Music sentiment and the cross-section of stock returns in the US

Authors

  • Shiqi Chen School of Economics and Management, Nanjing University of Science and Technology, Nanjing 210094, China
  • Yiwei Wang School of Economics and Management, Nanjing University of Science and Technology, Nanjing 210094, China
  • Huiyi Zhang School of Economics and Management, Nanjing University of Science and Technology, Nanjing 210094, China
  • Jie Zhou School of Economics and Management, Nanjing University of Science and Technology, Nanjing 210094, China

DOI:

https://doi.org/10.62051/xhj6bx84

Keywords:

Music sentiment; Asset pricing; Asymmetry; Cross-sectional stock returns.

Abstract

This paper examines the role of music sentiment, which endogenously measures investor sentiment, in the cross-sectional pricing of individual stocks in the US. We estimate individual stocks' exposure to country-level music sentiment and find that, following periods of low music sentiment, stocks with the highest sentiment beta significantly outperform those with the lowest sentiment beta on a daily basis in the future on a risk-adjusted basis. However, this return spread is not significant following high-sentiment periods, demonstrating an asymmetric pricing effect. This finding is consistent with the argument that overpricing following high-sentiment periods is more prevalent than underpricing following low-sentiment periods because of short-sale constraints.

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References

[1] Amihud, Y. (2002). Illiquidity and stock returns: Cross-section and time-series effects. Journal of Financial Markets, 5 (1), 31 – 56. DOI: https://doi.org/10.1016/S1386-4181(01)00024-6

[2] Baker, M., & Wurgler, J. (2006). Investor sentiment and the cross-section of stock returns. The Journal of Finance, 61 (4), 1645 – 1680. DOI: https://doi.org/10.1111/j.1540-6261.2006.00885.x

[3] Chen, Y., Han, B., & Pan, J. (2021). Sentiment trading and hedge fund returns. The Journal of Finance, 76 (4), 2001 – 2033. DOI: https://doi.org/10.1111/jofi.13025

[4] Chen, Z., Da, Z., Huang, D., & Wang, L. (2023). Presidential economic approval rating and the cross-section of stock returns. Journal of Financial Economics, 147 (1), 106– 131. DOI: https://doi.org/10.1016/j.jfineco.2022.10.004

[5] Da, Z., Engelberg, J., & Gao, P. (2015). The sum of all FEARS: Investor sentiment and asset prices. The Review of Financial Studies, 28 (1), 1 – 32. DOI: https://doi.org/10.1093/rfs/hhu072

[6] De Long, J. B., Shleifer, A., Summers, L. H., & Waldmann, R. J. (1990). Noise trader risk in financial markets. Journal of Political Economy, 98 (4), 703 – 738. DOI: https://doi.org/10.1086/261703

[7] Edmans, A., Fernandez-Perez, A., Garel, A., & Indriawan, I. (2022). Music sentiment and stock returns around the world. Journal of Financial Economics, 145 (2), 234 – 254. DOI: https://doi.org/10.1016/j.jfineco.2021.08.014

[8] Fama, E. F., & French, K. R. (1992). The cross-section of expected stock returns. The Journal of Finance, 47 (2), 427 – 465. DOI: https://doi.org/10.1111/j.1540-6261.1992.tb04398.x

[9] Fama, E. F., & French, K. R. (2015). A five-factor asset pricing model. Journal of Financial Economics, 116 (1), 1 – 22. DOI: https://doi.org/10.1016/j.jfineco.2014.10.010

[10] Glushkov, D. (2006). Sentiment beta (SSRN Working Paper No. 862444). Social Science Research Network. DOI: https://doi.org/10.2139/ssrn.862444

[11] Greenberg, D. M., Kosinski, M., Stillwell, D. J., Monteiro, B. L., Levitin, D. J., & Rentfrow, P. J. (2016). The song is you: Preferences for musical attribute dimensions reflects personality. Social Psychological and Personality Science, 7 (6), 597 – 605. DOI: https://doi.org/10.1177/1948550616641473

[12] Ho, J. C., & Hung, C. H. D. (2012). Predicting stock market returns and volatility with investor sentiment: Evidence from eight developed countries (SSRN Working Paper No. 2279339). Social Science Research Network. DOI: https://doi.org/10.2139/ssrn.2279339

[13] Hunter, P. G., Schellenberg, E. G., & Griffith, A. T. (2011). Misery loves company: Mood-congruent emotional responding to music. Emotion, 11 (5), 1068 – 1072. DOI: https://doi.org/10.1037/a0023749

