DeepLévy learns mixtures of Lévy stable distributions for heavy-tailed time series forecasting by minimizing discrepancies between empirical and parametric characteristic functions, outperforming prior methods on tail risk metrics under extreme volatility.
Regression-type estimation of the parameters of stable laws.Journal of the American statistical association, 75(372):918–928
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DeepL\'evy: Learning Heavy-Tailed Uncertainty in Highly Volatile Time Series
DeepLévy learns mixtures of Lévy stable distributions for heavy-tailed time series forecasting by minimizing discrepancies between empirical and parametric characteristic functions, outperforming prior methods on tail risk metrics under extreme volatility.