Does Alternative Data Improve Financial Forecasting? The Horizon Effect

• 成果类型: Article
• 署名作者: Dessaint, Olivier; Foucault, Thierry; Fresard, Laurent
• 署名单位: INSEAD Business School; Hautes Etudes Commerciales (HEC) Paris; Universita della Svizzera Italiana; INSEAD Business School
• 刊物名称: JOURNAL OF FINANCE
• ISSN/ISSBN: 0022-1082
• DOI: 10.1111/jofi.13323
• 发表日期: 2024
• 页码: 2237-2287
• 关键词: EARNINGS FORECASTS; stock returns; ANALYSTS USE; big data; INFORMATION; GROWTH; term; sample; matter

摘要

Existing research suggests that alternative data are mainly informative about short-term future outcomes. We show theoretically that the availability of short-term-oriented data can induce forecasters to optimally shift their attention from the long term to the short term because it reduces the cost of obtaining short-term information. Consequently, the informativeness of their long-term forecasts decreases, even though the informativeness of their short-term forecasts increases. We test and confirm this prediction by considering how the informativeness of equity analysts' forecasts at various horizons varies over the long run and with their exposure to social media data.