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The Effects Of Futures Trading By Large Hedge Funds And Ctas On Market Volatility

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  • Holt, Bryce R.
  • Irwin, Scott H.

Abstract

This study uses the newly available data from the CFTC to investigate the market impact of futures trading by large hedge funds and CTAs. Regression results show that there is a positive relationship between the trading volume of large hedge funds and CTAs and market volatility. However, a positive relationship between hedge fund and CTA trading volume and market volatility is consistent with either a private information or noise trader hypothesis. Three additional tests are conducted to distinguish between the private information hypothesis and the noise trader hypothesis. The first test consisted of identifying the noise component exhibited in return variances over different holding periods. The variance ratio tests provide little support for the noise trader hypothesis. The second test examined whether positive feedback trading characterized large hedge fund and CTA trading behavior. These results suggest that trading decisions by large hedge funds and CTAs, although influenced in small part by past price changes, are not driven by past price changes. The third test consists of estimating the profits and losses associated with the open interest positions of large hedge funds and CTAs. This test is based on the argument that speculative trading can only be destabilizing if speculators buy when prices are high and sell when prices are low, which in turn, implies that destabilizing speculators lose money. Across all thirteen markets, the profit for large hedge funds and CTAs is estimated to be just under $400 million. This implies that the trading decisions are likely based on valuable private information. Overall, the evidence presented in this study suggests trading by large hedge funds and CTAs is based on private fundamental information. These findings imply large hedge funds and CTAs benefit market efficiency by bringing valuable, fundamental information to the market through their trading.

Suggested Citation

  • Holt, Bryce R. & Irwin, Scott H., 2000. "The Effects Of Futures Trading By Large Hedge Funds And Ctas On Market Volatility," 2000 Conference, April 17-18 2000, Chicago, Illinois 18935, NCR-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    • Handle: RePEc:ags:ncrtci:18935
    DOI: 10.22004/ag.econ.18935
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    References listed on IDEAS

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    1. Parkinson, Michael, 1980. "The Extreme Value Method for Estimating the Variance of the Rate of Return," The Journal of Business, University of Chicago Press, vol. 53(1), pages 61-65, January.
    2. Stephen J. Brown & William N. Goetzmann & James Park, 1998. "Hedge Funds and the Asian Currency Crisis of 1997," NBER Working Papers 6427, National Bureau of Economic Research, Inc.
    3. Wiggins, James B, 1991. "Empirical Tests of the Bias and Efficiency of the Extreme-Value Variance Estimator for Common Stocks," The Journal of Business, University of Chicago Press, vol. 64(3), pages 417-432, July.
    4. Chang, Eric C. & Michael Pinegar, J. & Schachter, Barry, 1997. "Interday variations in volume, variance and participation of large speculators," Journal of Banking & Finance, Elsevier, vol. 21(6), pages 797-810, June.
    5. 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(1), pages 21-39, March.
    6. 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.
    7. 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.
    8. Leuthold, Raymond M & Garcia, Philip & Lu, Richard, 1994. "The Returns and Forecasting Ability of Large Traders in the Frozen Pork Bellies Futures Market," The Journal of Business, University of Chicago Press, vol. 67(3), pages 459-473, July.
    9. 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.
    10. Hartzmark, Michael L, 1987. "Returns to Individual Traders of Futures: Aggregate Results," Journal of Political Economy, University of Chicago Press, vol. 95(6), pages 1292-1306, December.
    11. Fung, William & Hsieh, David A, 1997. "Empirical Characteristics of Dynamic Trading Strategies: The Case of Hedge Funds," The Review of Financial Studies, Society for Financial Studies, vol. 10(2), pages 275-302.
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    Cited by:

    1. Yiuman Tse & Michael Williams, 2011. "Does Index Speculation Impact Commodity Prices? An Intraday Futures Analysis Using intraday data, we find that unidirectional causality runs from commodity index linked commodity futures to non-index ," Working Papers 0007, College of Business, University of Texas at San Antonio.
    2. Kidd, Willis V. & Brorsen, B. Wade, 2004. "Why have the returns to technical analysis decreased?," Journal of Economics and Business, Elsevier, vol. 56(3), pages 159-176.
    3. Nardella, Michele, 2007. "Price efficiency and speculative trading in cocoa futures markets," 81st Annual Conference, April 2-4, 2007, Reading University, UK 7970, Agricultural Economics Society.
    4. Mingue SUn, 2010. "A Branch-and-Bound Algorithm for Representative Integer Efficient Solutions in Multiple Objective Network Programming Problems," Working Papers 0007, College of Business, University of Texas at San Antonio.
    5. Yiuman Tse & Michael R. Williams, 2013. "Does Index Speculation Impact Commodity Prices? An Intraday Analysis," The Financial Review, Eastern Finance Association, vol. 48(3), pages 365-383, August.

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