Does Big Data Improve Financial Forecasting? The Horizon Effect

Olivier Dessaint, Thierry Foucault and Laurent Frésard
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Olivier Dessaint: INSEAD
Laurent Frésard: Universita della Svizzera italiana (USI Lugano); Swiss Finance Institute

No 20-106, Swiss Finance Institute Research Paper Series from Swiss Finance Institute

Abstract: We study how data abundance affects the informativeness of financial analysts' forecasts at various horizons. Analysts forecast short-term and long-term earnings and choose how much information to process about each horizon to minimize forecasting error, net of information processing costs. When the cost of obtaining short-term information drops (i.e., more data becomes available), analysts change their information processing strategy in a way that renders their short-term forecasts more informative but that possibly reduces the informativeness of their long-term forecasts. We provide empirical support for this prediction using a large sample of forecasts at various horizons and novel measures of analysts' exposure to abundant data. Data abundance can thus impair the quality of long-term financial forecasts.ty of long-term forecasts.

Keywords: Big data; Financial analysts' forecasts; Forecasting horizon; Forecasts' informativeness; Social media (search for similar items in EconPapers)
JEL-codes: D84 G14 G17 M41 (search for similar items in EconPapers)
Pages: 62 pages
Date: 2020-11
New Economics Papers: this item is included in nep-big, nep-for and nep-ore
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Related works:
Working Paper: Does Big Data Improve Financial Forecasting? The Horizon Effect (2020)
Working Paper: Does Big Data Improve Financial Forecasting? The Horizon Effect (2020)
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Persistent link: https://EconPapers.repec.org/RePEc:chf:rpseri:rp20106

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