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Analyst rating matters for index futures

Author

Listed:
  • Liyan Han
  • Xinbei Wei
  • Sen Yan
  • Qunzi Zhang

Abstract

Analyst recommendations convey valuable market‐wide information which implies analyst rating should generate reliable predictability for future market returns. This paper examines the predictive regressions which forecast the S&P 500 index futures return and volatility with lagged text‐based analyst rating index (TAR index). Empirical evidence shows that the TAR index generates superior in‐sample predictability. This substantial predictability remains after controlling the business cycles, macroeconomic factors, and economic conditions. Also, the TAR index outperforms the prevailing mean out‐of‐sample and generates significant economic performance. Notably, the TAR index also delivers consistent predictive gains on the volatility of index futures returns.

Suggested Citation

  • Liyan Han & Xinbei Wei & Sen Yan & Qunzi Zhang, 2022. "Analyst rating matters for index futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(11), pages 2084-2100, November.
    • Handle: RePEc:wly:jfutmk:v:42:y:2022:i:11:p:2084-2100
    DOI: 10.1002/fut.22341
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    References listed on IDEAS

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    1. Ivo Welch & Amit Goyal, 2008. "A Comprehensive Look at The Empirical Performance of Equity Premium Prediction," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1455-1508, July.
    2. Clark, Todd E. & McCracken, Michael W., 2001. "Tests of equal forecast accuracy and encompassing for nested models," Journal of Econometrics, Elsevier, vol. 105(1), pages 85-110, November.
    3. Womack, Kent L, 1996. "Do Brokerage Analysts' Recommendations Have Investment Value?," Journal of Finance, American Finance Association, vol. 51(1), pages 137-167, March.
    4. Charlotte Christiansen & Maik Schmeling & Andreas Schrimpf, 2012. "A comprehensive look at financial volatility prediction by economic variables," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(6), pages 956-977, September.
    5. John S. Howe & Emre Unlu & Xuemin (Sterling) Yan, 2009. "The Predictive Content of Aggregate Analyst Recommendations," Journal of Accounting Research, Wiley Blackwell, vol. 47(3), pages 799-821, June.
    6. Eric Jondeau & Xuewu Wang & Zhipeng Yan & Qunzi Zhang, 2020. "Skewness and index futures return," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(11), pages 1648-1664, November.
    7. Welagedara, Venura & Deb, Saikat Sovan & Singh, Harminder, 2017. "Investor attention, analyst recommendation revisions, and stock prices," Pacific-Basin Finance Journal, Elsevier, vol. 45(C), pages 211-223.
    8. Kim, Karam & Ryu, Doojin & Yang, Heejin, 2021. "Information uncertainty, investor sentiment, and analyst reports," International Review of Financial Analysis, Elsevier, vol. 77(C).
    9. Ser-Huang Poon & Clive W.J. Granger, 2003. "Forecasting Volatility in Financial Markets: A Review," Journal of Economic Literature, American Economic Association, vol. 41(2), pages 478-539, June.
    10. Valentyn Panchenko, 2007. "Impact of Analysts' Recommendations on Stock Performance," The European Journal of Finance, Taylor & Francis Journals, vol. 13(2), pages 165-179.
    11. Peng W. He & Andrew Grant & Joel Fabre, 2013. "Economic value of analyst recommendations in Australia: an application of the Black–Litterman asset allocation model," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 53(2), pages 441-470, June.
    12. Orie E. Barron & Mary Harris Stanford & Yong Yu, 2009. "Further Evidence on the Relation between Analysts' Forecast Dispersion and Stock Returns," Contemporary Accounting Research, John Wiley & Sons, vol. 26(2), pages 329-357, June.
    13. Corbet, Shaen & Dowling, Michael & Cummins, Mark, 2015. "Analyst recommendations and volatility in a rising, falling, and crisis equity market," Finance Research Letters, Elsevier, vol. 15(C), pages 187-194.
    14. Qunzi Zhang, 2021. "One hundred years of rare disaster concerns and commodity prices," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(12), pages 1891-1915, December.
    15. David E. Rapach & Jack K. Strauss & Guofu Zhou, 2010. "Out-of-Sample Equity Premium Prediction: Combination Forecasts and Links to the Real Economy," The Review of Financial Studies, Society for Financial Studies, vol. 23(2), pages 821-862, February.
    16. Brad Barber & Reuven Lehavy & Maureen McNichols & Brett Trueman, 2001. "Can Investors Profit from the Prophets? Security Analyst Recommendations and Stock Returns," Journal of Finance, American Finance Association, vol. 56(2), pages 531-563, April.
    17. Cao, Zhen & Han, Liyan & Wei, Xinbei & Zhang, Qunzi, 2022. "Fear in commodity return prediction," Finance Research Letters, Elsevier, vol. 46(PB).
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    Cited by:

    1. Lee, Hsiu-Chuan & Lee, Yun-Huan & Nguyen, Cuong, 2023. "Tail comovements of implied volatility indices and global index futures returns predictability," Pacific-Basin Finance Journal, Elsevier, vol. 80(C).
    2. Zhen Cao & Jiancheng Shen & Xinbei Wei & Qunzi Zhang, 2023. "Anger in predicting the index futures returns," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(4), pages 437-454, April.

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