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Deep Learning for Liability-Driven Investment (PDF)
Society of Actuaries Link to more items from this source
June 22, 2021

63 pages. "[T]his research contributes to the existing literature in three ways. First, it introduces [Reinforcement Learning (RL)] and deep learning to actuaries and tries to build some connections with actuarial concepts. Second, it provides a workable example to demonstrate the application of RL to LDI and assess its effectiveness. Without simplifying any liability and asset modeling, it shows the potential of RL to solve complex actuarial problems.... Third, sample implementation codes are made public for educational purposes[.]"

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