This paper introduces a general class of combined neural network-GARCH models suitable to financial time series analysis. We put special emphasis on designing a full model-building cycle for this class of models that includes all stages of econometric modelling (specification, estimation and...

This paper summarizes and assesses several of the most popular methods to seasonally adjust weekly data. The industry standard approach, known as X-13ARIMA-SEATS, is suitable only for monthly or quarterly data. Given the increased availability and promise of non-traditional data at higher...

This paper systematically studies the use of mixed-frequency data sets and suggests that the use of high frequency data in forecasting economic aggregates can improve forecast accuracy. The best way of using this information is to build a single model, for example, an ARMA model with missing...

This paper systematically studies the use of mixed-frequency data sets and suggests that the use of high frequency data in forecasting economic aggregates can improve forecast accuracy. The best way of using this information is to build a single model, for example, an ARMA model with missing...

Real GDP and oil prices are decomposed into common stochastic trend and cycle processes using structural time series models. Potential real GDP is represented by the level of the trend component of real GDP. The potential rate of growth of real GDP is represented by the stochastic drift element...

Using structural time series models, Cuevas estimates common stochastic trends of real GDP and imports in Venezuela from 1974-2000. The real imports trend drifts upward at almost twice the rate of growth of GDP. This highlights the powerful structural tendency toward increasing imports in...

Money demand in Venezuela is modeled using structural time series and error correction approaches, for the period 1993.1 to 2001.4. The preferred model features seasonal cointegration and was estimated following a structural time series approach. There are similarities in the long-run behavior...

In this paper we propose a test for a set of linear restrictions in a Vector Autoregressive Moving Average (VARMA) model. This test is based on the autoregressive metric, a notion of distance between two univariate ARMA models, M0 and M1, introduced by Piccolo in 1990. In particular, we show...