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9 papers · 2 filters
Prediction of time series by statistical learning: general losses and fast rates
Pierre Alquier, Xiaoyin Li, Olivier Wintenberger
We establish rates of convergences in time series forecasting using the statistical learning approach based on oracle inequalities. A series of papers extends the oracle inequaliti…
Continuous invertibility and stable QML estimation of the EGARCH(1,1) model
Olivier Wintenberger
We introduce the notion of continuous invertibility on a compact set for volatility models driven by a Stochastic Recurrence Equation (SRE). We prove the strong consistency of the…
GARCH models without positivity constraints: Exponential or Log GARCH?
Christian Francq, Olivier Wintenberger, Jean-Michel Zakoïan
This paper provides a probabilistic and statistical comparison of the log-GARCH and EGARCH models, which both rely on multiplicative volatility dynamics without positivity constrai…
Nonparametric estimation of a renewal reward process from discrete data
Celine Duval
We study the nonparametric estimation of the jump density of a renewal reward process from one discretely observed sample path over [0,T]. We consider the regime when the sampling…
Precise large deviations for dependent regularly varying sequences
Thomas Mikosch, Olivier Wintenberger
We study a precise large deviation principle for a stationary regularly varying sequence of random variables. This principle extends the classical results of A.V. Nagaev (1969) and…
The Degrees of Freedom of the Group Lasso
Samuel Vaiter, Charles Deledalle, Gabriel Peyré +2
This paper studies the sensitivity to the observations of the block/group Lasso solution to an overdetermined linear regression model. Such a regularization is known to promote spa…