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Persistence of the Dow Jones Index on Rising Volume

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  • LeBaron, B.

Abstract

This paper documents a relation between the persistence of stock returns for a large firm index and trading volume. Previous results on the negative relation between volume and persistence are replicated, but a second effect is discovered. Persistence is directly related to the current rate of change of volume. Also, this effect appears much stronger for positive returns than negative returns. Various specifications are tested to explore the structure of this phenomenon. Finally, individual firm returns are used showing that much of the correlation is coming from cross firm effects involving leads and lags. Some weak evidence is presented showing that lower beta firms are more likely to lead the overall index movements.
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Suggested Citation

  • LeBaron, B., 1992. "Persistence of the Dow Jones Index on Rising Volume," Working papers 9201, Wisconsin Madison - Social Systems.
  • Handle: RePEc:att:wimass:9201
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    Cited by:

    1. Bertrand Maillet & Thierry Michel, 2000. "Further insights on the puzzle of technical analysis profitability," The European Journal of Finance, Taylor & Francis Journals, vol. 6(2), pages 196-224.
    2. Serge Darolles & Gaëlle Le Fol, 2003. "Trading Volume and Arbitrage," Working Papers 2003-46, Center for Research in Economics and Statistics.
    3. Tut, DANIEL, 2024. "Bitcoin, speculative sentiments and crypto-assets valuation," MPRA Paper 120866, University Library of Munich, Germany.
    4. Cetin Ciner, 2003. "Dynamic Linkages Between Trading Volume and Price Movements: Evidence for Small Firm Stocks," Journal of Entrepreneurial Finance, Pepperdine University, Graziadio School of Business and Management, vol. 8(1), pages 87-102, Spring.
    5. 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.
    6. Chae, Joon & Kang, Mhin, 2019. "Low-volume return premium in the Korean stock market," Pacific-Basin Finance Journal, Elsevier, vol. 58(C).
    7. Lin, Wen-Ling, 1995. "Market closure and predictability of intradaily stock returns in the United States and Japan," Journal of Empirical Finance, Elsevier, vol. 2(1), pages 19-44, March.
    8. Covrig, Vicentiu & Ng, Lilian, 2004. "Volume autocorrelation, information, and investor trading," Journal of Banking & Finance, Elsevier, vol. 28(9), pages 2155-2174, September.
    9. Germán G. Creamer & Tal Ben-Zvi, 2021. "Volatility and Risk in the Energy Market: A Trade Network Approach," Sustainability, MDPI, vol. 13(18), pages 1-17, September.
    10. Rashid, Abdul, 2007. "Stock prices and trading volume: An assessment for linear and nonlinear Granger causality," Journal of Asian Economics, Elsevier, vol. 18(4), pages 595-612, August.
    11. Wang, Jiang, 1994. "A Model of Competitive Stock Trading Volume," Journal of Political Economy, University of Chicago Press, vol. 102(1), pages 127-168, February.
    12. He, Hua & Wang, Jiang, 1995. "Differential Information and Dynamic Behavior of Stock Trading Volume," The Review of Financial Studies, Society for Financial Studies, vol. 8(4), pages 919-972.
    13. Andrew W. Lo & Jiang Wang, 2006. "Trading Volume: Implications of an Intertemporal Capital Asset Pricing Model," Journal of Finance, American Finance Association, vol. 61(6), pages 2805-2840, December.
    14. Jiang Wang, 2002. "Trading Volume and Asset Prices," Annals of Economics and Finance, Society for AEF, vol. 3(2), pages 299-359, November.
    15. Tomasz Wójtowicz, 2017. "High-volume return premium on the stock markets in Warsaw and Vienna," Bank i Kredyt, Narodowy Bank Polski, vol. 48(4), pages 375-402.
    16. Kramer, Charles, 1999. "Noise trading, transaction costs, and the relationship of stock returns and trading volume," International Review of Economics & Finance, Elsevier, vol. 8(4), pages 343-362, November.
    17. Darolles, Serge & Fol, Gaëlle Le & Mero, Gulten, 2015. "Measuring the liquidity part of volume," Journal of Banking & Finance, Elsevier, vol. 50(C), pages 92-105.
    18. Guillermo Llorente & Roni Michaely & Gideon Saar & Jiang Wang, 2002. "Dynamic Volume-Return Relation of Individual Stocks," The Review of Financial Studies, Society for Financial Studies, vol. 15(4), pages 1005-1047.
    19. Po-Hsuan Hsu & Chung-Ming Kuan, 2004. "Re-Examining the Profitability of Technical Analysis with White’s Reality Check," IEAS Working Paper : academic research 04-A003, Institute of Economics, Academia Sinica, Taipei, Taiwan.
    20. Tauchen, George & Zhang, Harold & Liu, Ming, 1996. "Volume, volatility, and leverage: A dynamic analysis," Journal of Econometrics, Elsevier, vol. 74(1), pages 177-208, September.
    21. Kausik Chaudhuri & Alok Kumar, 2015. "A Markov-Switching Model for Indian Stock Price and Volume," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 14(3), pages 239-257, December.
    22. Eric Ghysels & João Pereira, 2003. "On Portfolio Choice, Liquidity, and Short Selling: A Nonparametric Investigation," CIRANO Working Papers 2003s-27, CIRANO.
    23. Thomas Hellström & Kenneth Holmström, 2000. "The relevance of trends for predictions of stock returns," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 9(1), pages 23-34, March.

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