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chirindaopensource / optimal_investment_and_pension_policy_in_pay_as_you_go_systems

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End-to-End Python implementation of consistent intergenerational pension optimization from Alonso-Garcia et al. (2026). Solves optimal PAYG pension policy via forward CRRA utilities and closed-form HJB feedback laws. Features a 10,000-path Euler-Maruyama Monte Carlo engine, Cholesky-correlated 4D Brownian shocks, and demographic stress-testing.

python numpy jupyter-notebook scientific-computing scipy monte-carlo-simulation quantitative-finance optimal-control stochastic-differential-equations mathematical-finance payg heston-model stochastic-control actuarial-science euler-maruyama vasicek-model demographic-ageing research-replication forward-utility pension-policy
  • Updated May 22, 2026
  • Jupyter Notebook

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