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Investment-Horizon Spillovers

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  • Alexander M. Chinco
  • Mao Ye

Abstract

This paper uses wavelets to decompose each stock’s trading-volume variance into frequency-specific components. We find that stocks dominated by short-run fluctuations in trading volume have abnormal returns that are 1% per month higher than otherwise similar stocks where short-run fluctuations in volume are less important—i.e., stocks with less of a short-run tilt. And, we document that a stock’s short-run tilt can change rapidly from month to month, suggesting that these abnormal returns are not due to some persistent firm characteristic that’s simultaneously adding both short-run fluctuations and long-term risk.

Suggested Citation

  • Alexander M. Chinco & Mao Ye, 2017. "Investment-Horizon Spillovers," NBER Working Papers 23650, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:23650
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    1. Jules van Binsbergen & Michael Brandt & Ralph Koijen, 2012. "On the Timing and Pricing of Dividends," American Economic Review, American Economic Association, vol. 102(4), pages 1596-1618, June.
    2. Acharya, Viral V. & Pedersen, Lasse Heje, 2005. "Asset pricing with liquidity risk," Journal of Financial Economics, Elsevier, vol. 77(2), pages 375-410, August.
    3. Ian Dew-Becker & Stefano Giglio, 2016. "Asset Pricing in the Frequency Domain: Theory and Empirics," The Review of Financial Studies, Society for Financial Studies, vol. 29(8), pages 2029-2068.
    4. Leonid Kogan & Dimitris Papanikolaou & Amit Seru & Noah Stoffman, 2017. "Technological Innovation, Resource Allocation, and Growth," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 132(2), pages 665-712.
    5. Ravi Jagannathan & Yong Wang, 2007. "Lazy Investors, Discretionary Consumption, and the Cross‐Section of Stock Returns," Journal of Finance, American Finance Association, vol. 62(4), pages 1623-1661, August.
    6. Cristina Cella & Andrew Ellul & Mariassunta Giannetti, 2013. "Investors' Horizons and the Amplification of Market Shocks," The Review of Financial Studies, Society for Financial Studies, vol. 26(7), pages 1607-1648.
    7. De Long, J Bradford & Andrei Shleifer & Lawrence H. Summers & Robert J. Waldmann, 1990. "Noise Trader Risk in Financial Markets," Journal of Political Economy, University of Chicago Press, vol. 98(4), pages 703-738, August.
    8. Pastor, Lubos & Stambaugh, Robert F., 2003. "Liquidity Risk and Expected Stock Returns," Journal of Political Economy, University of Chicago Press, vol. 111(3), pages 642-685, June.
    9. Qi Chen & Itay Goldstein & Wei Jiang, 2007. "Price Informativeness and Investment Sensitivity to Stock Price," The Review of Financial Studies, Society for Financial Studies, vol. 20(3), pages 619-650.
    10. Yihui Pan & Tracy Yue Wang & Michael S. Weisbach, 2015. "Learning About CEO Ability and Stock Return Volatility," The Review of Financial Studies, Society for Financial Studies, vol. 28(6), pages 1623-1666.
    11. John Y. Campbell & Sanford J. Grossman & Jiang Wang, 1993. "Trading Volume and Serial Correlation in Stock Returns," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 108(4), pages 905-939.
    12. Lan, Chunhua & Moneta, Fabio & Wermers, Russ, 2018. "Holding Horizon: A New Measure of Active Investment Management," CFR Working Papers 15-06, University of Cologne, Centre for Financial Research (CFR), revised 2018.
    13. Beber, Alessandro & Driessen, Joost & Neuberger, Anthony & Tuijp, Patrick, 2021. "Pricing Liquidity Risk with Heterogeneous Investment Horizons," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 56(2), pages 373-408, March.
    14. Sadka, Ronnie, 2006. "Momentum and post-earnings-announcement drift anomalies: The role of liquidity risk," Journal of Financial Economics, Elsevier, vol. 80(2), pages 309-349, May.
