Uncertainty and Explainability in Deep Rough Volatility: A Neural Information-Theoretic Posterior Approach
A simulation-based inference framework for rough Heston (rHeston) calibration that learns the posterior distribution of the model parameters conditional on an IV surface and introduces Hellinger-SHAP, an information-theoretic explainability method for posterior inference.
D. Brigo, Raphael Huser, Dan Leonte
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