We rely on bilevel programming to model the problem of financial service providers that, in order to meet stakeholders’ demands and regulatory requirements, aim at incentivizing accounts’ holders to construct ESG-oriented portfolios so that the overall ESG impact of the firm is optimized, while the preferences of accounts’ owners are still satisfied. We analyze this complicated framework from a theoretical point of view and identify sufficient conditions that make it numerically tractable via a novel, specifically tailored algorithm, whose convergence properties are studied. Numerical testing on real-world data confirms the theoretical insights and shows that our model can be solved even when dealing with considerable problem sizes.
Cesarone, F., Lampariello, L., Merolla, D., Ricci, J.M., Sagratella, S., Giuseppe Sasso, V. (2023). A bilevel approach to ESG multi‑portfolio selection. COMPUTATIONAL MANAGEMENT SCIENCE, 1-23 [10.1007/s10287-023-00458-y].
A bilevel approach to ESG multi‑portfolio selection
Francesco Cesarone;Lorenzo Lampariello
;Jacopo Maria Ricci;Simone Sagratella;
2023-01-01
Abstract
We rely on bilevel programming to model the problem of financial service providers that, in order to meet stakeholders’ demands and regulatory requirements, aim at incentivizing accounts’ holders to construct ESG-oriented portfolios so that the overall ESG impact of the firm is optimized, while the preferences of accounts’ owners are still satisfied. We analyze this complicated framework from a theoretical point of view and identify sufficient conditions that make it numerically tractable via a novel, specifically tailored algorithm, whose convergence properties are studied. Numerical testing on real-world data confirms the theoretical insights and shows that our model can be solved even when dealing with considerable problem sizes.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
