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Deep Learning for Liability-Driven Investment | SOA
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Deep Learning for Liability-Driven Investment

Author:

Kailan Shang, FSA, CFA, PRM, SCJP

Description:

The Society of Actuaries’ Committee on Finance Research is pleased to make available a research report that develops a framework for applying deep learning and reinforcement learning techniques to optimal dynamic strategic asset allocation for Liability Driven Investment (LDI).

Report:

Deep Learning for Liability-Driven Investment

Deep Learning for Liability-Driven Investments Fast Facts

Github:

The code used in this report is available on GitHub at GitHub - Society-of-actuaries-research-institute/FP198-Deep-Learning-for-Liability-Driven-Investment

Acknowledgments:

The Society of Actuaries would like to thank the Project Oversight Group for their guidance and input:

Lindsay Allen

David Cantor

Naxine Chang

Steven Craighead

Abid Kazmi

Zixiang Low

Michael Niemerg

Dennis Radliff

Ronald Richman

Haofeng Yu

Aolin Zhang

Barbara Scott, SOA Sr. Research Administrator

Steven Siegel, SOA Sr. Practice Research Actuary

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If you have comments or questions, please send an email to research@soa.org.