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The price discovery of day trading activities in futures market

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  • Ming-Hsien Chen

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  • Vivian Tai

    ()

Abstract

Access to information is necessary for market transparency. However, contrary to trading volume and open interest, information related to day trading activities is rarely available. By incorporating unexplored day trading volume in the literature, this paper demonstrates that both the expected open interest and expected day trading volume are consistently and positively correlated with returns, but that one-lagged day trading volume is negatively correlated with futures returns. Meanwhile, both expected and unexpected day trading volume are negatively correlated with volatility, suggesting that arbitrage activities related to unexpected day trading volume may accelerate the movement of futures prices to a new equilibrium. Moreover, open interest provides liquidity but increases volatility. Finally, we strongly suggest that day trading transaction information be released by futures exchanges to achieve greater transparency. Copyright Springer Science+Business Media New York 2014

Suggested Citation

  • Ming-Hsien Chen & Vivian Tai, 2014. "The price discovery of day trading activities in futures market," Review of Derivatives Research, Springer, vol. 17(2), pages 217-239, July.
  • Handle: RePEc:kap:revdev:v:17:y:2014:i:2:p:217-239
    DOI: 10.1007/s11147-014-9096-x
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    References listed on IDEAS

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    1. Keim, Donald B & Stambaugh, Robert F, 1984. " A Further Investigation of the Weekend Effect in Stock Returns," Journal of Finance, American Finance Association, vol. 39(3), pages 819-835, July.
    2. Schwert, G William, 1990. "Stock Volatility and the Crash of '87," Review of Financial Studies, Society for Financial Studies, vol. 3(1), pages 77-102.
    3. 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.
    4. John Y. Campbell, 2001. "Have Individual Stocks Become More Volatile? An Empirical Exploration of Idiosyncratic Risk," Journal of Finance, American Finance Association, vol. 56(1), pages 1-43, February.
    5. Alex Frino & Robert I. Webb & Hui Zheng, 2012. "Does International Order Flow Contribute to Price Discovery in Futures Markets?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 32(12), pages 1124-1143, December.
    6. Berkman, Henk & Brailsford, Tim & Frino, Alex, 2005. "A note on execution costs for stock index futures: Information versus liquidity effects," Journal of Banking & Finance, Elsevier, vol. 29(3), pages 565-577, March.
    7. Le, Van & Zurbruegg, Ralf, 2010. "The role of trading volume in volatility forecasting," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 20(5), pages 533-555, December.
    8. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    9. Terrance Odean, 1998. "Volume, Volatility, Price, and Profit When All Traders Are Above Average," Journal of Finance, American Finance Association, vol. 53(6), pages 1887-1934, December.
    10. Hong, Harrison & Yogo, Motohiro, 2012. "What does futures market interest tell us about the macroeconomy and asset prices?," Journal of Financial Economics, Elsevier, vol. 105(3), pages 473-490.
    11. Koopman, Siem Jan & Jungbacker, Borus & Hol, Eugenie, 2005. "Forecasting daily variability of the S&P 100 stock index using historical, realised and implied volatility measurements," Journal of Empirical Finance, Elsevier, vol. 12(3), pages 445-475, June.
    12. Chen, Ying & Härdle, Wolfgang Karl & Pigorsch, Uta, 2010. "Localized Realized Volatility Modeling," Journal of the American Statistical Association, American Statistical Association, vol. 105(492), pages 1376-1393.
    13. White, Halbert, 1980. "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity," Econometrica, Econometric Society, vol. 48(4), pages 817-838, May.
    14. Tauchen, George E & Pitts, Mark, 1983. "The Price Variability-Volume Relationship on Speculative Markets," Econometrica, Econometric Society, vol. 51(2), pages 485-505, March.
    15. French, Kenneth R. & Roll, Richard, 1986. "Stock return variances : The arrival of information and the reaction of traders," Journal of Financial Economics, Elsevier, vol. 17(1), pages 5-26, September.
    16. 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.
