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Does mixed-frequency investor sentiment impact stock returns? Based on the empirical study of MIDAS regression model

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  • Chunpeng Yang
  • Rengui Zhang

Abstract

We examine whether mixed-frequency investor sentiment affects stock returns. In line with recent evidence from China, we find that the aggregate effect and the individual effect of mixed-frequency investor sentiment are statistically significant, and mixed-frequency investor sentiment is more important than the low-frequency one. Moreover, mixed-frequency investor sentiment, which is mixed by high-frequency data, can be more important than the market premium.

Suggested Citation

  • Chunpeng Yang & Rengui Zhang, 2014. "Does mixed-frequency investor sentiment impact stock returns? Based on the empirical study of MIDAS regression model," Applied Economics, Taylor & Francis Journals, vol. 46(9), pages 966-972, March.
    • Handle: RePEc:taf:applec:v:46:y:2014:i:9:p:966-972
    DOI: 10.1080/00036846.2013.864041
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    Cited by:

    1. Li, Jinfang, 2019. "Sentiment trading, informed trading and dynamic asset pricing," The North American Journal of Economics and Finance, Elsevier, vol. 47(C), pages 210-222.
    2. Seok, Sang Ik & Cho, Hoon & Ryu, Doojin, 2019. "Firm-specific investor sentiment and daily stock returns," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    3. Gao, Bin & Liu, Xihua, 2020. "Intraday sentiment and market returns," International Review of Economics & Finance, Elsevier, vol. 69(C), pages 48-62.
    4. Li, Jinfang, 2020. "The momentum and reversal effects of investor sentiment on stock prices," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    5. Zhao, Xin & Han, Meng & Ding, Lili & Kang, Wanglin, 2018. "Usefulness of economic and energy data at different frequencies for carbon price forecasting in the EU ETS," Applied Energy, Elsevier, vol. 216(C), pages 132-141.
    6. Li, Jinfang, 2014. "Multi-period sentiment asset pricing model with information," International Review of Economics & Finance, Elsevier, vol. 34(C), pages 118-130.
    7. Han, Meng & Ding, Lili & Zhao, Xin & Kang, Wanglin, 2019. "Forecasting carbon prices in the Shenzhen market, China: The role of mixed-frequency factors," Energy, Elsevier, vol. 171(C), pages 69-76.
    8. Yang, Chunpeng & Zhou, Liyun, 2015. "Sentiment approach to underestimation and overestimation pricing model," Economic Modelling, Elsevier, vol. 51(C), pages 280-288.
    9. Heejin Yang & Doowon Ryu, 2021. "Investor Sentiment and Price Discrepancies between Common and Preferred Stocks in Korea," Sustainability, MDPI, vol. 13(10), pages 1-11, May.
    10. Sang Ik Seok & Hoon Cho & Chanhi Park & Doojin Ryu, 2019. "Do Overnight Returns Truly Measure Firm-Specific Investor Sentiment in the KOSPI Market?," Sustainability, MDPI, vol. 11(13), pages 1-14, July.
    11. 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.
    12. Yang, Chunpeng & Zhou, Liyun, 2015. "Investor trading behavior, investor sentiment and asset prices," The North American Journal of Economics and Finance, Elsevier, vol. 34(C), pages 42-62.
    13. 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.
    14. Yang, Chunpeng & Gao, Bin, 2014. "The term structure of sentiment effect in stock index futures market," The North American Journal of Economics and Finance, Elsevier, vol. 30(C), pages 171-182.
    15. Abderrahmen Aloulou & Siwar Ellouze, 2017. "Does fundamental value run asset price formation process? Evidence from option price information content," Journal of Asset Management, Palgrave Macmillan, vol. 18(4), pages 255-268, July.
    16. Julián Alonso Cárdenas-Cárdenas & Edgar Caicedo-García & Eliana R. González Molano, 2020. "Estimación de la variación del precio de los alimentos con modelos de frecuencias mixtas," Borradores de Economia 1109, Banco de la Republica de Colombia.
    17. Wang, Ruina & Li, Jinfang, 2021. "The influence and predictive powers of mixed-frequency individual stock sentiment on stock returns," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).

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