We consider several time series and for each of them, we fit an appropriate dynamic parametric model. This produces serially independent error terms for each...

For nearest neighbor univariate random walks in a periodic environment, where the probability of moving depends on a periodic function, we show how to estim...

In this paper, we propose an intuitive way to couple several dynamic time series models even when there are no innovations. This extends previous work for m...

In this paper, we consider non-stationary response variables and covariates, where the marginal distributions and the associated copula may be time-dependent...

Parrondo's paradox is extended to regime switching random walks in random environments. The paradoxical behavior of the resulting random walk is explained...

In this paper we solve the discrete time mean-variance hedging problem when asset returns follow a multivariate autoregressive hidden Markov model. Time dep...

In this paper, we first present a review of statistical tools that can be used in asset management either to track financial indexes or to create synthetic o...

An exchangeable bond is a debt that is convertible into shares of a firm's equity other than the bond's issuer. We evaluate an exchangeable bond within a two...

Most structural models for valuing corporate securities assume a geometric-Brownian motion to describe the firm's assets value. However, this does not reflec...

Recently, two different copula-based approaches have been proposed to estimate the conditional quantile function of a variable \(Y\) with respect to a vect...

We develop a general structural model for valuing risky corporate debts that takes into account both default and interest rate risk. We propose a two-dimensi...

Lévy processes provide a solution to overcome the shortcomings of the lognormal hypothesis. A growing literature proposes the use of pure-jump Lévy processe...

We propose a dynamic program coupled with finite elements for valuing two-dimensional American-style options. To speed-up our procedure, we use parallel comp...

We propose a quasi-analytical approach for valuing American-style options under Gaussian and double exponential jumps à la Merton (1976) and Kou (2002). Our ...

In this paper we present a forecasting method for time series using copula-based models for multivariate time series. We study how the performance of the p...

It is shown that parametric bootstrap can be used for computing P-values of goodness-of-fit tests of multivariate time series parametric models. These mo...

In view of applications to diagnostic tests of ARMA models, the asymptotic behavior of multivariate empirical and copula processes based on residuals of ARM...

In this paper, we introduce the notion of dynamic copulas to model serial dependence as well as interdependence between several time series. The proposed m...

In this article we find the optimal solution of the hedging problem in discrete time by minimizing the mean square hedging error, when the underlying assets ...

In this article, we construct a Malliavin derivative for functionals of a square-integrable Lévy process. The Malliavin derivative is defined via chaos expan...

A discretization scheme for nonnegative diffusion processes is proposed and the convergence of the corresponding sequence of approximate processes is proved ...

Many proposals have been made recently for goodness-of-fit testing of copula models. After reviewing them briefly, the authors concentrate on omnibus proced...

Using Clark-Ocone formula, explicit martingale representations for path-dependent Brownian functionals are computed. As direct consequences, explicit martin...

We develop a test of equality between two dependence structures estimated through empirical copulas. We provide inference for independent or paired samples....

We investigate the common practice of estimating the dependence structure between CDS prices on multi-name credit instruments by the dependence structure of ...

This paper proposes new tests of randomness for innovations of a large class of time series models. These tests are based on functionals of empirical proces...

The aim of this paper is to present efficient algorithms for the detection of multiple targets in noisy images of a finite region. The algorithms are based ...

While convergence properties of many sampling selection methods can be proven to hold in a context of approximation of Feynman-Kac solutions using sequentia...

In testing that a particular distribution <img src="/cgi-bin/mimetex.cgi?P"> belongs to a parameterized family <img src="/cgi-bin/mimetex.cgi?\cal{P}">, one ...

Deheuvels (1981a,b,c) and Genest and Rémillard (2004) have shown that powerful rank tests of multivariate independence can be based on combinations of asymp...

The multivariate modelling of default risk is a crucial aspect of the pricing of credit derivative products referencing a portfolio of underlying assets, an...

Deheuvels proposed a rank test of independence based on a Cramér–von Mises functional of the empirical copula process. Using a general result on the asympto...

Rank-based estimators were proposed by Clayton (1978) and Oakes (1982) for the association parameter in the bivariate gamma frailty model. The joint asympto...

Two methods of analytical approximations for computing the value of a European option on the conditional variance in a GARCH setting are presented. The firs...

An approach is suggested for testing whether the dependence structure of a random sample of multivariate data is appropriately modelled by a given family of ...

The aim of this paper is to present efficient algorithms for the detection of multiple targets in noisy images of a torus. The algorithms are based on the ...

The aim of this paper is to present efficient algorithms for the detection of multiple targets in noisy images. The algorithms are based on the optimal filte...

Exploiting an overlooked observation of Blum, Kiefer & Rosenblatt (1961), Dugué (1975) and Deheuvels (1981a) described a decomposition of empirical distribu...

This paper introduces new rank-based statistics for testing against serial dependence in a univariate time series context. These Kolmogorov-Smirnov and Cram...