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Sentiment-based momentum strategy

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  • Kim, Byungoh
  • Suh, Sangwon

Abstract

In this paper, we examine whether momentum profits can be predicted by sentiment and whether the momentum profit predictability is exploitable for investors. To this end, we use a novel approach by proposing a new momentum strategy that relies on the ability of sentiment to predict future momentum profits. We apply the new strategy to actual equity data and find that the new momentum strategy significantly outperforms the conventional momentum strategy. Our result more strongly supports the momentum profit predictability than usual linear predictive regressions suggest. We also present evidence that the outperformance of the new method over the conventional one is robust to various specification changes.

Suggested Citation

  • Kim, Byungoh & Suh, Sangwon, 2018. "Sentiment-based momentum strategy," International Review of Financial Analysis, Elsevier, vol. 58(C), pages 52-68.
  • Handle: RePEc:eee:finana:v:58:y:2018:i:c:p:52-68
    DOI: 10.1016/j.irfa.2018.04.004
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    Cited by:

    1. Song, Ziyu & Gong, Xiaomin & Zhang, Cheng & Yu, Changrui, 2023. "Investor sentiment based on scaled PCA method: A powerful predictor of realized volatility in the Chinese stock market," International Review of Economics & Finance, Elsevier, vol. 83(C), pages 528-545.
    2. Kim, Byungoh & Suh, Sangwon, 2021. "Overnight stock returns, intraday returns, and firm-specific investor sentiment," The North American Journal of Economics and Finance, Elsevier, vol. 55(C).
    3. Mehdi Zolfaghari & Bahram Sahabi, 2021. "The impact of oil price and exchange rate on momentum strategy profits in stock market: evidence from oil-rich developing countries," Review of Managerial Science, Springer, vol. 15(7), pages 1981-2023, October.
    4. Mohamed Sahbi Nakhli & Abderrazak Dhaoui & Julien Chevallier, 2022. "Bootstrap rolling-window Granger causality dynamics between momentum and sentiment: implications for investors," Annals of Finance, Springer, vol. 18(2), pages 267-283, June.
    5. Hung-Wen Lin & Kun-Ben Lin & Jing-Bo Huang & Shu-Heng Chen, 2021. "Timely Loss Recognition Helps Nothing," Sustainability, MDPI, vol. 13(14), pages 1-24, July.
    6. Song, Ziyu & Yu, Changrui, 2022. "Investor sentiment indices based on k-step PLS algorithm: A group of powerful predictors of stock market returns," International Review of Financial Analysis, Elsevier, vol. 83(C).
    7. Elie Bouri & Riza Demirer & David Gabauer & Rangan Gupta, 2020. "Sentiment and Financial Market Connectedness: The Role of Investor Happiness," Working Papers 202022, University of Pretoria, Department of Economics.
    8. Sadaqat, Mohsin & Butt, Hilal Anwar, 2023. "Stop-loss rules and momentum payoffs in cryptocurrencies," Journal of Behavioral and Experimental Finance, Elsevier, vol. 39(C).
    9. Wouassom, Alain & Muradoğlu, Yaz Gülnur & Tsitsianis, Nicholas, 2022. "Global momentum: The optimal trading approach," Journal of Behavioral and Experimental Finance, Elsevier, vol. 36(C).
    10. Kim, Karam & Ryu, Doojin & Yang, Heejin, 2021. "Information uncertainty, investor sentiment, and analyst reports," International Review of Financial Analysis, Elsevier, vol. 77(C).

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    More about this item

    Keywords

    Sentiment; Momentum; Momentum profit predictability; Portfolio performance;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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