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Stock Market Autoregressive Dynamics: A Multinational Comparative Study with Quantile Regression

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  • Lili Li
  • Shan Leng
  • Jun Yang
  • Mei Yu

Abstract

We study the nonlinear autoregressive dynamics of stock index returns in seven major advanced economies (G7) and China. The quantile autoregression model (QAR) enables us to investigate the autocorrelation across the whole spectrum of return distribution, which provides more insightful conditional information on multinational stock market dynamics than conventional time series models. The relation between index return and contemporaneous trading volume is also investigated. While prior studies have mixed results on stock market autocorrelations, we find that the dynamics is usually state dependent. The results for G7 stock markets exhibit conspicuous similarities, but they are in manifest contrast to the findings on Chinese stock markets.

Suggested Citation

  • Lili Li & Shan Leng & Jun Yang & Mei Yu, 2016. "Stock Market Autoregressive Dynamics: A Multinational Comparative Study with Quantile Regression," Mathematical Problems in Engineering, Hindawi, vol. 2016, pages 1-15, September.
    • Handle: RePEc:hin:jnlmpe:1285768
    DOI: 10.1155/2016/1285768
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    as
    1. Chong, Terence Tai-Leung & Lam, Tau-Hing & Yan, Isabel Kit-Ming, 2012. "Is the Chinese stock market really inefficient?," China Economic Review, Elsevier, vol. 23(1), pages 122-137.
    2. John Y. Campbell & Sanford J. Grossman & Jiang Wang, 1993. "Trading Volume and Serial Correlation in Stock Returns," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 108(4), pages 905-939.
    3. Koenker, Roger & Xiao, Zhijie, 2006. "Quantile Autoregression," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 980-990, September.
    4. Chang, Eric C. & Luo, Yan & Ren, Jinjuan, 2014. "Short-selling, margin-trading, and price efficiency: Evidence from the Chinese market," Journal of Banking & Finance, Elsevier, vol. 48(C), pages 411-424.
    5. Morgan, I G, 1976. "Stock Prices and Heteroscedasticity," The Journal of Business, University of Chicago Press, vol. 49(4), pages 496-508, October.
    6. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    7. Baur, Dirk G. & Dimpfl, Thomas & Jung, Robert C., 2012. "Stock return autocorrelations revisited: A quantile regression approach," Journal of Empirical Finance, Elsevier, vol. 19(2), pages 254-265.
    8. Bissoondoyal-Bheenick, Emawtee & Brooks, Robert D., 2010. "Does volume help in predicting stock returns? An analysis of the Australian market," Research in International Business and Finance, Elsevier, vol. 24(2), pages 146-157, June.
    9. Gebka, Bartosz & Wohar, Mark E., 2013. "Causality between trading volume and returns: Evidence from quantile regressions," International Review of Economics & Finance, Elsevier, vol. 27(C), pages 144-159.
    10. Michael D. McKenzie & Robert W. Faff, 2003. "The Determinants of Conditional Autocorrelation in Stock Returns," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 26(2), pages 259-274, June.
    11. M. F. M. Osborne, 1959. "Brownian Motion in the Stock Market," Operations Research, INFORMS, vol. 7(2), pages 145-173, April.
    12. Baur, Dirk G., 2013. "The structure and degree of dependence: A quantile regression approach," Journal of Banking & Finance, Elsevier, vol. 37(3), pages 786-798.
    13. Guillermo Llorente & Roni Michaely & Gideon Saar & Jiang Wang, 2002. "Dynamic Volume-Return Relation of Individual Stocks," The Review of Financial Studies, Society for Financial Studies, vol. 15(4), pages 1005-1047.
    14. Chiang, Thomas C. & Zheng, Dazhi, 2010. "An empirical analysis of herd behavior in global stock markets," Journal of Banking & Finance, Elsevier, vol. 34(8), pages 1911-1921, August.
    15. McQueen, Grant & Pinegar, Michael & Thorley, Steven, 1996. "Delayed Reaction to Good News and the Cross-Autocorrelation of Portfolio Returns," Journal of Finance, American Finance Association, vol. 51(3), pages 889-919, July.
