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The S&P 500 sectoral indices responses to economic news sentiment

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  • Mohamed Arbi Madani

Abstract

This study explores the dynamic relationship between economic news sentiment and the US stock market using a non‐linear empirical framework. The analysis focuses on both sectoral indices and the aggregate stock market index from November 2011 to November 2021. Using causality tests and a rolling window detrended cross‐correlation coefficient, the study reveals several key findings. First, the causal effect of investor sentiment on sectoral returns varies over time, with each sector responding differently. Second, while no evidence of dependence exists for time scales less than 2 months, a positive relationship emerges for time scales greater than 6 months, except for the utilities sector, which is found to be negative. Third, the study shows that the relationships between all pairs of variables are time‐dependent. Finally, economic news sentiment might have a varying impact on market inefficiency over different periods, making it challenging to predict market behaviour based on sentiment data.

Suggested Citation

  • Mohamed Arbi Madani, 2025. "The S&P 500 sectoral indices responses to economic news sentiment," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 30(2), pages 2042-2060, April.
    • Handle: RePEc:wly:ijfiec:v:30:y:2025:i:2:p:2042-2060
    DOI: 10.1002/ijfe.2989
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    1. Baker, Malcolm & Stein, Jeremy C., 2004. "Market liquidity as a sentiment indicator," Journal of Financial Markets, Elsevier, vol. 7(3), pages 271-299, June.
    2. Peter C. B. Phillips & Shuping Shi & Jun Yu, 2015. "Testing For Multiple Bubbles: Limit Theory Of Real‐Time Detectors," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 56, pages 1079-1134, November.
    3. repec:bla:jfinan:v:53:y:1998:i:6:p:1839-1885 is not listed on IDEAS
    4. David E. Allen & Michael McAleer & Abhay K. Singh, 2019. "Daily market news sentiment and stock prices," Applied Economics, Taylor & Francis Journals, vol. 51(30), pages 3212-3235, June.
    5. Steven L. Heston & Nitish Ranjan Sinha, 2017. "News vs. Sentiment: Predicting Stock Returns from News Stories," Financial Analysts Journal, Taylor & Francis Journals, vol. 73(3), pages 67-83, July.
    6. De Bondt, Werner F M & Thaler, Richard, 1985. "Does the Stock Market Overreact?," Journal of Finance, American Finance Association, vol. 40(3), pages 793-805, July.
    7. Zied Ftiti & Fredj Jawadi & Wael Louhichi & Mohamed El Arbi Madani, 2021. "Are oil and gas futures markets efficient? A multifractal analysis," Applied Economics, Taylor & Francis Journals, vol. 53(2), pages 164-184, January.
    8. Shuping Shi & Stan Hurn & Peter C B Phillips, 2020. "Causal Change Detection in Possibly Integrated Systems: Revisiting the Money–Income Relationship [Energy Consumption and Economic Growth in the United States]," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 18(1), pages 158-180.
    9. Shuping Shi & Peter C. B. Phillips & Stan Hurn, 2018. "Change Detection and the Causal Impact of the Yield Curve," Journal of Time Series Analysis, Wiley Blackwell, vol. 39(6), pages 966-987, November.
    10. Tiwari, Aviral Kumar & Abakah, Emmanuel Joel Aikins & Bonsu, Christiana Osei & Karikari, Nana Kwasi & Hammoudeh, Shawkat, 2022. "The effects of public sentiments and feelings on stock market behavior: Evidence from Australia," Journal of Economic Behavior & Organization, Elsevier, vol. 193(C), pages 443-472.
    11. Shapiro, Adam Hale & Sudhof, Moritz & Wilson, Daniel J., 2022. "Measuring news sentiment," Journal of Econometrics, Elsevier, vol. 228(2), pages 221-243.
    12. Tabak, Benjamin M. & Cajueiro, Daniel O., 2007. "Are the crude oil markets becoming weakly efficient over time? A test for time-varying long-range dependence in prices and volatility," Energy Economics, Elsevier, vol. 29(1), pages 28-36, January.
    13. Matthias W. Uhl, 2014. "Reuters Sentiment and Stock Returns," Journal of Behavioral Finance, Taylor & Francis Journals, vol. 15(4), pages 287-298, October.
    14. Rehman, Mobeen Ur & Sensoy, Ahmet & Eraslan, Veysel & Shahzad, Syed Jawad Hussain & Vo, Xuan Vinh, 2021. "Sensitivity of US equity returns to economic policy uncertainty and investor sentiments," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    15. Gao, Lin & Süss, Stephan, 2015. "Market sentiment in commodity futures returns," Journal of Empirical Finance, Elsevier, vol. 33(C), pages 84-103.
    16. Audrino, Francesco & Sigrist, Fabio & Ballinari, Daniele, 2020. "The impact of sentiment and attention measures on stock market volatility," International Journal of Forecasting, Elsevier, vol. 36(2), pages 334-357.
    17. Gu, Rongbao & Zhang, Bing, 2016. "Is efficiency of crude oil market affected by multifractality? Evidence from the WTI crude oil market," Energy Economics, Elsevier, vol. 53(C), pages 151-158.
    18. Kearney, Colm & Liu, Sha, 2014. "Textual sentiment in finance: A survey of methods and models," International Review of Financial Analysis, Elsevier, vol. 33(C), pages 171-185.
    19. CURATOLA, Giuliano & DONADELLI, Michael & KIZYS, Renatas & RIEDEL, Max, 2016. "Investor Sentiment and Sectoral Stock Returns: Evidence from World Cup Games," Finance Research Letters, Elsevier, vol. 17(C), pages 267-274.
    20. Groß-Klußmann, Axel & Hautsch, Nikolaus, 2011. "When machines read the news: Using automated text analytics to quantify high frequency news-implied market reactions," Journal of Empirical Finance, Elsevier, vol. 18(2), pages 321-340, March.
    21. Peter C. B. Phillips & Shuping Shi & Jun Yu, 2015. "Testing For Multiple Bubbles: Limit Theory Of Real‐Time Detectors," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 56(4), pages 1079-1134, November.
    22. Rilwan Sakariyahu & Mohamed Sherif & Audrey Paterson & Eleni Chatzivgeri, 2021. "Sentiment‐Apt investors and UK sector returns," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 3321-3351, July.
    23. Swanson, Norman R., 1998. "Money and output viewed through a rolling window," Journal of Monetary Economics, Elsevier, vol. 41(3), pages 455-474, May.
    24. Harrison Hong & Jeremy C. Stein, 1999. "A Unified Theory of Underreaction, Momentum Trading, and Overreaction in Asset Markets," Journal of Finance, American Finance Association, vol. 54(6), pages 2143-2184, December.
    25. Mobeen Ur Rehman & Nicholas Apergis, 2020. "Do global sentiment shocks spillover towards emerging and frontier markets?," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 47(3), pages 433-465, February.
    26. Hongli Niu & Yao Lu & Weiqing Wang, 2021. "Does investor sentiment differently affect stocks in different sectors? Evidence from China," International Journal of Emerging Markets, Emerald Group Publishing Limited, vol. 18(9), pages 3224-3244, October.
    27. Paul C. Tetlock, 2007. "Giving Content to Investor Sentiment: The Role of Media in the Stock Market," Journal of Finance, American Finance Association, vol. 62(3), pages 1139-1168, June.
    28. Wang, Yudong & Liu, Li, 2010. "Is WTI crude oil market becoming weakly efficient over time?: New evidence from multiscale analysis based on detrended fluctuation analysis," Energy Economics, Elsevier, vol. 32(5), pages 987-992, September.
    29. Zeitun, Rami & Rehman, Mobeen Ur & Ahmad, Nasir & Vo, Xuan Vinh, 2023. "The impact of Twitter-based sentiment on US sectoral returns," The North American Journal of Economics and Finance, Elsevier, vol. 64(C).
    30. Tim Loughran & Bill Mcdonald, 2011. "When Is a Liability Not a Liability? Textual Analysis, Dictionaries, and 10‐Ks," Journal of Finance, American Finance Association, vol. 66(1), pages 35-65, February.
    31. Audrino, Francesco & Tetereva, Anastasija, 2019. "Sentiment spillover effects for US and European companies," Journal of Banking & Finance, Elsevier, vol. 106(C), pages 542-567.
    32. Khan, Muhammad Asif & Hernandez, Jose Arreola & Shahzad, Syed Jawad Hussain, 2020. "Time and frequency relationship between household investors’ sentiment index and US industry stock returns," Finance Research Letters, Elsevier, vol. 36(C).
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