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mohin-io / Fractional-PDEs-under-Levy-Models-Machine-Learning-for-Calibrating-Advanced

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This project builds a fast, intelligent calibration engine for advanced asset pricing models. Standard Black-Scholes breaks down under real markets with fat tails and jumps, but Lévy models (Variance Gamma, CGMY) are too slow and unstable to calibrate with classical methods.

machine-learning deep-neural-networks tensorflow keras calibration option-pricing quantitative-finance mcmc variational-inference stochastic-processes asset-pricing variance-gamma levy-processes fourier-methods financial-machine-learning cgmy variance-gamma-process fractional-pde cgmy-model
  • Updated Oct 8, 2025
  • Python

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