOE and School of Mathematics and Statistics, Northeast Normal University, Department of Statistics and Applied Probability and Risk Management Institute, National University of Singapore)

  • Hua Li

    (Department of Statistics and Applied Probability, National University of Singapore)

  • Michael McAleer

    (Econometric Institute, Erasmus School of Economics, Erasmus University Rotterdam and Tinbergen Institute, The Netherlands, Department of Quantitative Economics, Complutense University of Madrid, and Institute of Economic Research, Kyoto University.)

  • Wing-Keung Wong

    (Department of Economics, Hong Kong Baptist University)

We derive the limiting process of the stochastic dominance statistics for risk averters as well as for risk seekers when the underlying processes might be dependent or independent. We take account of the dependency of the partitions and propose a bootstrap method to decide the critical point. In addition, we illustrate the applicability of the stochastic dominance statistics for both risk averters and risk seekers to analyze the dominance relationship between the Chinese and US stock markets in the entire period as well as the sub-periods before and after the ¯nancial crises, including the internet bubble and the recent sub-prime crisis. The ¯ndings could be used to draw inferences on the preferences of risk averters and risk seekers in investing in the Chinese and US stock markets. The results also enable us to examine whether there is any arbitrage opportunity in these markets and whether these markets are e±cient and investors are rational.

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File URL: http://eprints.ucm.es/15556/1/1213.pdf
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Paper provided by Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico in its series Documentos de Trabajo del ICAE with number 2012-13.

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Length: 42 pages
Date of creation: Jun 2012
Date of revision:
Handle: RePEc:ucm:doicae:1213
Note: Acknowledgments: This research is partially supported by Northeast Normal University, National University of Singapore, Research Grants Council of Hong Kong, and Hong Kong Baptist University. The third author wishes to acknowledge the ¯nancial support of the Australian Research Council, National Science Council, Taiwan, and the Japan Society for the Promotion of Science. The fourth author would like to thank Professors Robert B. Miller and Howard E. Thompson for their continuous guidance and encouragement.
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  1. Sugato Chakravarty & Asani Sarkar & Lifan Wu, 1998. "Information asymmetry, market segmentation, and the pricing of cross-listed shares: theory and evidence from Chinese A and B shares," Research Paper 9820, Federal Reserve Bank of New York.
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  3. Oliver Linton & Esfandiar Maasoumi & Yoon-Jae Whang, 2003. "Consistent testing for stochastic dominance under general sampling schemes," LSE Research Online Documents on Economics 2208, London School of Economics and Political Science, LSE Library.
  4. Egozcue, Martín & García, Luis Fuentes & Wong, Wing-Keung & Zitikis, Ricardas, 2011. "Do investors like to diversify? A study of Markowitz preferences," European Journal of Operational Research, Elsevier, vol. 215(1), pages 188-193, November.
  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. Dominic Gasbarro & Wing-Keung Wong & J. Kenton Zumwalt, 2007. "Stochastic Dominance Analysis of iShares," Finance Working Papers 21919, East Asian Bureau of Economic Research.
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  8. Egozcue, Martin & Wong, Wing-Keung, 2010. "Gains from diversification on convex combinations: A majorization and stochastic dominance approach," European Journal of Operational Research, Elsevier, vol. 200(3), pages 893-900, February.
  9. Fong, Wai Mun & Wong, Wing Keung & Lean, Hooi Hooi, 2005. "International momentum strategies: a stochastic dominance approach," Journal of Financial Markets, Elsevier, vol. 8(1), pages 89-109, February.
  10. Davidson, R. & Duclos, J.-Y., 1998. "Statistical Inference for Stochastic Dominance and for the Measurement of Poverty and Inequality," G.R.E.Q.A.M. 98a14, Universite Aix-Marseille III.
  11. Lean, H.H. & McAleer, M.J. & Wong, W.K., 2010. "Investor preferences for oil spot and futures based on mean-variance and stochastic dominance," Econometric Institute Research Papers EI 2010-37, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  12. Bishop, John A & Formby, John P & Thistle, Paul D, 1992. "Convergence of the South and Non-South Income Distributions, 1969-1979," American Economic Review, American Economic Association, vol. 82(1), pages 262-72, March.
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  16. Chan, Chia-Ying & de Peretti, Christian & Qiao, Zhuo & Wong, Wing-Keung, 2012. "Empirical test of the efficiency of the UK covered warrants market: Stochastic dominance and likelihood ratio test approach," Journal of Empirical Finance, Elsevier, vol. 19(1), pages 162-174.
  17. Lam, Kin & Liu, Taisheng & Wong, Wing-Keung, 2010. "A pseudo-Bayesian model in financial decision making with implications to market volatility, under- and overreaction," European Journal of Operational Research, Elsevier, vol. 203(1), pages 166-175, May.
  18. Wing-Keung Wong & Chenghu Ma, 2005. "Preferences over Meyer’s Location-Scale Family," Departmental Working Papers wp0506, National University of Singapore, Department of Economics.
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