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Popular Music, Sentiment, and Noise Trading

Kaivanto, Kim and Zhang, Peng (2019) Popular Music, Sentiment, and Noise Trading. Working Paper. Lancaster University, Department of Economics, Lancaster.

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Abstract

We construct a sentiment indicator as the first principal component of thirteen emotion metrics derived from the lyrics and composition of music-chart singles. This indicator performs well, dominating the Michigan Index of Consumer Sentiment and bettering the Baker-Wurgler index in long-horizon regression tests as well as in out-of-sample forecasting tests. The music-sentiment indicator captures both signal and noise. The part associated with fundamentals predicts more distant market returns positively. The second part is orthogonal to fundamentals, and predicts one-month-ahead market returns negatively. This is evidence of noise trading explained by the emotive content of popular music.

Item Type:
Monograph (Working Paper)
Subjects:
?? investor sentimentstock-return predictabilitybig datatextual analysisnatural language processingpopular musicnoise tradingbehavioural financeg12g17c55 ??
Departments:
Lancaster University Management School > Economics
ID Code:
138535
Deposited By:
ep_importer_pure
Deposited On:
01 Nov 2019 14:00
Refereed?:
No
Published?:
Published
Last Modified:
31 Dec 2023 01:27
URI:
https://eprints.lancs.ac.uk/id/eprint/138535