infinite-horizon-stochastic-analysis

What problem does it solve?

Infinite-horizon stochastic analysis provides methodology to analyze and solve optimization problems that extend to infinite time horizons using weighted spaces, BSVIEs, and measure transformations, enabling robust long-term decision making.

Core Features & Use Cases

• Weighted L^p spaces for convergence over infinite horizons
• BSVIE-based problem reformulation and resolvent-kernel approximations
• Measure-change techniques (Girsanov) for handling evolving probability measures
• Applications include perpetual asset pricing, retirement planning, climate policy, and long-term maintenance optimization

Quick Start

Model your infinite-horizon problem with a weighted L^p space, formulate it as a BSVIE, and compute a resolvent kernel to obtain an actionable approximation.