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End of preview. Expand in Data Studio
VA Riders — Nested Stochastic Simulation with AAD Greeks
Simulation dataset for variable annuity (VA) guarantee pricing and Greek estimation, generated with ActuaLib and test data for Sobolev-trained neural network surrogates.
Contents
Each HDF5 file corresponds to one contract of a nested Monte Carlo simulation:
fmv_per_path [n_outer]— fair market value per outer scenariodelta [n_outer × 5]— equity Gr)rho [n_outer × 10]— interest rate Greeks (AAD, 10 yield-curve knots)- Outer market state: spot prices,
Structure
| Split | Outer paths | Inner paths
|-------|------------|-------------|----------|-------------|
| test/{rule} | 100,000 | 1,000 | |
| trainJ/{rule} | 20,000 | 100 | 180 | Coverage-first training tier |
{rule} ∈ {rop, ratchet, rollup} (benefit-base update rule). Each split contains 180 policies: 20
per rider × 9 riders.
Riders: GMAB,GMDB,GMDB_AB,GMDB_IB,GMDB_MB,GMDB_WB,GMIB,GMMB,GMWB
Benefit-base rules: Return of P(step-up), annual roll-up
Simulation Engine
ActuaLib — C++17, reverse-mode AAD,er model: Multivariate Black-Scholes+ Hull-White 1-factor short rate. Outer model: regime-switching GBM (equity) + AIRG 3-factor log-normal (rates, AAA ESWG mandate
RNG: Sobol quasi-random sequencrainJ 20260402 (independent to prevent data leakage).
Integrity
SHA-256 manifest at sha256_manifest.txt — verify with:
sha256sum --check sha256_manifest.txt
Companion Models
ivanzoccolan/va-surrogates
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