Using Archimedean copulas, we investigate the dependence structure existing between several series of financial assets log-returns that come from different markets. These series are considered as components of a portfolio and they are investigated on a long period including high shocks. To...

In this paper we discuss different aspects of long memory behaviorand applicable parametric models. We discuss the confusion thatcan arise when the empirical autocorrelation function decreasesin an hyperbolic way.

In this paper, we compre the time fresuency deconvolution method with the wavelets method. We apply our results on several dynamical systems and show the capability of the wavelet's method to reconstruct the attractor of a chaotic time series? We de-noise different data sets in order to rebuilt...

This paper introduces non-parametric estimators for upper and lower tail dependence whose confidence intervals are obtained with a bootstrap method. We call these estimators "Naïve estimators" as they represent a discretization of Joe's formulae (1997)\nocite{Joe} linking copulas to tail...

For a GARCH(1,1) process, we study the large deviation asymptotics at the horizon k and their consequences for extreme quantile estimation. The results are relevant for the estimation of multi-period Value at Risk and prove that the heuristic “square k” rule used in financial risk management...

We consider a class of linear regression model with extreme distribution noise. We show by a mean of point process technique that the asymptotic distribution of the maximum is the same as the one of the max of the noise process, under specific conditions.

The paper focuses on the conditions of the use of the nearest neighbors method analysing the impact of the Euclidean distance and in sample predictions, the choice of the neighbors, the number of neighbors and the distance between the neighbors.

We examine the effect of two specific noises on a dynamical system. We obtain consistent estimates with their rates of convergence for the invariant density for such a model. Some simulations are provided.

We study the asymptotic behaviour of the extreme values of a stochastic volatility model when the noise follows a generalized error distribution extreme. We provide a Monte Carlo experiment to illustrate th choice of the assumptions. We deal also with the finite sample behaviour of the...

In this paper, we analyze the possible confusion in terms of long memory behavior of the autocorrelation function of a Markov switching model. Such a model is known to have a short memory behavior. Analyzing the value of sum of the transition probabilities and the number of switches inside such...