Detecting Relevant Deviations From the White Noise Assumption for Non‐Stationary Time Series
ABSTRACT We consider the problem of detecting deviations from a white noise assumption in time series. Our approach differs from the numerous methods proposed for this purpose with respect to two aspects. First, we allow for non‐stationary time series. Second, we address the problem that a white noise test is usually not performed because one believes ...
Patrick Bastian
wiley +1 more source
Adaptive Estimation for Weakly Dependent Functional Times Series
ABSTRACT We propose adaptive mean and autocovariance function estimators for stationary functional time series under 𝕃p−m‐approximability assumptions. These estimators are designed to adapt to the regularity of the curves and to accommodate both sparse and dense data designs.
Hassan Maissoro +2 more
wiley +1 more source
Robust CDF‐Filtering of a Location Parameter
ABSTRACT This paper introduces a novel framework for designing robust filters associated with signal plus noise models having symmetric observation density. The filters are obtained by a recursion where the innovation term is a transform of the cumulative distribution function of the residuals.
Leopoldo Catania +2 more
wiley +1 more source
Optimal control of stochastic partial differential equations in Banach spaces [PDF]
In this thesis we study optimal control problems in Banach spaces for stochastic partial differential equations. We investigate two different approaches.
Serrano Perdomo, Rafael Antonio +1 more
core
Sobolev-type fractional stochastic differential equations with non-Lipschitz coefficients
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Abbes Benchaabane, Rathinasamy Sakthivel
openaire +2 more sources
Robust Estimation and Inference for Time‐Varying Unconditional Volatility
ABSTRACT We derive a general and robust estimator of a large class of parametric specifications of time‐varying unconditional volatility of financial returns, both univariate and multivariate, and establish the Consistency and Asymptotic Normality (CAN) of the estimator.
Adam Lee +2 more
wiley +1 more source
Euler scheme for SDEs with non-Lipschitz diffusion coefficient : strong convergence
International audienceWe consider one-dimensional stochastic differential equations in the particular case of diffusion coefficient functions of the form |x|^a, a in [1/2,1).
Awa Diop +5 more
core +1 more source
Empirical‐Process Limit Theory and Filter Approximation Bounds for Score‐Driven Time Series Models
ABSTRACT This article examines the filtering and approximation‐theoretic properties of score‐driven time series models. Under specific Lipschitz‐type and tail conditions, new results are derived, leading to maximal and deviation inequalities for the filtering approximation error using empirical process theory.
Enzo D'Innocenzo
wiley +1 more source
BSVIEs with stochastic Lipschitz coefficients and applications in finance
This paper is concerned with existence and uniqueness of M-solutions of backward stochastic Volterra integral equations (BSVIEs for short), which Lipschitz coefficients are allowed to be random, which generalize the results in [15]. Then a class of continuous time dynamic dynamic coherent risk measures is derived, allowing the riskless interest rate to
openaire +2 more sources
Testing Distributional Granger Causality With Entropic Optimal Transport
ABSTRACT We develop a novel nonparametric test for Granger causality in distribution based on entropic optimal transport. Unlike classical mean‐based approaches, the proposed method directly compares the full conditional distributions of a response variable with and without the history of a candidate predictor.
Tao Wang
wiley +1 more source

