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The long of it: Odds that investor sentiment spuriously predicts anomaly returns

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  • Stambaugh, Robert F.
  • Yu, Jianfeng
  • Yuan, Yu

Abstract

Extremely long odds accompany the chance that spurious-regression bias accounts for investor sentiment׳s observed role in stock-return anomalies. We replace investor sentiment with a simulated persistent series in regressions reported by Stambaugh, Yu, and Yuan (2012), who find higher long-short anomaly profits following high sentiment, due entirely to the short leg. Among 200 million simulated regressors, we find none that support those conclusions as strongly as investor sentiment. The key is consistency across anomalies. Obtaining just the predicted signs for the regression coefficients across the 11 anomalies examined in the above study occurs only once for every 43 simulated regressors.

Suggested Citation

  • Stambaugh, Robert F. & Yu, Jianfeng & Yuan, Yu, 2014. "The long of it: Odds that investor sentiment spuriously predicts anomaly returns," Journal of Financial Economics, Elsevier, vol. 114(3), pages 613-619.
  • Handle: RePEc:eee:jfinec:v:114:y:2014:i:3:p:613-619
    DOI: 10.1016/j.jfineco.2014.07.008
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    4. Papapostolou, Nikos C. & Pouliasis, Panos K. & Nomikos, Nikos K. & Kyriakou, Ioannis, 2016. "Shipping investor sentiment and international stock return predictability," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 96(C), pages 81-94.
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    6. Yang, Chunpeng & Zhou, Liyun, 2015. "Investor trading behavior, investor sentiment and asset prices," The North American Journal of Economics and Finance, Elsevier, vol. 34(C), pages 42-62.
    7. Jacobs, Heiko, 2016. "Market maturity and mispricing," Journal of Financial Economics, Elsevier, vol. 122(2), pages 270-287.
    8. Robert F. Stambaugh & Yu Yuan, 2017. "Mispricing Factors," Review of Financial Studies, Society for Financial Studies, vol. 30(4), pages 1270-1315.
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    10. Bucher, Melk C., 2017. "Investor Attention and Sentiment: Risk or Anomaly?," Working Papers on Finance 1712, University of St. Gallen, School of Finance.
    11. repec:eee:ecofin:v:47:y:2019:i:c:p:365-379 is not listed on IDEAS
    12. Xiaomeng Lu & Robert F. Stambaugh & Yu Yuan, 2017. "Anomalies Abroad: Beyond Data Mining," NBER Working Papers 23809, National Bureau of Economic Research, Inc.
    13. Labidi, Chiraz & Yaakoubi, Soumaya, 2016. "Investor sentiment and aggregate volatility pricing," The Quarterly Review of Economics and Finance, Elsevier, vol. 61(C), pages 53-63.
    14. Jacobs, Heiko, 2015. "What explains the dynamics of 100 anomalies?," Journal of Banking & Finance, Elsevier, vol. 57(C), pages 65-85.
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    20. Sibley, Steven E. & Wang, Yanchu & Xing, Yuhang & Zhang, Xiaoyan, 2016. "The information content of the sentiment index," Journal of Banking & Finance, Elsevier, vol. 62(C), pages 164-179.
    21. repec:eee:finlet:v:22:y:2017:i:c:p:1-4 is not listed on IDEAS

    More about this item

    Keywords

    Investor sentiment; Anomalies; Spurious regressors;

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General

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