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Turning Over Turnover

  • Martijn Cremers
  • Jianping Mei

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

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File URL: http://icfpub.som.yale.edu/publications/2664
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Paper provided by Yale School of Management in its series Yale School of Management Working Papers with number ysm429.

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Date of creation: 01 Dec 2004
Date of revision: 01 May 2008
Handle: RePEc:ysm:somwrk:ysm429
Contact details of provider: Web page: http://icf.som.yale.edu/

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  1. Joseph Chen & Harrison Hong & Jeremy C. Stein, 2000. "Forecasting Crashes: Trading Volume, Past Returns and Conditional Skewness in Stock Prices," NBER Working Papers 7687, National Bureau of Economic Research, Inc.
  2. Pástor, Luboš & Stambaugh, Robert F., 2002. "Liquidity Risk and Expected Stock Returns," CEPR Discussion Papers 3494, C.E.P.R. Discussion Papers.
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  5. Guillermo Llorente & Roni Michaely & Gideon Saar & Jiang Wang, 2001. "Dynamic Volume-Return Relation of Individual Stocks," NBER Working Papers 8312, National Bureau of Economic Research, Inc.
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  8. Owen Lamont, . "Earnings and Expected Returns," CRSP working papers 345, Center for Research in Security Prices, Graduate School of Business, University of Chicago.
  9. Simon Gervais & Ron Kaniel & Dan Mingelgrin, . "The High Volume Return Premium," Rodney L. White Center for Financial Research Working Papers 01-99, Wharton School Rodney L. White Center for Financial Research.
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  11. Karpoff, Jonathan M., 1987. "The Relation between Price Changes and Trading Volume: A Survey," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 22(01), pages 109-126, March.
  12. Michaely, Roni & Vila, Jean-Luc, 1996. "Trading Volume with Private Valuation: Evidence from the Ex-dividend Day," Review of Financial Studies, Society for Financial Studies, vol. 9(2), pages 471-509.
  13. Jonathan B. Berk, 2000. "Sorting Out Sorts," Journal of Finance, American Finance Association, vol. 55(1), pages 407-427, 02.
  14. Andrew W. Lo & Jiang Wang, 2001. "Trading Volume: Implications of An Intertemporal Capital Asset Pricing Model," NBER Working Papers 8565, National Bureau of Economic Research, Inc.
  15. Connor, Gregory & Korajczyk, Robert A, 1993. " A Test for the Number of Factors in an Approximate Factor Model," Journal of Finance, American Finance Association, vol. 48(4), pages 1263-91, September.
  16. Fama, Eugene F & French, Kenneth R, 1996. " Multifactor Explanations of Asset Pricing Anomalies," Journal of Finance, American Finance Association, vol. 51(1), pages 55-84, March.
  17. Chordia, Tarun & Roll, Richard & Subrahmanyam, Avanidhar, 2000. "Commonality in liquidity," Journal of Financial Economics, Elsevier, vol. 56(1), pages 3-28, April.
  18. Jose A. Scheinkman & Wei Xiong, 2003. "Overconfidence and Speculative Bubbles," Journal of Political Economy, University of Chicago Press, vol. 111(6), pages 1183-1219, December.
  19. David Easley & Soeren Hvidkjaer & Maureen O'Hara, 2002. "Is Information Risk a Determinant of Asset Returns?," Journal of Finance, American Finance Association, vol. 57(5), pages 2185-2221, October.
  20. Connor, Gregory & Korajczyk, Robert A., 1988. "Risk and return in an equilibrium APT : Application of a new test methodology," Journal of Financial Economics, Elsevier, vol. 21(2), pages 255-289, September.
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