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Return Volatility, Trading Imbalance and the Information Content of Volume

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  • Wu, Chunchi
  • Xu, Xiaoqing Eleanor

Abstract

In this paper, we examine the relationship between volume and return volatility using the transaction data. We introduce transaction and volume imbalance measures to capture the information content of trades. These two information measures are shown to have a strong explanatory power for return volatility and contain incremental information about the asset values over and above that conveyed by the size and frequency of trades. Also, return volatility is significantly correlated with the percentage of trading volume taking place at NYSE. This result suggests that NYSE trades are more informative and contribute more to price discovery. There is evidence that price discovery concentrates in more heavily traded stocks, particularly the Dow Jones Stocks. Finally, return volatility is found to be persistent at the intraday level. The persistence level is higher for less frequently traded stocks. Return volatility also exhibits temporal variations. In particular, return volatility is significantly higher in the opening half-hour for less frequently traded stocks. Thus, stocks with different frequencies of trades may follow different volatility processes. Copyright 2000 by Kluwer Academic Publishers

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  • Wu, Chunchi & Xu, Xiaoqing Eleanor, 2000. "Return Volatility, Trading Imbalance and the Information Content of Volume," Review of Quantitative Finance and Accounting, Springer, vol. 14(2), pages 131-153, March.
  • Handle: RePEc:kap:rqfnac:v:14:y:2000:i:2:p:131-53
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    1. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
    2. Hasbrouck, Joel, 1991. "Measuring the Information Content of Stock Trades," Journal of Finance, American Finance Association, vol. 46(1), pages 179-207, March.
    3. Foster, F Douglas & Viswanathan, S, 1993. "Variations in Trading Volume, Return Volatility, and Trading Costs: Evidence on Recent Price Formation Models," Journal of Finance, American Finance Association, vol. 48(1), pages 187-211, March.
    4. Richardson, Matthew & Smith, Tom, 1994. "A Direct Test of the Mixture of Distributions Hypothesis: Measuring the Daily Flow of Information," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 29(1), pages 101-116, March.
    5. Jones, Charles M & Kaul, Gautam & Lipson, Marc L, 1994. "Transactions, Volume, and Volatility," The Review of Financial Studies, Society for Financial Studies, vol. 7(4), pages 631-651.
    6. Holden, Craig W & Subrahmanyam, Avanidhar, 1992. "Long-Lived Private Information and Imperfect Competition," Journal of Finance, American Finance Association, vol. 47(1), pages 247-270, March.
    7. Lo, Andrew W & MacKinlay, A Craig, 1990. "When Are Contrarian Profits Due to Stock Market Overreaction?," The Review of Financial Studies, Society for Financial Studies, vol. 3(2), pages 175-205.
    8. Glosten, Lawrence R. & Milgrom, Paul R., 1985. "Bid, ask and transaction prices in a specialist market with heterogeneously informed traders," Journal of Financial Economics, Elsevier, vol. 14(1), pages 71-100, March.
    9. Schwert, G William, 1989. " Why Does Stock Market Volatility Change over Time?," Journal of Finance, American Finance Association, vol. 44(5), pages 1115-1153, December.
    10. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    11. Schwert, G William, 1990. "Stock Volatility and the Crash of '87," The Review of Financial Studies, Society for Financial Studies, vol. 3(1), pages 77-102.
    12. Lamoureux, Christopher G & Lastrapes, William D, 1990. "Heteroskedasticity in Stock Return Data: Volume versus GARCH Effects," Journal of Finance, American Finance Association, vol. 45(1), pages 221-229, March.
    13. Madhavan, Ananth & Richardson, Matthew & Roomans, Mark, 1997. "Why Do Security Prices Change? A Transaction-Level Analysis of NYSE Stocks," The Review of Financial Studies, Society for Financial Studies, vol. 10(4), pages 1035-1064.
    14. Clark, Peter K, 1973. "A Subordinated Stochastic Process Model with Finite Variance for Speculative Prices," Econometrica, Econometric Society, vol. 41(1), pages 135-155, January.
    15. Kyle, Albert S, 1985. "Continuous Auctions and Insider Trading," Econometrica, Econometric Society, vol. 53(6), pages 1315-1335, November.
