The aims of this paper are estimate and forecast the Non-Accelerating Inflation Rate of Unemployment, or NAIRU, for Brazilian unemployment time series data. In doing so, we introduce a methodology for estimating mixed additive seasonal autoregressive (MASAR) models, by the Generalized Method of...

We propose a tree-structured heterogeneous autoregressive (tree-HAR) process as a simple and parsimonious model for the estimation and prediction of tick-by-tick realized correlations. The model can account for different time and other relevant predictors' dependent regime shifts in the...

It is generally accepted that the recent economic crisis of 2007-2010 has caused widespread economic recession in different countries. Since the ports and coastal regions are of great importance to economic infrastructure, this study examined the possible impact resulting from such a global...

La littérature sur l’instabilité macroéconomique couvre un champ extrêmement vaste qui se révèle par le spectre très large de mesures utilisées pour appréhender ce phénomène. Le choix de la mesure de l’instabilité macroéconomique apparait généralement peu discuté sous le...

La littérature sur l’instabilité macroéconomique couvre un champ extrêmement vaste qui se révèle par le spectre très large de mesures utilisées pour appréhender ce phénomène. Le choix de la mesure de l’instabilité macroéconomique apparait généralement peu discuté sous le...

We define risk spillover as the dependence of a given asset variance on the past covariances and variances of other assets. Building on this idea, we propose the use of a highly flexible and tractable model to forecast the volatility of an international equity portfolio. According to the risk...

El objetivo de este documento es presentar un conjunto de alternativas metodológicas paraestimar el producto interno bruto potencial mediante la aplicación de cincos metodologías,entre las cuales podemos citar: un modelo VAR estructural con restricciones de largo plazotipo Blanchard y Quah,...

We consider modeling and forecasting a variety of asset return volatility series by adding a random level shift component to the usual long-memory ARFIMA model. We propose a parametric state space model with an accompanying estimation and forecasting framework that combines long memory and level...

The globalisation on financial markets and the development of financial derivatives has increased not only chances but also potential risk within the banking industry. Especially market risk has gained major significance since market price variation of interest rates, stocks or exchange rates...

In modelling and forecasting volatility, two main trade-offs emerge: mathematical tractability versus economic interpretation and accuracy versus speed. The authors attempt to reconcile, at least partially, both trade-offs. The former trade-off is crucial for many financial applications,...