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 time series. The dependence between these error terms is then modeled by a regime-switching copula. The EM algorithm is used for...

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 time series. The dependence between these error terms is then modeled by a regime-switching copula. The EM algorithm is used for...

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 ones. More precisely, we look at two important replication methods: the strong replication, where a portfolio of very liquid assets is...

In this paper, we propose an intuitive way to couple several dynamic time series models by inducing dependence between the so-called generalized errors of each model. This extends previous work for modelling dependance between innovations of stochastic volatility models. We consider...

In this paper, we focus on a new generalization of multivariate general compound Hawkes process (MGCHP), which we referred to as the multivariate general compound point process (MGCPP). Namely, we applied a multivariate point process to model the order flow instead of the Hawkes process. The law...

Herein, we characterize strong solutions of multidimensional stochastic differential equations (formula) that can be represented locally as (formula) where W is an multidimensional Brownian motion and U, (symbole) are continuous functions. Assuming that (symbole) is continuously differentiable,...

Trying to perform non-parametric change point tests for multivariate data using empirical processes is much more difficult that in the univariate case, since the limiting distribution depends on the unknown joint distribution function or its associated copula. In order to solve this problem, we...

In this paper, we focus on a new generalization of multivariate general compound Hawkes process (MGCHP), which we referred to as the multivariate general compound point process (MGCPP). Namely, we applied a multivariate point process to model the order flow instead of the Hawkes process. Law of...

Parrondo's paradox is extended to regime switching random walks in random environments. The paradoxical behavior of the resulting random walk is explained by the effect of the random environment. Full characterization of the asymptotic behavior is achieved in terms of the dimensions of some...