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Forecasting stock index futures returns with mixed-frequency sentiment

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  • Gao, Bin
  • Yang, Chunpeng

Abstract

Using the data in Chinese financial market, mixed-frequency stock index futures sentiment and mixed-frequency stock index sentiment are constructed according to MIDAS model. We test whether mixed-frequency stock index futures sentiment and mixed-frequency stock index sentiment have predictive power on stock index futures returns. The empirical results show that mixed-frequency stock index futures sentiment factors have more predictive power than mixed-frequency stock index sentiment factors and Fama-French three factors. In out-sample forecast, we show that sentiment trading strategy provides a more positive returns than time series momentum trading strategy and passive long positions.

Suggested Citation

  • Gao, Bin & Yang, Chunpeng, 2017. "Forecasting stock index futures returns with mixed-frequency sentiment," International Review of Economics & Finance, Elsevier, vol. 49(C), pages 69-83.
    • Handle: RePEc:eee:reveco:v:49:y:2017:i:c:p:69-83
    DOI: 10.1016/j.iref.2017.01.020
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    Cited by:

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    7. Reis, Pedro Manuel Nogueira & Pinho, Carlos, 2020. "A new European investor sentiment index (EURsent) and its return and volatility predictability," Journal of Behavioral and Experimental Finance, Elsevier, vol. 27(C).
    8. Chen, Haozhi & Zhang, Yue, 2023. "Research on the effect of firm-specific investor sentiment on the idiosyncratic volatility anomaly: Evidence from the Chinese market," Pacific-Basin Finance Journal, Elsevier, vol. 81(C).
    9. Gao, Bin & Liu, Xihua, 2020. "Intraday sentiment and market returns," International Review of Economics & Finance, Elsevier, vol. 69(C), pages 48-62.
    10. Zhou, Liyun & Huang, Jialiang, 2020. "Contagion of future-level sentiment in Chinese Agricultural Futures Markets," Pacific-Basin Finance Journal, Elsevier, vol. 61(C).
    11. Seok, Sang Ik & Cho, Hoon & Ryu, Doojin, 2019. "Firm-specific investor sentiment and the stock market response to earnings news," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 221-240.
    12. Lee, Jong Hwa & Sung, Taeyoon & Seo, Sung Won, 2022. "Investor sentiment, credit rating, and stock returns," International Review of Economics & Finance, Elsevier, vol. 80(C), pages 1076-1092.
    13. Zhuo Li & Meiyu Tian & Guangda Ouyang & Fenghua Wen, 2021. "Relationship between investor sentiment and earnings news in high‐ and low‐sentiment periods," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 2748-2765, April.
    14. Ning Wang & Shanhui Ke & Yibo Chen & Tao Yan & Andrew Lim, 2019. "Textual Sentiment of Chinese Microblog Toward the Stock Market," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 18(02), pages 649-671, March.
    15. Qifa Xu & Zezhou Wang & Cuixia Jiang & Yezheng Liu, 2023. "Deep learning on mixed frequency data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(8), pages 2099-2120, December.
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    18. Shu‐Lien Chang & Hsiu‐Chuan Lee & Donald Lien, 2022. "The global latent factor and international index futures returns predictability," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(3), pages 514-538, April.
    19. Liu, Dehong & Qiu, Qi & Hughen, J. Christopher & Lung, Peter, 2019. "Price discovery in the price disagreement between equity and option markets: Evidence from SSE ETF50 options of China," International Review of Economics & Finance, Elsevier, vol. 64(C), pages 557-571.

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