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Does Big Data Improve Financial Forecasting? The Horizon Effect

Author

Listed:
  • Olivier Dessaint
  • Thierry Foucault

    (HEC Paris - Ecole des Hautes Etudes Commerciales)

  • Laurent Frésard

Abstract

We study how data abundance affects the informativeness of financial analysts' forecasts at various horizons. Analysts produce forecasts of short-term and long-term earnings and choose how much information to collect about each horizon to minimize their expected forecasting error, net of information acquisition costs. When the cost of obtaining short-term information drops (i.e., more data becomes available), analysts change their information collection strategy in a way that renders their short-term forecasts more informative but that possibly reduces the informativeness of their long-term forecasts. Using a large sample of analysts' forecasts at various horizons and novel measures of their exposure to abundant data (e.g., social media data), we provide empirical support for this prediction, which implies that data abundance can impair the quality of long-term forecasts.

Suggested Citation

  • Olivier Dessaint & Thierry Foucault & Laurent Frésard, 2020. "Does Big Data Improve Financial Forecasting? The Horizon Effect," Working Papers hal-03031876, HAL.
  • Handle: RePEc:hal:wpaper:hal-03031876
    DOI: 10.2139/ssrn.3702411
    as

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    Keywords

    Big data; Financial analysts' forecasts; 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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