[en] 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.
Disciplines :
Sciences informatiques
Auteur, co-auteur :
KIEFFER, Emmanuel ; University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Computer Science (DCS)
Meyer, Thomas; Simcorp Luxembourg SA
Gloukoviezoff, Georges; European Investment Bank
Lucius, Hakan; European Investment Bank
BOUVRY, Pascal ; University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Computer Science (DCS)
Co-auteurs externes :
yes
Langue du document :
Anglais
Titre :
Learning private equity recommitment strategies for institutional investors
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