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Music and the market: Song and stock volatility

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  • Maymin, Philip

Abstract

Popular music may presage market conditions because people contemplating complex future economic behavior prefer simpler music, and vice versa. In comparing the annual average beat variance of the songs in the U.S. Billboard Top 100 since its inception in 1958 through 2007 to the standard deviation of returns of the S&P 500 for the same or the subsequent year, a significant negative correlation is observed. Furthermore, the beat variance appears able to predict future market volatility, producing 2.5 volatility points of profit per year on average.

Suggested Citation

  • Maymin, Philip, 2012. "Music and the market: Song and stock volatility," The North American Journal of Economics and Finance, Elsevier, vol. 23(1), pages 70-85.
    • Handle: RePEc:eee:ecofin:v:23:y:2012:i:1:p:70-85
    DOI: 10.1016/j.najef.2011.11.004
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    References listed on IDEAS

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    Cited by:

    1. Yiming Liu & Longxin Wang & Yunsong Jia & Ziwen Li & Hongju Gao, 2021. "Dynamic Influence Ranking Algorithm Based on Musicians’ Social and Personal Information Network," Mathematics, MDPI, vol. 9(20), pages 1-19, October.
    2. Liao, Li-Chuan & Chou, Ray Yeutien & Chiu, Banghan, 2013. "Anchoring effect on foreign institutional investors’ momentum trading behavior: Evidence from the Taiwan stock market," The North American Journal of Economics and Finance, Elsevier, vol. 26(C), pages 72-91.
    3. Basak, Suryoday & Kar, Saibal & Saha, Snehanshu & Khaidem, Luckyson & Dey, Sudeepa Roy, 2019. "Predicting the direction of stock market prices using tree-based classifiers," The North American Journal of Economics and Finance, Elsevier, vol. 47(C), pages 552-567.

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