IDEAS home Printed from https://ideas.repec.org/a/wly/jfutmk/v43y2023i4p437-454.html
   My bibliography  Save this article

Anger in predicting the index futures returns

Author

Listed:
  • Zhen Cao
  • Jiancheng Shen
  • Xinbei Wei
  • Qunzi Zhang

Abstract

This paper aims to investigate how different emotions affect the subsequent index futures returns. We test the forecasting regressions which predict the S&P 500 index futures returns with lagged text‐based emotion (anger, joy, fear, optimism, and gloom) indices and find asymmetric forecasting power exists between pessimism and optimism emotion indices. We show that only the text‐based anger index could reliably perform at predicting index futures return in‐sample and outperform the prevailing unconditional mean out‐of‐sample. Notably, the predictive power of the text‐based anger index persists after controlling for other emotion indices, investor sentiment indices, and fundamental variables known to predict the futures market. And the asset allocation conditioning on text‐based anger index can generate substantial economic benefits. Furthermore, the anger index influences the index futures return through both the discount rate and cash flow channels.

Suggested Citation

  • 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.
  • Handle: RePEc:wly:jfutmk:v:43:y:2023:i:4:p:437-454
    DOI: 10.1002/fut.22394
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/fut.22394
    Download Restriction: no

    File URL: https://libkey.io/10.1002/fut.22394?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    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. Campbell, John Y, 1991. "A Variance Decomposition for Stock Returns," Economic Journal, Royal Economic Society, vol. 101(405), pages 157-179, March.
    3. 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.
    4. Neal, Robert & Wheatley, Simon M., 1998. "Do Measures of Investor Sentiment Predict Returns?," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 33(4), pages 523-547, December.
    5. Stambaugh, Robert F. & Yu, Jianfeng & Yuan, Yu, 2012. "The short of it: Investor sentiment and anomalies," Journal of Financial Economics, Elsevier, vol. 104(2), pages 288-302.
    6. 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.
    7. 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.
    8. Smales, Lee A., 2014. "News sentiment in the gold futures market," Journal of Banking & Finance, Elsevier, vol. 49(C), pages 275-286.
    9. Dashan Huang & Fuwei Jiang & Jun Tu & Guofu Zhou, 2015. "Investor Sentiment Aligned: A Powerful Predictor of Stock Returns," The Review of Financial Studies, Society for Financial Studies, vol. 28(3), pages 791-837.
    10. John Griffith & Mohammad Najand & Jiancheng Shen, 2020. "Emotions in the Stock Market," Journal of Behavioral Finance, Taylor & Francis Journals, vol. 21(1), pages 42-56, January.
    11. Manela, Asaf & Moreira, Alan, 2017. "News implied volatility and disaster concerns," Journal of Financial Economics, Elsevier, vol. 123(1), pages 137-162.
    12. Mele, Antonio, 2007. "Asymmetric stock market volatility and the cyclical behavior of expected returns," Journal of Financial Economics, Elsevier, vol. 86(2), pages 446-478, November.
    13. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Hui Qu & Tianyang Wang & Peng Shangguan & Mengying He, 2024. "Revisiting the puzzle of jumps in volatility forecasting: The new insights of high‐frequency jump intensity," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(2), pages 218-251, February.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Haibin Xie & Shouyang Wang, 2018. "Timing the market: the economic value of price extremes," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 4(1), pages 1-24, December.
    2. Guofu Zhou, 2018. "Measuring Investor Sentiment," Annual Review of Financial Economics, Annual Reviews, vol. 10(1), pages 239-259, November.
    3. Jiang, Fuwei & Liu, Hongkui & Yu, Jiasheng & Zhang, Huajing, 2023. "International stock return predictability: The role of U.S. uncertainty spillover," Pacific-Basin Finance Journal, Elsevier, vol. 82(C).
    4. Huang, Dashan & Li, Jiangyuan & Wang, Liyao, 2021. "Are disagreements agreeable? Evidence from information aggregation," Journal of Financial Economics, Elsevier, vol. 141(1), pages 83-101.
    5. Jian Chen & Jiaquan Yao & Qunzi Zhang & Xiaoneng Zhu, 2023. "Global Disaster Risk Matters," Management Science, INFORMS, vol. 69(1), pages 576-597, January.
    6. Yaojie Zhang & Mengxi He & Zhikai Zhang, 2024. "Forecasting stock returns with industry volatility concentration," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(7), pages 2705-2730, November.
    7. Xi Dong & Yan Li & David E. Rapach & Guofu Zhou, 2022. "Anomalies and the Expected Market Return," Journal of Finance, American Finance Association, vol. 77(1), pages 639-681, February.
    8. Christopher J. Neely & David E. Rapach & Jun Tu & Guofu Zhou, 2014. "Forecasting the Equity Risk Premium: The Role of Technical Indicators," Management Science, INFORMS, vol. 60(7), pages 1772-1791, July.
    9. Yongan Xu & Jianqiong Wang & Zhonglu Chen & Chao Liang, 2023. "Sentiment indices and stock returns: Evidence from China," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(1), pages 1063-1080, January.
    10. Yu, Deshui & Huang, Difang, 2023. "Cross-sectional uncertainty and expected stock returns," Journal of Empirical Finance, Elsevier, vol. 72(C), pages 321-340.
    11. Lin, Qi, 2018. "Technical analysis and stock return predictability: An aligned approach," Journal of Financial Markets, Elsevier, vol. 38(C), pages 103-123.
    12. Liya Chu & Xue-Zhong He & Kai Li & Jun Tu, 2015. "Market Sentiment and Paradigm Shifts," Research Paper Series 356, Quantitative Finance Research Centre, University of Technology, Sydney.
    13. Souropanis, Ioannis & Vivian, Andrew, 2023. "Forecasting realized volatility with wavelet decomposition," Journal of Empirical Finance, Elsevier, vol. 74(C).
    14. Jiang, Fuwei & Lee, Joshua & Martin, Xiumin & Zhou, Guofu, 2019. "Manager sentiment and stock returns," Journal of Financial Economics, Elsevier, vol. 132(1), pages 126-149.
    15. Bevilacqua, Mattia & Tunaru, Radu, 2021. "The SKEW index: Extracting what has been left," Journal of Financial Stability, Elsevier, vol. 53(C).
    16. Liya Chu & Xue-Zhong He & Kai Li & Jun Tu, 2022. "Investor Sentiment and Paradigm Shifts in Equity Return Forecasting," Management Science, INFORMS, vol. 68(6), pages 4301-4325, June.
    17. Lin, Qi & Lin, Xi, 2021. "Cash conversion cycle and aggregate stock returns," Journal of Financial Markets, Elsevier, vol. 52(C).
    18. Bevilacqua, Mattia & Tunaru, Radu, 2021. "The SKEW index: extracting what has been left," LSE Research Online Documents on Economics 108198, London School of Economics and Political Science, LSE Library.
    19. Xu, Yongan & Liang, Chao & Li, Yan & Huynh, Toan L.D., 2022. "News sentiment and stock return: Evidence from managers’ news coverages," Finance Research Letters, Elsevier, vol. 48(C).
    20. Rapach, David E. & Ringgenberg, Matthew C. & Zhou, Guofu, 2016. "Short interest and aggregate stock returns," Journal of Financial Economics, Elsevier, vol. 121(1), pages 46-65.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wly:jfutmk:v:43:y:2023:i:4:p:437-454. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: http://www.interscience.wiley.com/jpages/0270-7314/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.