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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
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    References listed on IDEAS

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    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.

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