Amortizing the Calibration Triple: A Projection-Consistent Neural Operator for Local-Stochastic Volatility
Local-stochastic volatility (LSV) combines vanilla marginals with richer smile dynamics, but calibration requires a slow, noisy and sequential McKean--Vlasov fixed point. We learn a projection-consistent operator for the calibration triple. Given finite quotes and a stochastic-volatility (SV) backbone, it jointly returns an implied-volatility surface subject to static-arbitrage constraints, its Dupire local volatility, LSV leverage and the conditional moment required by the projection identity. Starting from option-price marginals, we derive a division-free Dupire residual in log-implied-variance coordinates and a quotient Fokker--Planck equation after Gyöngy projection. Deep Operator Net...
| Authors | Xiaozhen Wang, Anaïs Després, Martin Dureau et al. |
|---|---|
| Primary category | q-fin.MF |
| Published | 2 August 2026 |
| Last updated at source | 2 August 2026 |
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