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Does Alternative Data Improve Financial Forecasting? The Horizon Effect

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  • Foucault, Thierry
  • Frésard, Laurent

Abstract

We analyze the effect of alternative data on the informativeness of financial forecasts. Our starting hypothesis is that the emergence of alternative data reduces the cost of obtaining information about firms' short-term cash-flows more than their long-term cash-flows. If correct, and forecasting short-term and long-term cash-flows are distinct tasks, analysts will reduce effort to process long-term information when alternative data become available. Alternative data thus makes long-term forecasts less informative, while increasing the informativeness of short-term forecasts. We confirm this prediction using variations in analysts' exposure to social media data and a new measure of forecast informativeness at various horizons.

Suggested Citation

  • Foucault, Thierry & Frésard, Laurent, 2021. "Does Alternative Data Improve Financial Forecasting? The Horizon Effect," CEPR Discussion Papers 15786, C.E.P.R. Discussion Papers.
  • Handle: RePEc:cpr:ceprdp:15786
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    as
    1. Shiyang Huang & Yan Xiong & Liyan Yang, 2022. "Skill Acquisition and Data Sales," Management Science, INFORMS, vol. 68(8), pages 6116-6144, August.
    2. Jules H. van Binsbergen & Xiao Han & Alejandro Lopez-Lira, 2020. "Man vs. Machine Learning: The Term Structure of Earnings Expectations and Conditional Biases," NBER Working Papers 27843, National Bureau of Economic Research, Inc.
    3. Edmans, Alex & Jayaraman, Sudarshan & Schneemeier, Jan, 2017. "The source of information in prices and investment-price sensitivity," Journal of Financial Economics, Elsevier, vol. 126(1), pages 74-96.
    4. François Derrien & Ambrus Kecskés, 2013. "The Real Effects of Financial Shocks: Evidence from Exogenous Changes in Analyst Coverage," Post-Print hal-00852356, HAL.
    5. Hirshleifer, David & Levi, Yaron & Lourie, Ben & Teoh, Siew Hong, 2019. "Decision fatigue and heuristic analyst forecasts," Journal of Financial Economics, Elsevier, vol. 133(1), pages 83-98.
    6. Bai, Jennie & Philippon, Thomas & Savov, Alexi, 2016. "Have financial markets become more informative?," Journal of Financial Economics, Elsevier, vol. 122(3), pages 625-654.
    7. Meng Gao & Jiekun Huang & Itay Goldstein, 2020. "Informing the Market: The Effect of Modern Information Technologies on Information Production," The Review of Financial Studies, Society for Financial Studies, vol. 33(4), pages 1367-1411.
    8. Meng Gao & Jiekun Huang & Itay GoldsteinEditor, 2020. "Informing the Market: The Effect of Modern Information Technologies on Information Production," Review of Finance, European Finance Association, vol. 33(4), pages 1367-1411.
    9. Froot, Kenneth & Kang, Namho & Ozik, Gideon & Sadka, Ronnie, 2017. "What do measures of real-time corporate sales say about earnings surprises and post-announcement returns?," Journal of Financial Economics, Elsevier, vol. 125(1), pages 143-162.
    10. Juliane Begenau & Maryam Farboodi & Laura Veldkamp, 2018. "Big Data in Finance and the Growth of Large Firms," Working Papers 18-08, New York University, Leonard N. Stern School of Business, Department of Economics.
    11. Juliane Begenau & Maryam Farboodi & Laura Veldkamp, 2018. "Big Data in Finance and the Growth of Large Firms," NBER Working Papers 24550, National Bureau of Economic Research, Inc.
    12. Martin, Ian W.R. & Nagel, Stefan, 2022. "Market efficiency in the age of big data," Journal of Financial Economics, Elsevier, vol. 145(1), pages 154-177.
    13. Juliane Begenau & Laura Veldkamp & Maryam Farboodi, 2018. "Big Data in Finance and the Growth of Large Firms," 2018 Meeting Papers 155, Society for Economic Dynamics.
    14. J Anthony Cookson & Joseph E Engelberg & William Mullins & Hui Chen, 0. "Does Partisanship Shape Investor Beliefs? Evidence from the COVID-19 Pandemic," The Review of Asset Pricing Studies, Society for Financial Studies, vol. 10(4), pages 863-893.
