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Uncertainty and Explainability in Deep Rough Volatility: A Neural Information-Theoretic Posterior Approach

arXiv:2609.31570v1 Announce Type: new Abstract: Deep learning has substantially accelerated the calibration of complex stochastic-volatility models, but neural point calibration alone does not capture the uncertainty remaining after an implied-volatility (IV) surface has been observed. We develop a…

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  1. 2026-09-28 04:00 · arXiv stat.ML
    Uncertainty and Explainability in Deep Rough Volatility: A Neural Information-Theoretic Posterior Approach

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