2025/04/09 by Yanfeng Wu, Yan-Feng Wu, Wu, Yan-Feng +2 · 1 voice
Economics, Econometrics and Finance · Engineering · Physics and Astronomy · #Advanced Numerical Methods in Computational Mathematics #Model Reduction and Neural Networks #Nuclear reactor physics and engineering #q-fin.MF
paper · pdf · doi:10.48550/arxiv.2504.06942
We develop a recursive approach for deriving closed-form solutions to both conditional and unconditional moments of affine jump diffusions with state-independent jump intensities. Using these moment solutions, we construct closed-form density approximations (up to a normalization constant) via moment matching for both conditional and unconditional distributions. Our framework enables important financial applications, including efficient option pricing and exact simulation for affine jump diffusions. Numerical experiments demonstrate the method's superior computational efficiency compared to existing simulation techniques, while preserving numerical precision.