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Dependence between stock returns and investor sentiment in Chinese markets: A copula approach

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Abstract

Using data of newly opened stock trading accounts in China as a proxy of investor sentiment index, the authors employ the time-varying copula-GARCH model with Hansen’s skewed Student-t innovations to investigate the dynamic dependence between investor sentiment and stock returns. The empirical findings show that shifts in investor sentiment are asymptotically positively correlated to stock returns in extreme value situations in both A shares market and B shares market in China, that is to say, stock prices will increase (decrease) more when investors become more bullish (bearish). Also, results show that the dependence between investor sentiment and stock returns is time-varying, which means that the traditional Pearson’s correlation based on normal distribution is not enough to describe the relationship between stock market behavior and investor behavior.

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References

  1. J. Treynor, Toward a theory of market value of risky assets. Unpublished manuscript. A final version was published in 1999, in Asset Pricing and Portfolio Performance: Models, Strategy and Performance Metrics, Robert A. Korajczyk (editor) London: Risk Books, 1962.

    Google Scholar 

  2. W. Sharpe, Capital asset prices: A theory of market equilibrium under conditions of risk, Journal of Finance, 1964, 19(3): 425–442.

    MathSciNet  Google Scholar 

  3. J. Lintner, The valuation of risk assets and the selection of risky investments in stock portfolios and capital budgets, The Review of Economics and Statistics, 1965, 47(1): 13–37.

    Article  Google Scholar 

  4. J. Mossin, Equilibrium in a capital asset market, Econometrica, 1966, 34(4): 768–783.

    Article  Google Scholar 

  5. S. A. Ross, The arbitrage theory of capital asset pricing, Journal of Economic Theory, 1976, 13(3): 341–360.

    Article  MathSciNet  Google Scholar 

  6. E. Fama, Efficient capital markets: A review of theory and empirical work, Journal of Finance, 1970, 25(2): 383–417.

    Article  Google Scholar 

  7. D. Kahneman and A. Tversky, Prospect theory: An analysis of decision under risk, Econometrica, 1979, 47(2): 263–291.

    Article  MATH  Google Scholar 

  8. F. Black, Noise, Journal of Finance, 1986, 41(3): 529–543.

    Google Scholar 

  9. J. De Long, A. Shleifer, L. G. Summers, and R. Waldmann, Noise trader risk in financial markets, Journal of Political Economy, 1990, 98(4): 703–738.

    Article  Google Scholar 

  10. N. Barberis, A. Shleifer, and R. Vishny, A model of investor sentiment, Journal of Financial Economics, 1998, 49(3): 307–343.

    Article  Google Scholar 

  11. K. Daniel, D. Hirshleifer and A. Subrahmanyam, Investor psychology and security market underand overreactions, Journal of Finance, 1998, 53(6): 1839–1885.

    Article  Google Scholar 

  12. H. Hong and J. Stein, A unified theory of underreaction, momentum trading, and overreaction in asset markets, Journal of Finance, 1999, 54(6): 2143–2184.

    Article  Google Scholar 

  13. G. W. Brown and M. T. Cliff, Investor sentiment and the near-term stock market, Journal of Empirical Finance, 2004, 11(1): 1–27.

    Article  Google Scholar 

  14. P. Embrechts, A. McNeil, and D. Straumann, Correlation and dependency in risk management: Properties and pitfalls, Working Paper, 1999.

  15. U. Cherubini, E. Luciano and W. Vecchiato, Copula Methods in Finance, John Wiley & Sons, England, 2004.

    MATH  Google Scholar 

  16. A. Patton, Modelling asymmetric exchange rate dependence, International Economic Review, 2006, 47(2): 527–556.

    Article  MathSciNet  Google Scholar 

  17. E. Jondeau and M. Rockinger, The copula-GARCH model for conditional dependencies: An international stock market application, Journal of International Money and Finance, 2006, 25(5): 827–853.

    Article  Google Scholar 

  18. D. Fantazzini, Dynamic copula modeling for value at risk, Frontiers in Finance and Economics, 2008, 5(2): 72–108.

    Google Scholar 

  19. J. Hu, Dependence structures in Chinese and US financial markets: A time-varying conditional copula approach, Applied Financial Economics, 2010, 20(7): 561–583.

    Article  Google Scholar 

  20. A. McNeil, R. Frey, and P. Embrechts, Quantitative Risk Management: Concepts, Techniques and Tools, Princeton University Press, New Jersey, 2005.

