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Turning Over Turnover

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  • Martijn Cremers
  • Jianping Mei

Abstract

This paper applies the methodology of Bai and Ng (2002, 2004) for decomposing large panel data into systematic and idiosyncratic components to both returns and turnover. Combining the methodology with a generalized-least-squares-based principal components procedure, we demonstrate that this approach works well for both returns and turnover despite the presence of severe heteroscedasticity and non-stationarity in turnover of individual stocks. We then test the duo-factor model of Lo and Wang's (2000), which is based on mutual fund separation. Our results indicate that trading due to systematic risk in returns can account for as much as 73% of all systematic turnover variation in the weekly time-series and 76% in

Suggested Citation

  • Martijn Cremers & Jianping Mei, 2004. "Turning Over Turnover," Yale School of Management Working Papers ysm429, Yale School of Management, revised 01 May 2008.
  • Handle: RePEc:ysm:somwrk:ysm429
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    File URL: http://icfpub.som.yale.edu/publications/2664
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    Cited by:

    1. Ľuboš Pástor & Robert F. Stambaugh & Lucian A. Taylor, 2017. "Do Funds Make More When They Trade More?," Journal of Finance, American Finance Association, vol. 72(4), pages 1483-1528, August.
    2. Perez, M. Fabricio & Shkilko, Andriy & Sokolov, Konstantin, 2015. "Factor models for binary financial data," Journal of Banking & Finance, Elsevier, vol. 61(S2), pages 177-188.
    3. Rossi, Francesco, 2011. "U.K. cross-sectional equity data: do not trust the dataset! The case for robust investability filters," MPRA Paper 38303, University Library of Munich, Germany, revised Nov 2011.
    4. Edelen, Roger M. & Kadlec, Gregory B., 2012. "Delegated trading and the speed of adjustment in security prices," Journal of Financial Economics, Elsevier, vol. 103(2), pages 294-307.
    5. Andrade, Sandro C. & Bian, Jiangze & Burch, Timothy R., 2013. "Analyst Coverage, Information, and Bubbles," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 48(05), pages 1573-1605, October.
    6. Min Hwang & John Quigley, 2010. "Housing Price Dynamics in Time and Space: Predictability, Liquidity and Investor Returns," The Journal of Real Estate Finance and Economics, Springer, vol. 41(1), pages 3-23, July.
    7. Rossi, Francesco, 2012. "UK cross-sectional equity data: The case for robust investability filters," European Economic Letters, European Economics Letters Group, vol. 1(1), pages 6-13.
    8. Rossi, Francesco, 2011. "Risk components in UK cross-sectional equities: evidence of regimes and overstated parametric estimates," MPRA Paper 38682, University Library of Munich, Germany, revised 31 Mar 2012.
    9. Aragon, George O. & Dieckmann, Stephan, 2011. "Stock market trading activity and returns around milestones," Journal of Empirical Finance, Elsevier, vol. 18(4), pages 570-584, September.

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