Forecasting Climate Transition Regulatory and Market Risk Variables with Machine Learning-Reference-Cited by-同舟云学术

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Forecasting Climate Transition Regulatory and Market Risk Variables with Machine Learning

Published:2023-09-13 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE International Symposium on Technology and Society (ISTAS)
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Author:

Pérez-Pérez Juan F.¹,Cruz Isis Bonet¹,Sánchez-Pinzón María Solange²,Caraffini Fabio³,Lochmuller Christian⁴

Affiliation:

1. EIA University,Dept. of Engineering and Basic Sciences,Envigado,Colombia

2. Vicepresidency of Sustainability, Grupo Nutresa,Medellin,Colombia

3. Swansea University,Dept. of Computer Science,Swansea,UK

4. EIA University,Dept. of Economic and Administrative Sciences,Envigado,Colombia

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10305708/10305722/10306196.pdf?arnumber=10306196

Reference39 articles.

1. Development of a web-based tool for climate change risk assessment in the business sector;kim;Sustainability,2016

2. Statistical and Machine Learning forecasting methods: Concerns and ways forward

3. Climate Risk Assessment under Uncertainty: An Application to Main European Coastal Cities

4. Financial Time Series Forecasting – A Deep Learning Approach

5. A system dynamic approach for exploring the effects of climate change risks on firms' economic performance

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