[14] Jacoby, G., Liao, C., Lin, N., & Lu, L. (2024). Sentiment and the cross-section of expected stock returns. Financial Review, 59 (2), 459 – 485. DOI: https://doi.org/10.1111/fire.12380

[15] Kozak, S., Nagel, S., & Santosh, S. (2018). Interpreting factor models. The Journal of Finance, 73 (3), 1183 – 1223. DOI: https://doi.org/10.1111/jofi.12612

[16] Lee, C. M., Shleifer, A., & Thaler, R. H. (1991). Investor sentiment and the closed-end fund puzzle. The Journal of Finance, 46 (1), 75 – 109. DOI: https://doi.org/10.1111/j.1540-6261.1991.tb03746.x

[17] Lee, W. Y., Jiang, C. X., & Indro, D. C. (2002). Stock market volatility, excess returns, and the role of investor sentiment. Journal of Banking & Finance, 26 (12), 2277 – 2299. DOI: https://doi.org/10.1016/S0378-4266(01)00202-3

[18] Liang, S. X. (2018). The systematic pricing of market sentiment shock. The European Journal of Finance, 24 (18), 1835 – 1860. DOI: https://doi.org/10.1080/1351847X.2018.1491875

[19] Mehr, S. A., Singh, M., Knox, D., Ketter, D. M., Pickens-Jones, D., Atwood, S., Lucas, C., Jacoby, N., Egner, A. A., Pearson, P., Vallier, L., Lamarre, B. T., Bovin, J., Rosen, A. F. G., Kim, J. C., Gordon, I. J., Brand, C. M., Trach, M. R., McCall, J., ... Glowacki, L. (2019). Universality and diversity in human song. Science, 366 (6468), Article eaax0868. DOI: https://doi.org/10.1126/science.aax0868

[20] Nagel, S. (2005). Short sales, institutional investors, and the cross-section of stock returns. Journal of Financial Economics, 78 (2), 277 – 309. DOI: https://doi.org/10.1016/j.jfineco.2004.08.008

[21] Newey, W. K., & West, K. D. (1987). A simple, positive semi-definite, heteroskedasticity and autocorrelation consistent covariance matrix. Econometrica, 55 (3), 703 – 708. DOI: https://doi.org/10.2307/1913610

[22] Obaid, K., & Pukthuanthong, K. (2022). A picture is worth a thousand words: Measuring investor sentiment by combining machine learning and photos from news. Journal of Financial Economics, 144 (1), 273 – 297. DOI: https://doi.org/10.1016/j.jfineco.2021.06.002

[23] Shen, J., Yu, J., & Zhao, S. (2017). Investor sentiment and economic forces. Journal of Monetary Economics, 86, 1 – 21. DOI: https://doi.org/10.1016/j.jmoneco.2017.01.001

[24] Stambaugh, R. F., Yu, J., & Yuan, Y. (2012). The short of it: Investor sentiment and anomalies. Journal of Financial Economics, 104 (2), 288 – 302. DOI: https://doi.org/10.1016/j.jfineco.2011.12.001

[25] Stambaugh, R. F., Yu, J., & Yuan, Y. (2015). Arbitrage asymmetry and the idiosyncratic volatility puzzle. The Journal of Finance, 70 (5), 1903 – 1948. DOI: https://doi.org/10.1111/jofi.12286

[26] Xie, Y., Peng, H., & Feng, T. (2024). Pricing stock index futures with sentiments. Finance Research Letters, 61, Article 104980. DOI: https://doi.org/10.1016/j.frl.2024.104980

[27] Zhang, Y., He, M., Liao, C., & Wang, Y. (2023). Climate risk exposure and the cross-section of Chinese stock returns. Finance Research Letters, 55, Article 103987. DOI: https://doi.org/10.1016/j.frl.2023.103987

[28] Zhang, Y., Zhang, Y., Ren, X., & Jin, M. (2024). Geopolitical risk exposure and stock returns: Evidence from China. Finance Research Letters, 64, Article 105479. DOI: https://doi.org/10.1016/j.frl.2024.105479

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Published

27-11-2025

How to Cite

Chen, S., Wang, Y., Zhang, H., & Zhou, J. (2025). Music sentiment and the cross-section of stock returns in the US. Transactions on Economics, Business and Management Research, 15, 399-406. https://doi.org/10.62051/xhj6bx84