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Dynamic relationship between trading volume, returns and returns volatility: an empirical investigation on the main African’s stock markets

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  • Daouda Lawa tan Toe

    (University Thomas SANKARA (UTS))

  • Salifou Ouedraogo

    (University Thomas SANKARA (UTS))

Abstract

In this empirical investigation, we examine the relationship between trading volume, return and volatility for eleven African Stock Exchanges. This study covers the period from September 24, 2010 to September 24, 2020, i.e., a total of 3037 daily observations per country. The relationship between trading volume and return is examined using the Granger causality test. For the relationship between trading volume and returns volatility, we use an asymmetric EGARCH (1, 1) model. The results indicate that returns do not cause volume while volume causes return in some countries’ Stock Exchanges. Regarding the volatility of the daily return, the study shows on the one hand that the persistence in the volatility is low and the trading volume increases this persistence on the majority of Stock Exchanges. On the other hand, lag trading volume affects the daily volatility of the markets.

Suggested Citation

  • Daouda Lawa tan Toe & Salifou Ouedraogo, 2022. "Dynamic relationship between trading volume, returns and returns volatility: an empirical investigation on the main African’s stock markets," Journal of Asset Management, Palgrave Macmillan, vol. 23(5), pages 429-444, September.
    • Handle: RePEc:pal:assmgt:v:23:y:2022:i:5:d:10.1057_s41260-022-00274-0
    DOI: 10.1057/s41260-022-00274-0
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    1. Simon Gervais & Ron Kaniel & Dan H. Mingelgrin, 2001. "The High‐Volume Return Premium," Journal of Finance, American Finance Association, vol. 56(3), pages 877-919, June.
    2. Komain Jiranyakul, 2016. "Causal linkages between electricity consumption and GDP in Thailand: evidence from the bounds test," Economics Bulletin, AccessEcon, vol. 36(2), pages 921-930.
    3. Lamoureux, Christopher G & Lastrapes, William D, 1990. "Heteroskedasticity in Stock Return Data: Volume versus GARCH Effects," Journal of Finance, American Finance Association, vol. 45(1), pages 221-229, March.
    4. Andrey Kudryavtsev, 2017. "The Effect of Preceding Sequences on Stock Returns," European Financial and Accounting Journal, Prague University of Economics and Business, vol. 2017(4), pages 83-96.
    5. Miller, Edward M, 1977. "Risk, Uncertainty, and Divergence of Opinion," Journal of Finance, American Finance Association, vol. 32(4), pages 1151-1168, September.
    6. Pramod Kumar Naik & Puja Padhi, 2014. "Equity Trading Volume and its Relationship with Market Volatility: Evidence from Indian Equity Market," Journal of Asian Business Strategy, Asian Economic and Social Society, vol. 4(9), pages 108-124, September.
    7. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    8. Shekar Bose & Hafizur Rahman, 2015. "Examining the relationship between stock return volatility and trading volume: new evidence from an emerging economy," Applied Economics, Taylor & Francis Journals, vol. 47(18), pages 1899-1908, April.
    9. Anirut Pisedtasalasai & Abeyratna Gunasekarage, 2007. "Causal and Dynamic Relationships among Stock Returns, Return Volatility and Trading Volume: Evidence from Emerging markets in South-East Asia," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 14(4), pages 277-297, December.
    10. Giampiero Gallo & Barbara Pacini, 2000. "The effects of trading activity on market volatility," The European Journal of Finance, Taylor & Francis Journals, vol. 6(2), pages 163-175.
    11. Bradford Cornell, 1981. "The relationship between volume and price variability in futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 1(3), pages 303-316, September.
    12. 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.
    13. Pagan, Adrian R. & Schwert, G. William, 1990. "Alternative models for conditional stock volatility," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 267-290.
