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Trading volume and exchange rate volatility: Evidence for the sequential arrival of information hypothesis

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  • Mougoué, Mbodja
  • Aggarwal, Raj

Abstract

The relationship between trading volume and volatility in foreign exchange markets continues to be of much interest, especially given the higher than expected volatility of returns. Allowing for nonlinearities, this paper tests competing hypotheses on the possible relationship between volatility and trading volume using data for three major currency futures contracts denominated in US dollars, namely the British pound, the Canadian dollar and the Japanese yen. We find that trading volumes and return volatility are negatively correlated, implying a lack of support for the mixture of distributions hypothesis (MDH). Using linear and nonlinear Granger causality tests, we document significant lead-lag relations between trading volumes and return volatility consistent with the sequential arrival of information (SAI) hypothesis. These findings are robust and not sample-dependent or due to heterogeneity of beliefs as proxied by open interest. Furthermore, our results are insensitive to the modeling approach used to recover volatility measures. Overall, our findings support the contention that short- to medium-term currency relationships may be dominated by trading dynamics and not by fundamentals.

Suggested Citation

  • Mougoué, Mbodja & Aggarwal, Raj, 2011. "Trading volume and exchange rate volatility: Evidence for the sequential arrival of information hypothesis," Journal of Banking & Finance, Elsevier, vol. 35(10), pages 2690-2703, October.
  • Handle: RePEc:eee:jbfina:v:35:y:2011:i:10:p:2690-2703
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    Cited by:

    1. Do, Hung Xuan & Brooks, Robert & Treepongkaruna, Sirimon & Wu, Eliza, 2014. "How does trading volume affect financial return distributions?," International Review of Financial Analysis, Elsevier, vol. 35(C), pages 190-206.
    2. Antonakakis, Nikolaos & Floros, Christos & Kizys, Renatas, 2016. "Dynamic spillover effects in futures markets: UK and US evidence," International Review of Financial Analysis, Elsevier, vol. 48(C), pages 406-418.
    3. repec:eee:ecmode:v:69:y:2018:i:c:p:127-133 is not listed on IDEAS
    4. Antonakakis, Nikolaos & Kizys, Renatas & Floros, Christos, 2014. "Dynamic Spillover Effects in Futures Markets," MPRA Paper 53876, University Library of Munich, Germany.
    5. Fredj Jawadi & Waël Louhichi & Abdoulkarim Idi Cheffou & Rivo Randrianarivony, 2016. "Intraday jumps and trading volume: a nonlinear Tobit specification," Review of Quantitative Finance and Accounting, Springer, vol. 47(4), pages 1167-1186, November.
    6. Damette, Olivier, 2016. "Mixture Distribution Hypothesis And The Impact Of A Tobin Tax On Exchange Rate Volatility: A Reassessment," Macroeconomic Dynamics, Cambridge University Press, vol. 20(06), pages 1600-1622, September.
    7. Kumar, Satish, 2017. "On the nonlinear relation between crude oil and gold," Resources Policy, Elsevier, vol. 51(C), pages 219-224.
    8. Fethi Belhaj & Ezzeddine Abaoub, 2015. "A Generalized Autoregressive Conditional Heteroskedasticity Examination of the Relationship between Trading Volume and Conditional Volatility in the Tunisian Stock Market: Evidence for the Information," International Journal of Economics and Financial Issues, Econjournals, vol. 5(2), pages 354-364.
    9. Jawadi Fredj & Ureche-Rangau Loredana, 2013. "Threshold linkages between volatility and trading volume: evidence from developed and emerging markets," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(3), pages 313-333, May.

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