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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

    (Erasmus University Rotterdam,Tinbergen Institute,Kyoto University,Complutense University of Madrid)

  • 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://www.kier.kyoto-u.ac.jp/DP/DP820.pdf
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Paper provided by Kyoto University, Institute of Economic Research in its series KIER Working Papers with number 820.

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Date of creation: Jun 2012
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Handle: RePEc:kyo:wpaper:820
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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. Hooi Hooi Lean & Michael McAleer & Wing-Keung Wong, 2011. "Investor Preferences for Oil Spot and Futures based on Mean-Variance and Stochastic Dominance," KIER Working Papers 755, Kyoto University, Institute of Economic Research.
  4. 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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  7. 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.
  8. 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.
  9. Schechtman, Edna & Shelef, Amit & Yitzhaki, Shlomo & Zitikis, Ričardas, 2008. "Testing Hypotheses About Absolute Concentration Curves And Marginal Conditional Stochastic Dominance," Econometric Theory, Cambridge University Press, vol. 24(04), pages 1044-1062, August.
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  18. 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.
  19. Harry Markowitz, 1952. "The Utility of Wealth," Journal of Political Economy, University of Chicago Press, vol. 60, pages 151.
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  22. 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.
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