    15. Long Chen & Zhi Da & Xinlei Zhao, 2013. "What Drives Stock Price Movements?," The Review of Financial Studies, Society for Financial Studies, vol. 26(4), pages 841-876.
    16. Christina Zhu, 2019. "Big Data as a Governance Mechanism," The Review of Financial Studies, Society for Financial Studies, vol. 32(5), pages 2021-2061.
    17. Bandyopadhyay, Sati P. & Brown, Lawrence D. & Richardson, Gordon D., 1995. "Analysts' use of earnings forecasts in predicting stock returns: Forecast horizon effects," International Journal of Forecasting, Elsevier, vol. 11(3), pages 429-445, September.
    18. John Y. Campbell & Samuel B. Thompson, 2008. "Predicting Excess Stock Returns Out of Sample: Can Anything Beat the Historical Average?," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1509-1531, July.
    19. Mest, David P. & Plummer, Elizabeth, 1999. "Transitory and persistent earnings components as reflected in analysts' short-term and long-term earnings forecasts: evidence from a nonlinear model," International Journal of Forecasting, Elsevier, vol. 15(3), pages 291-308, July.
    20. Kenneth Merkley & Roni Michaely & Joseph Pacelli, 2017. "Does the Scope of the Sell-Side Analyst Industry Matter? An Examination of Bias, Accuracy, and Information Content of Analyst Reports," Journal of Finance, American Finance Association, vol. 72(3), pages 1285-1334, June.
    21. François Derrien & Ambrus Kecskés, 2013. "The Real Effects of Financial Shocks: Evidence from Exogenous Changes in Analyst Coverage," Journal of Finance, American Finance Association, vol. 68(4), pages 1407-1440, August.
    22. Dugast, Jérôme & Foucault, Thierry, 2018. "Data abundance and asset price informativeness," Journal of Financial Economics, Elsevier, vol. 130(2), pages 367-391.
    23. Alan Crane & Kevin Crotty, 2020. "How Skilled Are Security Analysts?," Journal of Finance, American Finance Association, vol. 75(3), pages 1629-1675, June.
    24. Green, T. Clifton & Huang, Ruoyan & Wen, Quan & Zhou, Dexin, 2019. "Crowdsourced employer reviews and stock returns," Journal of Financial Economics, Elsevier, vol. 134(1), pages 236-251.
    25. J. Anthony Cookson & Marina Niessner, 2020. "Why Don't We Agree? Evidence from a Social Network of Investors," Journal of Finance, American Finance Association, vol. 75(1), pages 173-228, February.
    26. Hailiang Chen & Prabuddha De & Yu (Jeffrey) Hu & Byoung-Hyoun Hwang, 2014. "Wisdom of Crowds: The Value of Stock Opinions Transmitted Through Social Media," The Review of Financial Studies, Society for Financial Studies, vol. 27(5), pages 1367-1403.
    27. Gilles Hilary & Charles Hsu, 2013. "Analyst Forecast Consistency," Journal of Finance, American Finance Association, vol. 68(1), pages 271-297, February.
    28. Tim de Silva & David Thesmar, 2021. "Noise in Expectations: Evidence from Analyst Forecasts," NBER Working Papers 28963, National Bureau of Economic Research, Inc.
    29. Itay Goldstein & Liyan Yang, 2015. "Information Diversity and Complementarities in Trading and Information Acquisition," Journal of Finance, American Finance Association, vol. 70(4), pages 1723-1765, August.
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    Cited by:

    1. Guy Aridor & Rafael Jiménez-Durán & Ro'ee Levy & Lena Song, 2024. "The Economics of Social Media," Journal of Economic Literature, American Economic Association, vol. 62(4), pages 1422-1474, December.
    2. Ben-Rephael, Azi & Cookson, J. Anthony & izhakian, yehuda, 2022. "Do I Really Want to Hear The News? Public Information Arrival and Investor Beliefs," SocArXiv ud7yw, Center for Open Science.

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    More about this item

    Keywords

    Alternative data; Security analysts; Forecasting horizon; Forecasts' informativeness; Social media;
    All these keywords.

    JEL classification:

    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • M41 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Accounting - - - Accounting

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