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The Theory Of Contrary Opinion: A Test Using Sentiment Indices In Futures Markets

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  • Sanders, Dwight R.
  • Irwin, Scott H.
  • Leuthold, Raymond M.

Abstract

The theory of contrary opinion predicts price reversals following extremes in market sentiment. This research tests a survey-based sentiment index's usefulness as a contrary indicator across 28 U.S. futures markets. Using rigorous time-series tests, the sentiment index displays only a sporadic and marginal ability to predict returns, and in those instances the pattern is one of return continuation--not reversals. Therefore, futures traders who rely solely upon sentiment indices as contrary indicators may be misguided.

Suggested Citation

  • Sanders, Dwight R. & Irwin, Scott H. & Leuthold, Raymond M., 2003. "The Theory Of Contrary Opinion: A Test Using Sentiment Indices In Futures Markets," Journal of Agribusiness, Agricultural Economics Association of Georgia, vol. 21(1), pages 1-26.
    • Handle: RePEc:ags:jloagb:14673
    DOI: 10.22004/ag.econ.14673
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    References listed on IDEAS

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    1. 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.
    2. De Bondt, Werner P. M., 1993. "Betting on trends: Intuitive forecasts of financial risk and return," International Journal of Forecasting, Elsevier, vol. 9(3), pages 355-371, November.
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    Cited by:

    1. Peri, Massimo & Vandone, Daniela & Baldi, Lucia, 2014. "Internet, noise trading and commodity futures prices," International Review of Economics & Finance, Elsevier, vol. 33(C), pages 82-89.
    2. Bahloul, Walid & Bouri, Abdelfettah, 2016. "The impact of investor sentiment on returns and conditional volatility in U.S. futures markets," Journal of Multinational Financial Management, Elsevier, vol. 36(C), pages 89-102.
    3. Sanders, Dwight R. & Irwin, Scott H. & Merrin, Robert P., 2007. "Smart Money? The Forecasting Ability of CFTC Large Traders," 2007 Conference, April 16-17, 2007, Chicago, Illinois 37556, NCCC-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    4. Li, Xin & Ma, Jian & Wang, Shouyang & Zhang, Xun, 2015. "How does Google search affect trader positions and crude oil prices?," Economic Modelling, Elsevier, vol. 49(C), pages 162-171.
    5. Wang, Lu & Ma, Feng & Niu, Tianjiao & Liang, Chao, 2021. "The importance of extreme shock: Examining the effect of investor sentiment on the crude oil futures market," Energy Economics, Elsevier, vol. 99(C).
    6. Chen, Rongda & Bao, Weiwei & Jin, Chenglu, 2021. "Investor sentiment and predictability for volatility on energy futures Markets: Evidence from China," International Review of Economics & Finance, Elsevier, vol. 75(C), pages 112-129.
    7. Bahloul, Walid & Bouri, Abdelfettah, 2016. "Profitability of return and sentiment-based investment strategies in US futures markets," Research in International Business and Finance, Elsevier, vol. 36(C), pages 254-270.
    8. Maslyuk-Escobedo, Svetlana & Rotaru, Kristian & Dokumentov, Alexander, 2017. "News sentiment and jumps in energy spot and futures markets," Pacific-Basin Finance Journal, Elsevier, vol. 45(C), pages 186-210.
    9. Zhou, Liyun & Huang, Jialiang, 2020. "Contagion of future-level sentiment in Chinese Agricultural Futures Markets," Pacific-Basin Finance Journal, Elsevier, vol. 61(C).

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