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Return-Volume Dependence and Extremes in International Equity Markets

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  • Wagner, Niklas
  • Marsh, Terry A.

Abstract

This paper reconsiders return-volume dependence for the U.S. and six international equity markets. We contribute to previous work by proposing surprise volume as a new proxy for private information flow and apply extreme value theory in studying dependence for large volume and return, i.e. under situations of market stress. Results from a GARCH-M model indicate that surprise volume is superior in explaining conditional variance and reveals a positive market risk premium. Under conditions of market stress, the return-volume dependence is weaker, albeit mostly significant. The results for the U.S. market are most pronounced in that surprise volume explains ARCH- as well as leverage-effects and, under market stress, the return-volume dependence remains significant and symmetric. For the European and Asian markets, however, the dependence is weaker with asymmetry under market stress, i.e. small minimal returns show lower volume dependence than large maximal returns. We argue that our results are more consistent with a Gennotte and Leland (1990) misinterpretation hypothesis for market crashes than with cascade or behavioral explanations which associate high volume with steep price declines.

Suggested Citation

  • Wagner, Niklas & Marsh, Terry A., 2003. "Return-Volume Dependence and Extremes in International Equity Markets," Research Program in Finance, Working Paper Series qt1z87z922, Research Program in Finance, Institute for Business and Economic Research, UC Berkeley.
    • Handle: RePEc:cdl:rpfina:qt1z87z922
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    Cited by:

    1. Go, You-How & Lau, Wee-Yeap, 2020. "The impact of global financial crisis on informational efficiency: Evidence from price-volume relation in crude palm oil futures market," Journal of Commodity Markets, Elsevier, vol. 17(C).
    2. Razvan Stefanescu & Ramona Dumitriu, 2016. "Contrarian and Momentum Profits during Periods of High Trading Volume preceded by Stock Prices Shocks," Risk in Contemporary Economy, "Dunarea de Jos" University of Galati, Faculty of Economics and Business Administration, pages 378-384.
    3. Bartosz Gębka, 2012. "The Dynamic Relation Between Returns, Trading Volume, And Volatility: Lessons From Spillovers Between Asia And The United States," Bulletin of Economic Research, Wiley Blackwell, vol. 64(1), pages 65-90, January.
    4. Yousaf, Imran & Yarovaya, Larisa, 2022. "The relationship between trading volume, volatility and returns of Non-Fungible Tokens: evidence from a quantile approach," Finance Research Letters, Elsevier, vol. 50(C).
    5. Gebka, Bartosz, 2006. "Leaders and Laggards: International Evidence on Spillovers in Returns, Variance, and Trading Volume," Working Paper Series 2006,1, European University Viadrina Frankfurt (Oder), The Postgraduate Research Programme Capital Markets and Finance in the Enlarged Europe.
    6. Naeem, Muhammad & Bouri, Elie & Boako, Gideon & Roubaud, David, 2020. "Tail dependence in the return-volume of leading cryptocurrencies," Finance Research Letters, Elsevier, vol. 36(C).
    7. Fan, Yunqi & Fu, Hui, 2020. "Institutional investors, selling pressure and crash risk: Evidence from China," Emerging Markets Review, Elsevier, vol. 42(C).
    8. Chan, Stephen & Chu, Jeffrey & Zhang, Yuanyuan & Nadarajah, Saralees, 2022. "An extreme value analysis of the tail relationships between returns and volumes for high frequency cryptocurrencies," Research in International Business and Finance, Elsevier, vol. 59(C).

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