    17. Harris, Jeffrey H. & Schultz, Paul H., 1998. "The trading profits of SOES bandits," Journal of Financial Economics, Elsevier, vol. 50(1), pages 39-62, October.
    18. Bessembinder, Hendrik & Seguin, Paul J., 1993. "Price Volatility, Trading Volume, and Market Depth: Evidence from Futures Markets," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 28(01), pages 21-39, March.
    19. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    20. Bessembinder, Hendrik & Seguin, Paul J, 1992. " Futures-Trading Activity and Stock Price Volatility," Journal of Finance, American Finance Association, vol. 47(5), pages 2015-2034, December.
    21. Elena Kalotychou & Sotiris Staikouras, 2006. "Volatility and trading activity in Short Sterling futures," Applied Economics, Taylor & Francis Journals, vol. 38(9), pages 997-1005.
    22. 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.
    23. 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.
    24. Schwert, G William & Seguin, Paul J, 1990. " Heteroskedasticity in Stock Returns," Journal of Finance, American Finance Association, vol. 45(4), pages 1129-1155, September.
    25. Chen, Nai-Fu & Cuny, Charles J & Haugen, Robert A, 1995. " Stock Volatility and the Levels of the Basis and Open Interest in Future Contracts," Journal of Finance, American Finance Association, vol. 50(1), pages 281-300, March.
    26. Brad M. Barber & Terrance Odean, 2001. "The Internet and the Investor," Journal of Economic Perspectives, American Economic Association, vol. 15(1), pages 41-54, Winter.
    27. 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.
    28. Brad M. Barber & Terrance Odean, 2000. "Trading Is Hazardous to Your Wealth: The Common Stock Investment Performance of Individual Investors," Journal of Finance, American Finance Association, vol. 55(2), pages 773-806, April.
    29. Arago, Vicent & Nieto, Luisa, 2005. "Heteroskedasticity in the returns of the main world stock exchange indices: volume versus GARCH effects," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 15(3), pages 271-284, July.
    30. Epps, Thomas W, 1975. "Security Price Changes and Transaction Volumes: Theory and Evidence," American Economic Review, American Economic Association, vol. 65(4), pages 586-597, September.
    31. Engle, Robert F & Lilien, David M & Robins, Russell P, 1987. "Estimating Time Varying Risk Premia in the Term Structure: The Arch-M Model," Econometrica, Econometric Society, vol. 55(2), pages 391-407, March.
    32. Judd, Kenneth L. & Leisen, Dietmar P.J., 2010. "Equilibrium open interest," Journal of Economic Dynamics and Control, Elsevier, vol. 34(12), pages 2578-2600, December.
    33. Chen, Gong-meng & Firth, Michael & Rui, Oliver M, 2001. "The Dynamic Relation between Stock Returns, Trading Volume, and Volatility," The Financial Review, Eastern Finance Association, vol. 36(3), pages 153-173, August.
    34. Rogalski, Richard J, 1978. "The Dependence of Prices and Volume," The Review of Economics and Statistics, MIT Press, vol. 60(2), pages 268-274, May.
    35. Merton, Robert C., 1980. "On estimating the expected return on the market : An exploratory investigation," Journal of Financial Economics, Elsevier, vol. 8(4), pages 323-361, December.
    36. French, Kenneth R., 1980. "Stock returns and the weekend effect," Journal of Financial Economics, Elsevier, vol. 8(1), pages 55-69, March.
    37. Jennings, Robert H & Starks, Laura T & Fellingham, John C, 1981. "An Equilibrium Model of Asset Trading with Sequential Information Arrival," Journal of Finance, American Finance Association, vol. 36(1), pages 143-161, March.
    38. Copeland, Thomas E, 1976. "A Model of Asset Trading under the Assumption of Sequential Information Arrival," Journal of Finance, American Finance Association, vol. 31(4), pages 1149-1168, September.
    39. Robert T. Daigler & Marilyn K. Wiley, 1999. "The Impact of Trader Type on the Futures Volatility-Volume Relation," Journal of Finance, American Finance Association, vol. 54(6), pages 2297-2316, December.
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    Cited by:

    1. Elina Pradkhan, 2016. "Information Content of Trading Activity in Precious Metals Futures Markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 36(5), pages 421-456, May.

    More about this item

    Keywords

    Day trading volume; Price discovery; Unexpected shocks; Stock index futures; G12; G13; G14; C22;

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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