    16. Hiemstra, Craig & Jones, Jonathan D, 1994. "Testing for Linear and Nonlinear Granger Causality in the Stock Price-Volume Relation," Journal of Finance, American Finance Association, vol. 49(5), pages 1639-1664, December.
    17. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    18. Holden, Craig W & Subrahmanyam, Avanidhar, 1996. "Risk Aversion, Liquidity, and Endogenous Short Horizons," The Review of Financial Studies, Society for Financial Studies, vol. 9(2), pages 691-722.
    19. Foster, F Douglas & Viswanathan, S, 1995. "Can Speculative Trading Explain the Volume-Volatility Relation?," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(4), pages 379-396, October.
    20. 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.
    21. 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(1), pages 109-126, March.
    22. Hasbrouck, Joel, 1995. "One Security, Many Markets: Determining the Contributions to Price Discovery," Journal of Finance, American Finance Association, vol. 50(4), pages 1175-1199, September.
    23. Harris, Milton & Raviv, Artur, 1993. "Differences of Opinion Make a Horse Race," The Review of Financial Studies, Society for Financial Studies, vol. 6(3), pages 473-506.
    24. Lamoureux, Christopher G & Lastrapes, William D, 1994. "Endogenous Trading Volume and Momentum in Stock-Return Volatility," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(2), pages 253-260, April.
    25. Easley, David, et al, 1996. "Liquidity, Information, and Infrequently Traded Stocks," Journal of Finance, American Finance Association, vol. 51(4), pages 1405-1436, September.
    26. 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.
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    2. Kao, Erin H. & Fung, Hung-Gay, 2012. "Intraday trading activities and volatility in round-the-clock futures markets," International Review of Economics & Finance, Elsevier, vol. 21(1), pages 195-209.
    3. Peter Chen & Kasing Man & Chunchi Wu, 2003. "The Information Content in Trades of Inactive Nasdaq Stocks," Journal of Entrepreneurial Finance, Pepperdine University, Graziadio School of Business and Management, vol. 8(2), pages 25-53, Summer.
    4. Entorf, Horst & Steiner, Christian, 2006. "Makroökonomische Nachrichten und die Reaktion des 15-Sekunden-DAX: Eine Ereignisstudie zur Wirkung der ZEW-Konjunkturprognose," Darmstadt Discussion Papers in Economics 159, Darmstadt University of Technology, Department of Law and Economics.
    5. Doureige J. Jurdi, 2020. "Intraday Jumps, Liquidity, and U.S. Macroeconomic News: Evidence from Exchange Traded Funds," JRFM, MDPI, vol. 13(6), pages 1-19, June.
    6. Chng, Michael T., 2004. "The trading dynamics of close-substitute futures markets: evidence of margin policy spillover effects," Journal of Multinational Financial Management, Elsevier, vol. 14(4-5), pages 463-483.
    7. Ana-Maria Fuertes & Elena Kalotychou & Natasa Todorovic, 2015. "Daily volume, intraday and overnight returns for volatility prediction: profitability or accuracy?," Review of Quantitative Finance and Accounting, Springer, vol. 45(2), pages 251-278, August.
    8. Chen, An-Sing & Fung, Hung-Gay & Kao, Erin H.C., 2008. "The dynamic relations among return volatility, trading imbalance, and trading volume in futures markets," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(3), pages 429-436.
    9. Mehmet Umutlu & Levent Akdeniz & Aslihan Altay-Salih, 2013. "Foreign Equity Trading and Average Stock-return Volatility," The World Economy, Wiley Blackwell, vol. 36(9), pages 1209-1228, September.
    10. Jinliang Li, 2016. "When noise trading fades, volatility rises," Review of Quantitative Finance and Accounting, Springer, vol. 47(3), pages 475-512, October.
    11. An-Sing Chen & Hui-Jyuan Gao & Mark Leung, 2008. "Is Trading Imbalance a Better Explanatory Factor in the Volatility Process? Intraday and Daily Evidence from E-mini S&P 500 Index Futures and Information-Based Hypotheses," Working Papers 0039, College of Business, University of Texas at San Antonio.
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    13. Entorf Horst & Steiner Christian, 2007. "Makroökonomische Nachrichten und die Reaktion des 15-Sekunden-DAX: Eine Ereignisstudie zur Wirkung der ZEW-Konjunkturprognose / Announcement of Business Cycle Forecasts and the Reaction of the German ," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 227(1), pages 3-26, February.
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