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New evidence on the relation between return volatility and trading volume

Author

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  • Thomas C. Chiang

    (Department of Finance, Drexel University, Philadelphia, PA, USA)

  • Zhuo Qiao

    (Faculty of Business Administration, University of Macau, Macau)

  • Wing-Keung Wong

    (Department of Economics, Hong Kong Baptist University, Hong Kong)

Abstract

In the empirical literature, it has been shown that there exists both linear and non-linear bi-directional causality between trading volumes and return volatility (measured by the square of daily return). We re-examine this claim by using realized volatility as an estimator of the unobserved volatility, adopting a stationary de-trended trading volume, and applying a more recent data sample with robustness tests over time. Our linear Granger causality test shows that there is no causal linear relation running from volume to volatility, but there exists an ambiguous causality for the reverse direction. In contrast, we find strong bi-directional non-linear Granger causality between these two variables. On the basis of the non-linear forecasting modeling technique, this study provides strong evidence to support the sequential information hypothesis and demonstrates that it is useful to use lagged values of trading volume to predict return volatility. Copyright © 2009 John Wiley & Sons, Ltd.

Suggested Citation

  • Thomas C. Chiang & Zhuo Qiao & Wing-Keung Wong, 2010. "New evidence on the relation between return volatility and trading volume," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(5), pages 502-515.
  • Handle: RePEc:jof:jforec:v:29:y:2010:i:5:p:502-515
    DOI: 10.1002/for.1151
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    References listed on IDEAS

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    7. Cathy W. S. Chen & Mike K. P. So & Thomas C. Chiang, 2016. "Evidence of Stock Returns and Abnormal Trading Volume: A Threshold Quantile Regression Approach," The Japanese Economic Review, Springer, vol. 67(1), pages 96-124, March.
    8. Sibel ?EL?K, 2013. "New Evidence on the Relation between Trading Volume and Volatility," Business and Economic Research, Macrothink Institute, vol. 3(1), pages 176-186, June.
    9. Bai, Zhidong & Li, Heng & Wong, Wing-Keung & Zhang, Bingzhi, 2011. "Multivariate causality tests with simulation and application," Statistics & Probability Letters, Elsevier, vol. 81(8), pages 1063-1071, August.
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    11. Owyong, David & Wong, Wing-Keung & Horowitz, Ira, 2015. "Cointegration and causality among the onshore and offshore markets for China's currency," Journal of Asian Economics, Elsevier, vol. 41(C), pages 20-38.
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    13. Souček, Michael & Todorova, Neda, 2013. "Realized volatility transmission between crude oil and equity futures markets: A multivariate HAR approach," Energy Economics, Elsevier, vol. 40(C), pages 586-597.
    14. Ganesh R & Naresh G & Thiyagarajan S, 2020. "Manifesting Overconfidence Bias and Disposition Effect in the Stock Market," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 19(3), pages 257-284, December.
    15. Min Liu & Chien‐Chiang Lee & Wei‐Chong Choo, 2021. "An empirical study on the role of trading volume and data frequency in volatility forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 792-816, August.
    16. Tian, Xiao & Duong, Huu Nhan & Kalev, Petko S., 2019. "Information content of the limit order book for crude oil futures price volatility," Energy Economics, Elsevier, vol. 81(C), pages 584-597.
    17. Rilwan Sakariyahu & Mohamed Sherif & Audrey Paterson & Eleni Chatzivgeri, 2021. "Sentiment‐Apt investors and UK sector returns," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 3321-3351, July.
    18. Chu, Amanda M.Y. & Lv, Zhihui & Wagner, Niklas F. & Wong, Wing-Keung, 2020. "Linear and nonlinear growth determinants: The case of Mongolia and its connection to China," Emerging Markets Review, Elsevier, vol. 43(C).
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