This article is devoted to study the e¤ects of the S-periodical fractional di¤erencing filter (1-L^S)^Dt . To put this e¤ect in evidence, we have derived the periodic auto-covariance functions of two distinct univariate seasonally fractionally di¤erenced periodic models. A multivariate...

This paper illustrates the usefulness of resampling based methods in the context of multiple (simultaneous) tests, with emphasis on econometric applications. Economic theory often suggests joint (or simultaneous) hypotheses on econometric models; consequently, the problem of evaluating joint...

Cet article illustre l’applicabilité des méthodes de rééchantillonnage dans le cadre des tests multiples (simultanés), pour divers problèmes économétriques. Les hypothèses simultanées sont une conséquence habituelle de la théorie économique, de sorte que le contrôle de la...

This paper illustrates the usefulness of resampling based methods in the context of multiple (simultaneous) tests, with emphasis on econometric applications. Economic theory often suggests joint (or simultaneous) hypotheses on econometric models; consequently, the problem of evaluating joint...

The purpose of the System Dynamics method is to study the relationship between structure and behavior in non-linear, dynamic systems. In such systems, the significance of various structural components to the behavior pattern exhibited, changes as the behavior unfolds. Changes in structural...

This paper is concerned with simulation based inference in generalized models of stochastic volatility defined by heavy-tailed student-t distributions (with unknown degrees of freedom) and covariate effects in the observation and volatility equations and a jump component in the observation...

This paper develops a systematic Markov Chain Monte Carlo (MCMC) framework based upon Efficient Importance Sampling (EIS) which can be used for the analysis of a wide range of econometric models involving integrals without an analytical solution. EIS is a simple, generic and yet accurate...

We show the convergence of an online stochastic gradient descent estimator to obtain the drift parameter of a continuous-time jump-diffusion process. The stochastic gradient descent follows a stochastic path in the gradient direction of a function to find a minimum, which in our case determines...

Classical univariate and multivariate time series models have problems to deal with the high variability of hourly electricity spot prices. We propose to model alternatively the daily mean electricity supply functions using a dynamic factor model. And to derive, subsequently, the hourly...