Data di Pubblicazione:
2024
Citazione:
Ferrara, M., T., Ciano, A., Capriotti e S., Muzzioli. "Machine learning technique to compute climate risk in finance" Working paper, DEMB WORKING PAPER SERIES, Dipartimento di Economia Marco Biagi, 2024. https://doi.org/10.25431/11380_1362074
Abstract:
We investigate how the application of advanced predictive models could help
investors to assess and manage climate risk in their portfolios, contributing to
the development of more sustainable and resilient investment practices. We
highlight the possible applications of predictive analytics as a key tool in
climate finance. It emerges how emerging technologies (blockchain and
Artificial Intelligence) can improve transparency, efficiency, and climate risk
analysis in sustainable investments. Further lines of research are highlighted,
focusing on how investors and portfolio managers can develop strategies to
manage the risks associated with climate events and the integration of climate
risks into the management of Supply Chain Finance to ensure greater resilience
and sustainability.
Tipologia CRIS:
Working paper
Keywords:
Climate Risk, Machine Learning, Supply Chain Finance, Blockchain, Predictive Models
Elenco autori:
Ferrara, M.; Ciano, T.; Capriotti, A.; Muzzioli, S.
Link alla scheda completa:
Link al Full Text:
Pubblicato in: