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FIDAI

Financiado

Financial Information Data Abundance and Investment

"Thierry Foucault ERC ADG 2020 Recent years have witnessed a massive growth in the volume and variety of data (""Data Abundance""). In parallel, thanks to progress in computing power, new techniques (Artificial Intelligence) have... ver más

30/06/2026

ETABLISSEMENT DENS...

1M€

Presupuesto del proyecto: 1M€

Líder del proyecto

ETABLISSEMENT DENSEIGNEMENT SUPERIEUR CONSULA... No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Ver 2 Participantes

Financiación concedida El organismo H2020 notifico la concesión del proyecto el día 2021-06-13

Línea de financiación objetivo El proyecto se financió a través de la siguiente ayuda:

ERC-2020-ADG: ERC ADVANCED GRANT

I+D

Cerrada hace 4 años

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2 Participantes

ETABLISSEMENT DENSEIGNEMENT...

1.10M€ | Lider

ARTESANOS QUESEROS MANCHEGOS

627.09K€ | Participante

Últimas noticias

29-11-2024: IDAE En las últimas 48 horas el Organismo IDAE ha otorgado 4 concesiones

29-11-2024: ECE En las últimas 48 horas el Organismo ECE ha otorgado 2 concesiones

29-11-2024: CMVAMADRID En las últimas 48 horas el Organismo CMVAMADRID ha otorgado 37 concesiones

Duración del proyecto: 60 meses Fecha Inicio: 2021-06-13
Fecha Fin: 2026-06-30

Presupuesto del proyecto 1M€

Descripción del proyecto "Thierry Foucault ERC ADG 2020 Recent years have witnessed a massive growth in the volume and variety of data (""Data Abundance""). In parallel, thanks to progress in computing power, new techniques (Artificial Intelligence) have emerged to harness the information in these data. How does this evolution affect the quality and nature of information produced in financial markets? Is there a risk that it induces investors to trade on noisier signals about economic fundamentals? How does it change the horizon at which information is produced? How does it affect the signal-to-noise ratio in securities prices and capital allocation? This project will break new ground on these unanswered, yet fundamental, questions using a combination of analytical and empirical analyses. First, I will develop a theory of optimal data mining to disentangle the effect of Data Abundance (DA) from the effect of Artificial Intelligence (AI) on the quality of predictors used by investors. I will then (i) use this theory to make predictions about the effects of AI and DA on the average quality of investors’ predictors, the dispersion of this quality across investors, and the informativeness of securities prices about economic fundamentals and (ii) test some of these predictions. Second, I will study theoretically and empirically (i) the effects of DA and AI on agents’ allocation of their resources for information production between two tasks: forecasting short-term cash-flows and forecasting long-term cash-flows and (ii) the consequence of these effects for the maturity of corporate investments. In particular, I will focus on whether there is a risk that DA and AI make securities prices more informative about conventional investment projects (whose cash-flows are realized quickly) rather than innovative investment projects (whose cash-flows are realized more slowly), thereby reducing capital available for innovation. "

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