    14. Foster, F Douglas & Viswanathan, S, 1995. "Can Speculative Trading Explain the Volume-Volatility Relation?," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(4), pages 379-396, October.
    15. Meir Statman & Steven Thorley & Keith Vorkink, 2006. "Investor Overconfidence and Trading Volume," The Review of Financial Studies, Society for Financial Studies, vol. 19(4), pages 1531-1565.
    16. Hsin-Yi Lin, 2013. "Dynamic Stock Return–Volume Relation: Evidence From Emerging Asian Markets," Bulletin of Economic Research, Wiley Blackwell, vol. 65(2), pages 178-193, April.
    17. 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.
    18. Ding, David K. & McInish, Thomas H. & Wongchoti, Udomsak, 2008. "Behavioral explanations of trading volume and short-horizon price patterns: An investigation of seven Asia-Pacific markets," Pacific-Basin Finance Journal, Elsevier, vol. 16(3), pages 183-203, June.
    19. Clark, Peter K, 1973. "A Subordinated Stochastic Process Model with Finite Variance for Speculative Prices," Econometrica, Econometric Society, vol. 41(1), pages 135-155, January.
    20. Kumar, Brajesh & Singh, Priyanka & Pandey, Ajay, 2009. "The Dynamic Relationship between Price and Trading Volume:Evidence from Indian Stock Market," IIMA Working Papers WP2009-12-04, Indian Institute of Management Ahmedabad, Research and Publication Department.
    21. 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.
    22. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    23. Pramod Kumar Naik & Puja Padhi, 2014. "Equity Trading Volume and its Relationship with Market Volatility: Evidence from Indian Equity Market," Journal of Asian Business Strategy, Asian Economic and Social Society, vol. 4(9), pages 108-124.
    24. Rachael Carroll & Colm Kearney, 2012. "Do trading volumes explain the persistence of GARCH effects?," Applied Financial Economics, Taylor & Francis Journals, vol. 22(23), pages 1993-2008, December.
    25. Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, vol. 37(3), pages 424-438, July.
    26. Mohammad Majand & Kenneth Yung, 1991. "A GARCH examination of the relationship between volume and price variability in futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 11(5), pages 613-621, October.
    27. Allaudeen Hameed & Yuanto Kusnadi, 2002. "Momentum Strategies: Evidence from Pacific Basin Stock Markets," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 25(3), pages 383-397, September.
    28. Andrey Kudryavtsev, 2017. "The Effect of Stock Return Sequences on Trading Volumes," IJFS, MDPI, vol. 5(4), pages 1-15, October.
    29. 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.
    30. Mayshar, Joram, 1983. "On Divergence of Opinion and Imperfections in Capital Markets," American Economic Review, American Economic Association, vol. 73(1), pages 114-128, March.
    31. Harris, Lawrence E & Gurel, Eitan, 1986. "Price and Volume Effects Associated with Changes in the S&P 500 List: New Evidence for the Existence of Price Pressures," Journal of Finance, American Finance Association, vol. 41(4), pages 815-829, September.
    32. Jennings, Robert H & Starks, Laura T & Fellingham, John C, 1981. "An Equilibrium Model of Asset Trading with Sequential Information Arrival," Journal of Finance, American Finance Association, vol. 36(1), pages 143-161, March.
    33. G. Caginalp & M. Desantis, 2011. "Stock price dynamics: nonlinear trend, volume, volatility, resistance and money supply," Quantitative Finance, Taylor & Francis Journals, vol. 11(6), pages 849-861.
    34. Copeland, Thomas E, 1976. "A Model of Asset Trading under the Assumption of Sequential Information Arrival," Journal of Finance, American Finance Association, vol. 31(4), pages 1149-1168, September.
    35. Andersen, Torben G, 1996. "Return Volatility and Trading Volume: An Information Flow Interpretation of Stochastic Volatility," Journal of Finance, American Finance Association, vol. 51(1), pages 169-204, March.
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    More about this item

    Keywords

    Trading volume; Volatility; EGARCH model; Granger causality test;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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