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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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    1. 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.
    2. Baker, Malcolm & Stein, Jeremy C., 2004. "Market liquidity as a sentiment indicator," Journal of Financial Markets, Elsevier, vol. 7(3), pages 271-299, June.
    3. Malcolm Baker & Jeffrey Wurgler, 2006. "Investor Sentiment and the Cross‐Section of Stock Returns," Journal of Finance, American Finance Association, vol. 61(4), pages 1645-1680, August.
    4. Mark Hallam & Jose Olmo, 2014. "Semiparametric Density Forecasts of Daily Financial Returns from Intraday Data," Journal of Financial Econometrics, Oxford University Press, vol. 12(2), pages 408-432.
    5. Campbell, John Y. & Yogo, Motohiro, 2006. "Efficient tests of stock return predictability," Journal of Financial Economics, Elsevier, vol. 81(1), pages 27-60, July.
    6. Changyun Wang, 2003. "Investor sentiment, market timing, and futures returns," Applied Financial Economics, Taylor & Francis Journals, vol. 13(12), pages 891-898.
    7. 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.
    8. Ling Cen & Hai Lu & Liyan Yang, 2013. "Investor Sentiment, Disagreement, and the Breadth--Return Relationship," Management Science, INFORMS, vol. 59(5), pages 1076-1091, May.
    9. Eric Ghysels & Arthur Sinko & Rossen Valkanov, 2007. "MIDAS Regressions: Further Results and New Directions," Econometric Reviews, Taylor & Francis Journals, vol. 26(1), pages 53-90.
    10. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2003. "Modeling and Forecasting Realized Volatility," Econometrica, Econometric Society, vol. 71(2), pages 579-625, March.
    11. Andersen, Torben G. & Bollerslev, Tim & Lange, Steve, 1999. "Forecasting financial market volatility: Sample frequency vis-a-vis forecast horizon," Journal of Empirical Finance, Elsevier, vol. 6(5), pages 457-477, December.
    12. Changyun Wang, 2001. "Investor Sentiment and Return Predictability in Agricultural Futures Markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 21(10), pages 929-952, October.
    13. Kurov, Alexander, 2010. "Investor sentiment and the stock market's reaction to monetary policy," Journal of Banking & Finance, Elsevier, vol. 34(1), pages 139-149, January.
    14. Robin Greenwood & Andrei Shleifer, 2014. "Expectations of Returns and Expected Returns," The Review of Financial Studies, Society for Financial Studies, vol. 27(3), pages 714-746.
    15. Ghysels, Eric & Santa-Clara, Pedro & Valkanov, Rossen, 2004. "The MIDAS Touch: Mixed Data Sampling Regression Models," University of California at Los Angeles, Anderson Graduate School of Management qt9mf223rs, Anderson Graduate School of Management, UCLA.
    16. Robert I. Webb & David P. Simon & Roy A. Wiggins III, 2001. "S&P futures returns and contrary sentiment indicators," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 21(5), pages 447-462, May.
    17. Kim, Jun Sik & Ryu, Doojin & Seo, Sung Won, 2014. "Investor sentiment and return predictability of disagreement," Journal of Banking & Finance, Elsevier, vol. 42(C), pages 166-178.
    18. Yu, Jianfeng & Yuan, Yu, 2011. "Investor sentiment and the mean-variance relation," Journal of Financial Economics, Elsevier, vol. 100(2), pages 367-381, May.
    19. Moskowitz, Tobias J. & Ooi, Yao Hua & Pedersen, Lasse Heje, 2012. "Time series momentum," Journal of Financial Economics, Elsevier, vol. 104(2), pages 228-250.
    20. Joseph, Kissan & Babajide Wintoki, M. & Zhang, Zelin, 2011. "Forecasting abnormal stock returns and trading volume using investor sentiment: Evidence from online search," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1116-1127, October.
    21. Jegadeesh, Narasimhan & Titman, Sheridan, 1993. "Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency," Journal of Finance, American Finance Association, vol. 48(1), pages 65-91, March.
    22. Gregory W. Brown & Michael T. Cliff, 2005. "Investor Sentiment and Asset Valuation," The Journal of Business, University of Chicago Press, vol. 78(2), pages 405-440, March.
    23. Schmeling, Maik, 2009. "Investor sentiment and stock returns: Some international evidence," Journal of Empirical Finance, Elsevier, vol. 16(3), pages 394-408, June.
    24. Verma, Rahul & Soydemir, Gökçe, 2009. "The impact of individual and institutional investor sentiment on the market price of risk," The Quarterly Review of Economics and Finance, Elsevier, vol. 49(3), pages 1129-1145, August.
    25. Wang, Yaw-Huei & Keswani, Aneel & Taylor, Stephen J., 2006. "The relationships between sentiment, returns and volatility," International Journal of Forecasting, Elsevier, vol. 22(1), pages 109-123.
    26. Baker, Malcolm & Wurgler, Jeffrey & Yuan, Yu, 2012. "Global, local, and contagious investor sentiment," Journal of Financial Economics, Elsevier, vol. 104(2), pages 272-287.
    27. Fong, Wai Mun & Toh, Benjamin, 2014. "Investor sentiment and the MAX effect," Journal of Banking & Finance, Elsevier, vol. 46(C), pages 190-201.
    28. Jose A. Scheinkman & Wei Xiong, 2003. "Overconfidence and Speculative Bubbles," Journal of Political Economy, University of Chicago Press, vol. 111(6), pages 1183-1219, December.
    29. Li, Jinfang, 2014. "Multi-period sentiment asset pricing model with information," International Review of Economics & Finance, Elsevier, vol. 34(C), pages 118-130.
    30. 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.
    31. Hallam, Mark & Olmo, Jose, 2014. "Forecasting daily return densities from intraday data: A multifractal approach," International Journal of Forecasting, Elsevier, vol. 30(4), pages 863-881.
    32. Brown, Gregory W. & Cliff, Michael T., 2004. "Investor sentiment and the near-term stock market," Journal of Empirical Finance, Elsevier, vol. 11(1), pages 1-27, January.
    33. Wai Mun Fong, 2014. "The MAX Effect," Palgrave Macmillan Books, in: The Lottery Mindset: Investors, Gambling and the Stock Market, chapter 7, pages 138-155, Palgrave Macmillan.
    34. Niklas Karlsson & George Loewenstein & Duane Seppi, 2009. "The ostrich effect: Selective attention to information," Journal of Risk and Uncertainty, Springer, vol. 38(2), pages 95-115, April.
    35. Alok Kumar & Charles M.C. Lee, 2006. "Retail Investor Sentiment and Return Comovements," Journal of Finance, American Finance Association, vol. 61(5), pages 2451-2486, October.
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    Cited by:

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    3. 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.
    4. Pedro Manuel Nogueira Reis & Carlos Pinho, 2021. "A Reappraisal of the Causal Relationship between Sentiment Proxies and Stock Returns," Journal of Behavioral Finance, Taylor & Francis Journals, vol. 22(4), pages 420-442, October.
    5. 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.
    6. 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).
    7. 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).
    8. Gao, Bin & Liu, Xihua, 2020. "Intraday sentiment and market returns," International Review of Economics & Finance, Elsevier, vol. 69(C), pages 48-62.
    9. Zhou, Liyun & Huang, Jialiang, 2020. "Contagion of future-level sentiment in Chinese Agricultural Futures Markets," Pacific-Basin Finance Journal, Elsevier, vol. 61(C).
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. 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).
    16. 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.
    17. 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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