The aim of this chapter is to dsicuss the contagionbetween the financial sphere and the real sphere. We define the concept of contagion, then we introduce some parametric models used to detect the contagion phenomenum, then we introduce some non-parametric tools focusing on copulas....

This paper proposes a new fractional model with a time-varying long-memory parameter. The latter evolves nonlinearly according to a transition variable through a logistic function. We present a LR-based test that allows to discriminate between the standard fractional model and our model. We...

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.

This paper generalizes the standard long memory modeling by assuming that the long memory parameter d is stochastic and time varying: we introduce a STAR process on this parameter characterized by a logistic function. We propose an estimation method of this model. Some simulation experiments are...

The main purpose of this paper is to consider the multivariate GARCH (MGARCH) framework to model the volatility of a multivariate process exhibiting long term dependence in stock returns. More precisely, the long term dependence is examined in the …first conditional moment of US stock returns...

Researchers in finance very often rely on highly persistent - nearly integrated - explanatory variables to predict returns. This paper proposes to stand up to the usual problem of persistent regressor bias, by detrending the highly auto-correlated predictors. We find that the statistical...