The industry standard model for commodity price dynamics implies constant correlation between returns of futures with different tenors. We extend the model by allowing its parameters to vary over time. This practice enables us to capture the seasonality effect embedded in the evolution of a...

In this paper, we present a new time series model, whichdescribes self-exciting threshold autoregressive (SETAR) nonlinearityand seasonality simultaneously. The model is termed multiplicativeseasonal SETAR (SEASETAR). It can be viewed as a special case of ageneral non-multiplicativeSETAR model...

Structural change affects the estimation of economic signals, like the underlying growth rate or the seasonally adjusted series. An important issue, which has at- tracted a great deal of attention also in the seasonal adjustment literature, is its detection by an expert procedure. The...

The analysis of seasonality in economics and the development of new seasonal adjustment procedures have been following new directions in the last twenty years. We study this question through the work performed at the Banque de France (Monetary Statistic and Studies Directorate) to compile new...

We develop a new targeted maximum likelihood estimation method that provides improved forecasting for misspecified linear autoregressive models. The method weighs data points in the observed sample and is useful in the presence of data generating processes featuring structural breaks, complex...

The problem of optimal decision between unit roots, trend stationarity and trend stationarity with structural breaks is considered. Each of three classes is represented by a hierarchically random process whose parameters are distributed in a non-informative way based on a simple rule. Given a...