Frontiers in Artificial Intelligence (Feb 2023)
Learning private equity recommitment strategies for institutional investors
Abstract
Keeping strategic allocations at target level to maintain high exposure to private equity is a complex but essential task for investors who need to balance against the risk of default. Illiquidity and cashflow uncertainty are critical challenges especially when commitments are irrevocable. In this work, we propose to use a trustworthy and explainable A.I. approach to design recommitment strategies. Using intensive portfolios simulations and evolutionary computing, we show that efficient and dynamic recommitment strategies can be brought forth automatically.
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