Machine Learning: Further Reading

 

Alternative Thinking

Can Machine Learning Help Manage Climate Risks?

Some investors have incorporated carbon emissions into investment selection as their primary approach to preparing their portfolios for a future regime shift to a lower-carbon economy. However, carbon emissions can be a narrow measure of overall climate risk. To complement this approach, we explore how machine learning techniques may be able create a broad climate hedging portfolio based on stocks’ sensitivity to climate news.

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Journal Article

Can Machines "Learn" Finance?

Can Machines “Learn” Finance?” was named the winner of the 2020 Harry M. Markowitz Award. Machine learning for asset management faces a unique set of challenges that differ markedly from other domains where machine learning has excelled. We discuss a variety of beneficial use cases and potential pitfalls for machine learning in asset management, and emphasize the importance of economic theory and human expertise for achieving success through financial machine learning.

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Working Paper

Hedging Climate Change News

We propose and implement a procedure to dynamically hedge climate change risk and discuss multiple directions for future research on financial approaches to managing climate risk.

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Working Paper

Autoencoder Asset Pricing Models

We propose a new latent factor conditional asset pricing model, which delivers out-of-sample pricing errors that are far smaller (and generally insignificant) compared to other leading factor models.

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