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Stochastic Volatility, Trading Volume, and the Daily Flow of Information

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Author Info

  • Jeff Fleming

    (Rice University)

  • Chris Kirby

    (Clemson University)

  • Barbara Ostdiek

    (Rice University)

Abstract

We use state-space methods to investigate the relation between volume, volatility, and ARCH effects within a mixture of distributions hypothesis (MDH) framework. Most recent studies of the MDH fit AR(1) specifications that require the information flow to be highly persistent. Using a more general specification, we find evidence of a large nonpersistent component of volatility that is closely related to the contemporaneous nonpersistent component of volume. However, in contrast to studies that fit volume-augmented GARCH models, we find no evidence that volume subsumes ARCH effects. Since volume-augmented GARCH models are subject to simultaneity bias, our findings should be more robust than these prior results.

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Bibliographic Info

Article provided by University of Chicago Press in its journal Journal of Business.

Volume (Year): 79 (2006)
Issue (Month): 3 (May)
Pages: 1551-1590

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Handle: RePEc:ucp:jnlbus:v:79:y:2006:i:3:p:1551-1590

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Cited by:
  1. Li, Ziran & Sun, Jiajing & Wang, Shouyang, 2013. "Amplitude-Duration-Persistence Trade-off Relationship for Long Term Bear Stock Markets," MPRA Paper 54177, University Library of Munich, Germany.
  2. Chang, Yoosoon & Isaac Miller, J. & Park, Joon Y., 2009. "Extracting a common stochastic trend: Theory with some applications," Journal of Econometrics, Elsevier, vol. 150(2), pages 231-247, June.
  3. Shimokawa, Tetsuya & Suzuki, Kyoko & Misawa, Tadanobu, 2007. "An agent-based approach to financial stylized facts," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 379(1), pages 207-225.
  4. Loredana Ureche-Rangau & Fabien Collado & Ulysse Galiay, 2011. "The dynamics of the volatility – trading volume relationship: New evidence from developed and emerging markets," Economics Bulletin, AccessEcon, vol. 31(3), pages 2569-2583.
  5. Fleming, Jeff & Kirby, Chris, 2011. "Long memory in volatility and trading volume," Journal of Banking & Finance, Elsevier, vol. 35(7), pages 1714-1726, July.
  6. 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.
  7. Zhang, Yongjie & Feng, Lina & Jin, Xi & Shen, Dehua & Xiong, Xiong & Zhang, Wei, 2014. "Internet information arrival and volatility of SME PRICE INDEX," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 399(C), pages 70-74.
  8. Farag, Hisham & Cressy, Robert, 2011. "Do regulatory policies affect the flow of information in emerging markets?," Research in International Business and Finance, Elsevier, vol. 25(3), pages 238-254, September.
  9. Eduardo Rossi & Paolo Santucci de Magistris, 2009. "Long Memory and Tail dependence in Trading Volume and Volatility," CREATES Research Papers 2009-30, School of Economics and Management, University of Aarhus.
  10. Ai-ru (Meg) Cheng & Yin-Wong Cheung, 2008. "Return, Trading Volume, and Market Depth in Currency Futures Markets," Working Papers 202008, Hong Kong Institute for Monetary Research.
  11. Matthew Pritsker, 2005. "Large investors: implications for equilibrium asset, returns, shock absorption, and liquidity," Finance and Economics Discussion Series 2005-36, Board of Governors of the Federal Reserve System (U.S.).
  12. J. Isaac Miller & Yoosoon Chang & Joon Y. Park, 2005. "Extracting a Common Stochastic Trend:Theories with Some Applications," Working Papers 0507, Department of Economics, University of Missouri, revised 18 Aug 2005.
  13. Asai, Manabu & Brugal, Ivan, 2013. "Forecasting volatility via stock return, range, trading volume and spillover effects: The case of Brazil," The North American Journal of Economics and Finance, Elsevier, vol. 25(C), pages 202-213.
  14. Wai Fong & Wing Wong, 2006. "The modified mixture of distributions model: a revisit," Annals of Finance, Springer, vol. 2(2), pages 167-178, March.
  15. Ho, Kin-Yip & Zheng, Lin & Zhang, Zhaoyong, 2012. "Volume, volatility and information linkages in the stock and option markets," Review of Financial Economics, Elsevier, vol. 21(4), pages 168-174.
  16. 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.
  17. Sin, Chor-Yiu (CY), 2013. "Using CARRX models to study factors affecting the volatilities of Asian equity markets," The North American Journal of Economics and Finance, Elsevier, vol. 26(C), pages 552-564.
  18. Amir Rubin & Daniel Smith, 2010. "Comparing Different Explanations of the Volatility Trend," NCER Working Paper Series 68, National Centre for Econometric Research.

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