FIDAI (“Financial Information, Data Abundance and Investment) is a research project, funded by the European Union (ERC–grants program) that studies how the big data revolution affects the quality and nature of information produced in financial markets and its effects on corporate investment and asset management, combining theoretical and empirical approaches.
Main Findings
Does Alternative Data Improve Financial Forecasting? The Horizon Effect , forthcoming Journal of Finance with Olivier Dessaint and Laurent Frésard.
The rise of alternative data improves the informativeness of equity analysts’ short-term forecasts but reduce the informativeness of their long-term forecasts (chart on the left hand side).
The Horizon of Investors’ Information and Corporate Investment, with Olivier Dessaint and Laurent Frésard.
Firms with long horizon investment opportunities invest more when the informativeness of investors’ long-term forecasts increases
Equilibrium Data Mining and Data Abundance, with Jérôme Dugast; Forthcoming Journal of Finance.
Provides a theory of data mining by quant funds. Predicts that as new datasets become available, the dispersion of quant funds (data miners)’s performance increases and the capital allocated to quant funds eventually decreases.
Displaced by big data: Evidence from Active Fund Manager with Maxime Bonelli. The availability of new alternative data reduces active managers’ stock picking ability
Thierry Foucault 
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