    16. Chuangxia Huang & Xu Gong & Xiaohong Chen & Fenghua Wen, 2013. "Measuring and Forecasting Volatility in Chinese Stock Market Using HAR-CJ-M Model," Abstract and Applied Analysis, Hindawi, vol. 2013, pages 1-13, March.
    17. Zhu, Hui-Ming & Li, ZhaoLai & You, WanHai & Zeng, Zhaofa, 2015. "Revisiting the asymmetric dynamic dependence of stock returns: Evidence from a quantile autoregression model," International Review of Financial Analysis, Elsevier, vol. 40(C), pages 142-153.
    18. Karpoff, Jonathan M., 1987. "The Relation between Price Changes and Trading Volume: A Survey," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 22(1), pages 109-126, March.
    19. Lee, Cheng F & Rui, Oliver M, 2000. "Does Trading Volume Contain Information to Predict Stock Returns? Evidence from China's Stock Markets," Review of Quantitative Finance and Accounting, Springer, vol. 14(4), pages 341-360, June.
    20. Yao, Juan & Ma, Chuanchan & He, William Peng, 2014. "Investor herding behaviour of Chinese stock market," International Review of Economics & Finance, Elsevier, vol. 29(C), pages 12-29.
    21. Chiang, Thomas C. & Li, Jiandong & Tan, Lin, 2010. "Empirical investigation of herding behavior in Chinese stock markets: Evidence from quantile regression analysis," Global Finance Journal, Elsevier, vol. 21(1), pages 111-124.
    22. Gębka, Bartosz & Wohar, Mark E., 2013. "The determinants of quantile autocorrelations: Evidence from the UK," International Review of Financial Analysis, Elsevier, vol. 29(C), pages 51-61.
    23. Lo, Andrew W. & Craig MacKinlay, A., 1990. "An econometric analysis of nonsynchronous trading," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 181-211.
    24. Chuang, Chia-Chang & Kuan, Chung-Ming & Lin, Hsin-Yi, 2009. "Causality in quantiles and dynamic stock return-volume relations," Journal of Banking & Finance, Elsevier, vol. 33(7), pages 1351-1360, July.
    25. Kim, Kenneth & Rhee, S Ghon, 1997. "Price Limit Performance: Evidence from the Tokyo Stock Exchange," Journal of Finance, American Finance Association, vol. 52(2), pages 885-899, June.
    26. Jonathan Lewellen, 2002. "Momentum and Autocorrelation in Stock Returns," The Review of Financial Studies, Society for Financial Studies, vol. 15(2), pages 533-564, March.
    27. Blume, Lawrence & Easley, David & O'Hara, Maureen, 1994. "Market Statistics and Technical Analysis: The Role of Volume," Journal of Finance, American Finance Association, vol. 49(1), pages 153-181, March.
    28. Chen, Gong-meng & Firth, Michael & Rui, Oliver M, 2001. "The Dynamic Relation between Stock Returns, Trading Volume, and Volatility," The Financial Review, Eastern Finance Association, vol. 36(3), pages 153-173, August.
    29. Chuang, Wen-I & Liu, Hsiang-Hsi & Susmel, Rauli, 2012. "The bivariate GARCH approach to investigating the relation between stock returns, trading volume, and return volatility," Global Finance Journal, Elsevier, vol. 23(1), pages 1-15.
    30. Westerfield, Randolph, 1977. "The Distribution of Common Stock Price Changes: An Application of Transactions Time and Subordinated Stochastic Models," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 12(5), pages 743-765, December.
    31. Tan, Lin & Chiang, Thomas C. & Mason, Joseph R. & Nelling, Edward, 2008. "Herding behavior in Chinese stock markets: An examination of A and B shares," Pacific-Basin Finance Journal, Elsevier, vol. 16(1-2), pages 61-77, January.
    32. Kenneth A. Kim & Haixiao Liu & J. Jimmy Yang, 2013. "Reconsidering Price Limit Effectiveness," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 36(4), pages 493-518, December.
    33. Rezvanian, Rasoul & Turk, Rima A. & Mehdian, Seyed M., 2011. "Investors' reactions to sharp price changes: Evidence from equity markets of the People's Republic of China," Global Finance Journal, Elsevier, vol. 22(1), pages 1-18.
    34. Chen, Shiu-Sheng, 2012. "Revisiting the empirical linkages between stock returns and trading volume," Journal of Banking & Finance, Elsevier, vol. 36(6), pages 1781-1788.
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