To date, most functional Magnetic Resonance Imaging (fMRI) studies have assumed that the functional connectivity (FC) between time series from distinct brain regions is constant across time. However, recently, there has been an increased interest in quantifying possible dynamic changes in FC during fMRI experiments, as it is thought that this may provide insight into the fundamental workings of...

In this research, the DCC model is estimated to calculate dynamic correlation series between crude oil price and growth of Industry and Mine sector during 1367:1-1392:4. Then, Macroeconomic variables which can explain the dynamic correlation are analyzed as variables of contagion. So, the import, as an effective and affected variable from crude oil price, is separated to real import of consumpt...

We model the conditional mean and volatility of stock returns as a latent vector autoregressive (VAR) process to study the contemporaneous and intertemporal relationship between expected returns and risk in a flexible statistical framework and without relying on exogenous predictors. We find a strong and robust negative correlation between the innovations to the conditional moments that leads t...

We model the conditional mean and volatility of stock returns as a latent vector autoregressive (VAR) process to study the contemporaneous and intertemporal relationship between expected returns and risk in a flexible statistical framework and without relying on exogenous predictors. We find a strong and robust negative correlation between the innovations to the conditional moments that leads t...

This paper addresses several questions surrounding volatility forecasting and its use in the estimation of optimal hedging ratios. Specifically: Are there economic gains by nesting time-series econometric models (GARCH) and dynamic programming models (therefore forecasting volatility several periods out) in the estimation of hedging ratios whilst accounting for volatility in the futures bid–ask...

The conditional correlation patterns of an anatomical shape may provide some important information on the structure of this shape. We propose to investigate these patterns by Gaussian Graphical Modelling. We design a model which takes into account both local and longdistance dependencies. We provide an algorithm which estimates sparse long-distance conditional correlations, highlighting the mos...

J.-P. Montagner,1 C. Larmat,2 Y. Capdeville,1 M. Fink,3 H. Phung,1 B. Romanowicz,4 E. Clévédé1 and H. Kawakatsu5 1Seismology Laboratory, Institut de Physique du Globe UMR-CNRS 7154, 1 rue Jussieu 75238 Paris Cedex 05, France. E-mail: [email protected] 2L.A.N.L., Los Alamos, NM, USA 3Institut Langevin, ESPCI ParisTech, CNRS, 1 rue Jussieu, 75005 Paris, France 4Seismology Lab., U.C. Berkeley, Berkeley,...