Stochastic Local Volatility models form the backbone of EQ derivative pricing.
For calibration and one-asset trades, the ability to quickly price (backward induction) or construct the distribution (Kolmogorov forward PDE) is essential.
For calibration and one-asset trades, the ability to quickly price (backward induction) or construct the distribution (Kolmogorov forward PDE) is essential.
The nZetta toolkit provides many 2D PDE methods so you can choose the best one for your trade. All the algorithms have been designed for modern hardware and memory to provide top performance.
Douglas ADI has slow convergence for non-zero correlations so is not ideal here. Using the Hunsdorfer-Verwer method, the same level of accuracy as Modified Craig-Sneyd can be achieved with approximately 30% fe
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