    MATH  Google Scholar 

  21. J. Rank, Copulas: from Theory to Applications in Finance, Risk Books, London, 2006.

    Google Scholar 

  22. C. Alexander, Market Risk Analysis, Wiley & Sons, London, 2008.

    Google Scholar 

  23. T. Ane, L. Ureche-Rangau, and C. Labidi-Makni, Time-varying conditional dependence in Chinese stock markets, Applied Financial Economics, 2008, 18(11): 895–916.

    Article  Google Scholar 

  24. M. Barker and J. Wurgler, Investor sentiment in stock market, Journal of Economic Perspectives, 2007, 21(2): 129–151.

    Article  Google Scholar 

  25. R. G. Clarke and M. Statman, Bullish or Bearish, Financial Analysts Journal, 1998, 54(3): 63–72.

    Article  Google Scholar 

  26. K. L. Fisher and M. Statman, Investor sentiment and stock returns, Financial Analysts Journal, 2000, 56(2): 16–23.

    Article  Google Scholar 

  27. A. Sklar, Fonctions de repartition n dimensions et leurs marges, Publications de l’Institut de Statistique de l’Universit de Paris, 1959, 8: 229–231.

    MathSciNet  Google Scholar 

  28. P. M. Morilas, A method to obtain new copulas from a given one, Metrika, 2005, 61(2): 169–184.

    Article  MathSciNet  Google Scholar 

  29. K. Aas, C. Czado, A. Frigessi, and H. Bakken, Pair copula constructions of multiple dependence, Insurance, Mathematics, and Economics, 2009, 44(2): 182–198.

    Article  MathSciNet  MATH  Google Scholar 

  30. R. B. Nelsen, An Introduction to Copula, Springer, New York, 1998.

    Google Scholar 

  31. C. Genest and B. Rmillard, Validity of the parametric bootstrap for goodness-of-fit testing in semiparametric models, Annales de l’Institut Henri Poincar, Probabilits et Statistiques, 2008, 44(6): 1096–1127.

    Article  MATH  Google Scholar 

  32. J. H. Shih and T. A. Louis, Inference on the association parameter in copula models for bivariate survival data, Biometrics, 1995, 51(4): 1384–1399.

    Article  MathSciNet  MATH  Google Scholar 

  33. H. Joe and J. J. Xu, The estimation method of inference functions for margins for multivariate models, Technical Report 166, Department of Statistics, University of British Columbia, 1996.

  34. H. Joe, Multivariate Models and Dependence Concepts, Chapman and Hall, London, 1997.

    MATH  Google Scholar 

  35. D. B. Nelson, Conditional heteroskedasticity in asset returns: A new approach, Econometrica, 1991 59(2): 347–370.

    Article  MathSciNet  MATH  Google Scholar 

  36. T. Bollerslev and J. M. Wooldridge, Quasi-maximum likelihood estimation and inference in dynamic models with time-varying covariances, Econometric Reviews, 1992, 11(2): 143–172.

    Article  MathSciNet  MATH  Google Scholar 

  37. B. E. Hansen, Autoregressive conditional density estimation, International Economic Review, 1994, 35(3): 705–730.

    Article  MATH  Google Scholar 

  38. China Securities Depository and Clearing Corporation Limited, http://www.chinaclear.cn/index.html.

  39. A. Ang and J. Chen, Asymmetric correlations of equity portfolios, Journal of Financial Economics, 2002, 63(3): 443–494.

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Management Sciences, City University of Hong Kong, Hong Kong, China

    Xunfa Lu & Kin Keung Lai

  2. School of Business, University of Science and Technology of China, Hefei, 230026, China

    Xunfa Lu & Liang Liang

Authors
  1. Xunfa Lu
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  2. Kin Keung Lai
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  3. Liang Liang
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Corresponding author

Correspondence to Xunfa Lu.

Additional information

This research is supported by the National Natural Science Foundation of China under Grant No. 70821001.

This paper was recommended for publication by Editor Shouyang WANG.

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Lu, X., Lai, K.K. & Liang, L. Dependence between stock returns and investor sentiment in Chinese markets: A copula approach. J Syst Sci Complex 25, 529–548 (2012). https://doi.org/10.1007/s11424-012-9332-0

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  • DOI: https://doi.org/10.1007/s11424-012-9332-0

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