IDEAS home Printed from https://ideas.repec.org/a/hin/jnlmpe/1285768.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/MPE/2016/1285768.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/MPE/2016/1285768.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2016/1285768?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    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. 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.
    3. M. F. M. Osborne, 1959. "Brownian Motion in the Stock Market," Operations Research, INFORMS, vol. 7(2), pages 145-173, April.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. Morgan, I G, 1976. "Stock Prices and Heteroscedasticity," The Journal of Business, University of Chicago Press, vol. 49(4), pages 496-508, October.
    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. 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.
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. Lo, Andrew W. & Craig MacKinlay, A., 1990. "An econometric analysis of nonsynchronous trading," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 181-211.
    17. 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.
    18. 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.
    19. 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.
    20. 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.
    21. 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.
    22. Koenker, Roger & Xiao, Zhijie, 2006. "Quantile Autoregression," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 980-990, September.
    23. 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.
    24. 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.
    25. 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.
    26. 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.
    27. 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.
    28. 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.
    29. 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.
    30. 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.
    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. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    33. 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.
    34. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Pegah Eslamieh & Mehdi Shajari & Ahmad Nickabadi, 2023. "User2Vec: A Novel Representation for the Information of the Social Networks for Stock Market Prediction Using Convolutional and Recurrent Neural Networks," Mathematics, MDPI, vol. 11(13), pages 1-26, July.
    2. Wentao Xu & Weiqing Liu & Lewen Wang & Yingce Xia & Jiang Bian & Jian Yin & Tie-Yan Liu, 2021. "HIST: A Graph-based Framework for Stock Trend Forecasting via Mining Concept-Oriented Shared Information," Papers 2110.13716, arXiv.org, revised Jan 2022.
    3. Wentao Xu & Weiqing Liu & Chang Xu & Jiang Bian & Jian Yin & Tie-Yan Liu, 2021. "REST: Relational Event-driven Stock Trend Forecasting," Papers 2102.07372, arXiv.org, revised Feb 2021.
    4. Geoffrey M. Ngene & Catherine Anitha Manohar & Ivan F. Julio, 2020. "Overreaction in the REITs Market: New Evidence from Quantile Autoregression Approach," JRFM, MDPI, vol. 13(11), pages 1-28, November.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ngene, Geoffrey M. & Mungai, Ann Nduati, 2022. "Stock returns, trading volume, and volatility: The case of African stock markets," International Review of Financial Analysis, Elsevier, vol. 82(C).
    2. 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.
    3. Abhinava Tripathi, 2021. "The Arrival of Information and Price Adjustment Across Extreme Quantiles: Global Evidence," IIM Kozhikode Society & Management Review, , vol. 10(1), pages 7-19, January.
    4. Ashok Chanabasangouda Patil & Shailesh Rastogi, 2019. "Time-Varying Price–Volume Relationship and Adaptive Market Efficiency: A Survey of the Empirical Literature," JRFM, MDPI, vol. 12(2), pages 1-18, June.
    5. Panpan Wang & Tsungwu Ho & Yishi Li, 2020. "The Price-Volume Relationship of the Shanghai Stock Index: Structural Change and the Threshold Effect of Volatility," Sustainability, MDPI, vol. 12(8), pages 1-17, April.
    6. Hau, Liya & Zhu, Huiming & Shahbaz, Muhammad & Sun, Wuqin, 2021. "Does transaction activity predict Bitcoin returns? Evidence from quantile-on-quantile analysis," The North American Journal of Economics and Finance, Elsevier, vol. 55(C).
    7. Elina Pradkhan, 2016. "Information Content of Trading Activity in Precious Metals Futures Markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 36(5), pages 421-456, May.
    8. Hong Cheng & Yunqing Wang & Yihong Wang & Tinggan Yang, 2022. "Inferring Causal Interactions in Financial Markets Using Conditional Granger Causality Based on Quantile Regression," Computational Economics, Springer;Society for Computational Economics, vol. 59(2), pages 719-748, February.
    9. Park, Jin Suk & Newaz, Mohammad Khaleq, 2021. "Liquidity and short-run predictability: Evidence from international stock markets," Global Finance Journal, Elsevier, vol. 50(C).
    10. 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.
    11. Yamani, Ehab, 2023. "Return–volume nexus in financial markets: A survey of research," Research in International Business and Finance, Elsevier, vol. 65(C).
    12. Wang, Zijun & Qian, Yan & Wang, Shiwen, 2018. "Dynamic trading volume and stock return relation: Does it hold out of sample?," International Review of Financial Analysis, Elsevier, vol. 58(C), pages 195-210.
    13. Marcus Alexander Ong, 2015. "An information theoretic analysis of stock returns, volatility and trading volumes," Applied Economics, Taylor & Francis Journals, vol. 47(36), pages 3891-3906, August.
    14. Sarika Mahajan & Balwinder Singh, 2008. "An Empirical Analysis of Stock Price-Volume Relationship in Indian Stock Market," Vision, , vol. 12(3), pages 1-13, July.
    15. 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.
    16. Gupta, Suman & Das, Debojyoti & Hasim, Haslifah & Tiwari, Aviral Kumar, 2018. "The dynamic relationship between stock returns and trading volume revisited: A MODWT-VAR approach," Finance Research Letters, Elsevier, vol. 27(C), pages 91-98.
    17. 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.
    18. Xiangmei Fan & Yanrui Wu & Nicolaas Groenewold, 2003. "The Stock Return-volume Relation and Policy Effects: The Case of the Chinese Energy Sector," Economics Discussion / Working Papers 03-15, The University of Western Australia, Department of Economics.
    19. Nasiri, S. & Bektas, E. & Jafari, G.R., 2018. "The impact of trading volume on the stock market credibility: Bohmian quantum potential approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 1104-1112.
    20. 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.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hin:jnlmpe:1285768. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.