In this paper, we discuss the class of Bilinear GATRCH (BL-GARCH) models which are capable of capturing simultaneously two key properties of non-linear time series : volatility clustering and leverage effects. It has been observed often that the marginal distributions of such time series have...

Business surveys are an important element in the analysis of the short-term economic situation because of the timeliness and nature of the information they convey. Especially, surveys are often involved in econometric models in order to provide an early assessment of the current state of the...

In this paper we deal with the problem of non-stationarity encountered in a lot of data sets coming from existence of multiple seasonnalities, jumps, volatility, distorsion, aggregation, etc. We study the problem caused by these non stationarities on the estimation of the sample autocorrelation...

The purpose of this paper is to study the self-similar properties of discrete-time long memory processes. We apply our results to specific processes such as GARMA processes and GIGARCH processes, heteroscedastic models and the processes with switches and jumps.

This paper develops a method for pricing bivariate contingent claims under General Autoregressive Conditionally Heteroskedastic (GARCH) process. As the association between the underlying assets may vary over time, the dynamic copula with time-varying parameter offers a better alternative to any...

In this paper, index tranches'properties and several hedging strategies are discussed. Model risk and correlation risk are analysed through the study of the efficiency of several factor based copula models, like the Gaussian, the double-t and the double NIG using implied correlation and a...

The detection of chaotic behaviors in commodities, stock markets and weather data is usually complicated by large noise perturbation inherent to the underlying system. It is well known, that predictions, from pure deterministic chaotic systems can be accurate mainly in the short term. Thus, it...

This paper analyzes the dynamics of the US inflation series using two classes of models : structural changes models and Long memory processes. For the first class, we use the Markov Switching (MS-AR) model of Hamilton (1989) and the Structural Change (SCH-AR) model using the sequential method...

This paper develops the method for pricing bivariate contingent claims under General Autoregressive Conditionally Heteroskedastic (GARCH) process. In order to provide a general framework being able to accommodate skewness, leptokurtosis, fat tails as well as the time varying volatility that are...

In this paper, we recall some concepts on seasonal long memory, we review the diverse fractionally integrated seasonal time series models and we discuss their statistical properties. Then, we compare the empirical performances of those models on euro area economic data and we show that...