    15. Baker, Malcolm & Wurgler, Jeffrey, 2013. "Behavioral Corporate Finance: An Updated Survey," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, volume 2, chapter 0, pages 357-424, Elsevier.
    16. Ang, Andrew & Piazzesi, Monika, 2003. "A no-arbitrage vector autoregression of term structure dynamics with macroeconomic and latent variables," Journal of Monetary Economics, Elsevier, vol. 50(4), pages 745-787, May.
    17. Lo, Andrew W & Wang, Jiang, 2000. "Trading Volume: Definitions, Data Analysis, and Implications of Portfolio Theory," The Review of Financial Studies, Society for Financial Studies, vol. 13(2), pages 257-300.
    18. Amihud, Yakov, 2002. "Illiquidity and stock returns: cross-section and time-series effects," Journal of Financial Markets, Elsevier, vol. 5(1), pages 31-56, January.
    19. Bandi, F.M. & Perron, B. & Tamoni, A. & Tebaldi, C., 2019. "The scale of predictability," Journal of Econometrics, Elsevier, vol. 208(1), pages 120-140.
    20. Amber Anand & Paul Irvine & Andy Puckett & Kumar Venkataraman, 2012. "Performance of Institutional Trading Desks: An Analysis of Persistence in Trading Costs," The Review of Financial Studies, Society for Financial Studies, vol. 25(2), pages 557-598.
    21. Stefano Dellavigna & Joshua M. Pollet, 2009. "Investor Inattention and Friday Earnings Announcements," Journal of Finance, American Finance Association, vol. 64(2), pages 709-749, April.
    22. Kyle, Albert S, 1985. "Continuous Auctions and Insider Trading," Econometrica, Econometric Society, vol. 53(6), pages 1315-1335, November.
    23. Epps, Thomas W & Epps, Mary Lee, 1976. "The Stochastic Dependence of Security Price Changes and Transaction Volumes: Implications for the Mixture-of-Distributions Hypothesis," Econometrica, Econometric Society, vol. 44(2), pages 305-321, March.
    24. Carhart, Mark M, 1997. "On Persistence in Mutual Fund Performance," Journal of Finance, American Finance Association, vol. 52(1), pages 57-82, March.
    25. Dimitri Vayanos, 2001. "Strategic Trading in a Dynamic Noisy Market," Journal of Finance, American Finance Association, vol. 56(1), pages 131-171, February.
    26. Jonathan Brogaard & Terrence Hendershott & Ryan Riordan, 2014. "High-Frequency Trading and Price Discovery," The Review of Financial Studies, Society for Financial Studies, vol. 27(8), pages 2267-2306.
    27. Gençay, Ramazan & Gençay, Ramazan & Selçuk, Faruk & Whitcher, Brandon J., 2001. "An Introduction to Wavelets and Other Filtering Methods in Finance and Economics," Elsevier Monographs, Elsevier, edition 1, number 9780122796708.
    28. Fama, Eugene F. & French, Kenneth R., 1993. "Common risk factors in the returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 33(1), pages 3-56, February.
    29. Harris, Lawrence, 1987. "Transaction Data Tests of the Mixture of Distributions Hypothesis," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 22(2), pages 127-141, June.
    30. Gallant, A Ronald & Rossi, Peter E & Tauchen, George, 1992. "Stock Prices and Volume," The Review of Financial Studies, Society for Financial Studies, vol. 5(2), pages 199-242.
    31. Andersen, Torben G, 1996. "Return Volatility and Trading Volume: An Information Flow Interpretation of Stochastic Volatility," Journal of Finance, American Finance Association, vol. 51(1), pages 169-204, March.
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    Cited by:

    1. Yufan Chen & Lan Wu & Renyuan Xu & Ruixun Zhang, 2024. "Periodic Trading Activities in Financial Markets: Mean-field Liquidation Game with Major-Minor Players," Papers 2408.09505, arXiv.org.

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    More about this item

    JEL classification:

    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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