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A Direct Test of the Mixture of Distributions Hypothesis: Measuring the Daily Flow of Information

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  • Richardson, Matthew
  • Smith, Tom
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    File URL: http://journals.cambridge.org/abstract_S0022109000008814
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    Bibliographic Info

    Article provided by Cambridge University Press in its journal Journal of Financial and Quantitative Analysis.

    Volume (Year): 29 (1994)
    Issue (Month): 01 (March)
    Pages: 101-116

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    Handle: RePEc:cup:jfinqa:v:29:y:1994:i:01:p:101-116_00

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    Cited by:
    1. Wu, Chunchi, 2004. "Information flow, volatility and spreads of infrequently traded Nasdaq stocks," The Quarterly Review of Economics and Finance, Elsevier, vol. 44(1), pages 20-43, February.
    2. repec:lan:wpaper:3326 is not listed on IDEAS
    3. Joel Hasbrouck, 1999. "Trading Fast and Slow: Security Market Events in Real Time," New York University, Leonard N. Stern School Finance Department Working Paper Seires 99-012, New York University, Leonard N. Stern School of Business-.
    4. Ainhoa Zarraga, 2003. "GMM-based testing procedures of the mixture of distributions model," Applied Financial Economics, Taylor & Francis Journals, vol. 13(11), pages 841-848.
    5. Jondeau, E. & Rockinger, M., 2002. "Asset Allocation in Transition Economies," Working papers 90, Banque de France.
    6. repec:lan:wpaper:3048 is not listed on IDEAS
    7. repec:lan:wpaper:3142 is not listed on IDEAS
    8. Geman, Hélyette, 2005. "From measure changes to time changes in asset pricing," Journal of Banking & Finance, Elsevier, vol. 29(11), pages 2701-2722, November.
    9. Park, Beum-Jo, 2010. "Surprising information, the MDH, and the relationship between volatility and trading volume," Journal of Financial Markets, Elsevier, vol. 13(3), pages 344-366, August.
    10. Rubin, Amir & Smith, Daniel R., 2011. "Comparing different explanations of the volatility trend," Journal of Banking & Finance, Elsevier, vol. 35(6), pages 1581-1597, June.
    11. Taylor, Nicholas, 2008. "Can idiosyncratic volatility help forecast stock market volatility?," International Journal of Forecasting, Elsevier, vol. 24(3), pages 462-479.
    12. Marwan Izzeldin, 2007. "Trading volume and the number of trades: a comparative study using high frequency data," Working Papers 584864, Lancaster University Management School, Economics Department.
    13. Jondeau, Eric & Rockinger, Michael, 2001. "Gram-Charlier densities," Journal of Economic Dynamics and Control, Elsevier, vol. 25(10), pages 1457-1483, October.
    14. repec:lan:wpaper:3050 is not listed on IDEAS
    15. Su, Dongwei & Fleisher, Belton M., 1999. "Why does return volatility differ in Chinese stock markets?," Pacific-Basin Finance Journal, Elsevier, vol. 7(5), pages 557-586, December.
    16. Liesenfeld, Roman, 2001. "A generalized bivariate mixture model for stock price volatility and trading volume," Journal of Econometrics, Elsevier, vol. 104(1), pages 141-178, August.
    17. Aki-Hiro Sato & Takaki Hayashi & Janusz Hołyst, 2012. "Comprehensive analysis of market conditions in the foreign exchange market," Journal of Economic Interaction and Coordination, Springer, vol. 7(2), pages 167-179, October.
    18. Elena Kalotychou & Sotiris Staikouras, 2006. "Volatility and trading activity in Short Sterling futures," Applied Economics, Taylor & Francis Journals, vol. 38(9), pages 997-1005.
    19. Serge Darolles & Gaëlle Le Fol & Gulten Mero, 2010. "When Market Illiquidity Generates Volumes," Working Papers halshs-00536046, HAL.
    20. Kalev, Petko S. & Liu, Wai-Man & Pham, Peter K. & Jarnecic, Elvis, 2004. "Public information arrival and volatility of intraday stock returns," Journal of Banking & Finance, Elsevier, vol. 28(6), pages 1441-1467, June.
    21. Goodhart, Charles A. E. & O'Hara, Maureen, 1997. "High frequency data in financial markets: Issues and applications," Journal of Empirical Finance, Elsevier, vol. 4(2-3), pages 73-114, June.

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