Optimal investment and Pension policy in Pay-As-You-Go systems under forward utility and ageing population

Battle Count: 52

The paper is primarily focused on public pension policy design and intergenerational risk sharing rather than quantitative trading. However, it uses Heston stochastic volatility and Vasicek interest rate models common in quantitative finance. The forward utility framework and portfolio allocation insights (risky asset allocation ~50% for theta=4) have tangential relevance to long-term institutional asset allocation. The risk premium and market price of risk dynamics could inform long-horizon investment strategies. Overall, the connection to active quantitative trading is minimal.

High complexity due to: (1) SPDE representation of forward utilities requiring advanced stochastic analysis; (2) HJB consistency conditions with non-linear SDEs; (3) 4-dimensional correlated Brownian motion with Cholesky decomposition; (4) Heston + Vasicek + wage dynamics with full correlation structure; (5) Monte Carlo simulation with 10,000 paths and Euler discretization; (6) Multiple sensitivity analyses across demographic scenarios, preference parameters, and initial conditions; (7) Closed-form derivations requiring careful handling of the buffer depletion time and utility weight processes. The mathematical framework builds on Hillairet, Kaakai and Mrad (2024) and requires expertise in stochastic control and pension economics.

The paper provides detailed parametrization (Table 1), specifies the Python implementation with Euler schemes, uses 10,000 Monte Carlo simulations, and calibrates parameters from published literature. However, no code repository is explicitly linked. The mathematical derivations are complete with proofs. Demographic scenarios (steady-state DR=0.3, baby boom DR=0.3→0.5) are clearly defined. Reproducibility is high given the detailed parameter table and methodology description.