Showing 1 - 10 of 12,613
In this paper, we used the GARCH (1,1) and GARCH-M (1,1) models to investigate volatility and persistence at daily frequency for European and US financial markets. In the study we included fourteen stock indices (twelve Europeans and two Americans), during March 2013 - January 2017. The results...
Persistent link: https://www.econbiz.de/10011964941
Typical issues of multivariate GARCH models are dimensionality, which is time consuming, both in terms of computations and their programming, and the availability of very few distributional schemes, since linear correlations are a natural dependence measure, only if the joint distribution of the...
Persistent link: https://www.econbiz.de/10013080398
We compare real-time density forecasts for the euro area using three DSGE models. The benchmark is the Smets-Wouters model and its forecasts of real GDP growth and inflation are compared with those from two extensions. The first adds financial frictions and expands the observables to include a...
Persistent link: https://www.econbiz.de/10011813503
This paper compares within-sample and out-of-sample fit of a DSGE model with rational expectations to a model with adaptive learning. The Galí, Smets and Wouters model is the chosen laboratory using quarterly real-time euro area data vintages, covering 2001Q1-2019Q4. The adaptive learning model...
Persistent link: https://www.econbiz.de/10013492913
The ability of Google Trends data to forecast the number of new daily cases and deaths of COVID-19 is examined using a dataset of 158 countries. The analysis includes the computations of lag correlations between confirmed cases and Google data, Granger causality tests, and an out-of-sample...
Persistent link: https://www.econbiz.de/10012826063
The use of large datasets for macroeconomic forecasting has received a great deal of interest recently. Boosting is one possible method of using high-dimensional data for this purpose. It is a stage-wise additive modelling procedure, which, in a linear specification, becomes a variable selection...
Persistent link: https://www.econbiz.de/10009721997
The use of large datasets for macroeconomic forecasting has received a great deal of interest recently. Boosting is one possible method of using high-dimensional data for this purpose. It is a stage-wise additive modelling procedure, which, in a linear specification, becomes a variable selection...
Persistent link: https://www.econbiz.de/10013085278
We compare real-time density forecasts for the euro area using three DSGE models. The benchmark is the Smets-Wouters model and its forecasts of real GDP growth and inflation are compared with those from two extensions. The first adds financial frictions and expands the observables to include a...
Persistent link: https://www.econbiz.de/10012921899
The period of extraordinary volatility in euro area headline inflation starting in 2007 raised the question whether forecast combination methods can be used to hedge against bad forecast performance of single models during such periods and provide more robust forecasts. We investigate this issue...
Persistent link: https://www.econbiz.de/10011579164
This paper develops Area-wide Leading Inflation CyclE (ALICE) indicators for euro area headline and core inflation with an aim to provide early signals about turning points in the respective inflation cycle. The series included in the two composite leading indicators are carefully selected from...
Persistent link: https://www.econbiz.de/10011901421