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Learning private equity recommitment strategies for institutional investors.

In Frontiers in artificial intelligence

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.

Kieffer Emmanuel, Meyer Thomas, Gloukoviezoff Georges, Lucius Hakan, Bouvry Pascal

2023

artificial intelligence, evolutionary learning, optimization, private equity, recommitment strategies