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Forecasting Macroeconomic Variables using Neural Network Models and Three Automated Model Selection Techniques
Kock, Anders Bredahl; Teräsvirta, Timo - School of Economics and Management, University of Aarhus - 2011
In this paper we consider the forecasting performance of a well-defined class of flexible models, the so-called single hidden-layer feedforward neural network models. A major aim of our study is to find out whether they, due to their flexibility, are as useful tools in economic forecasting as...
Persistent link: https://www.econbiz.de/10009277000
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Forecasting performance of three automated modelling techniques during the economic crisis 2007-2009
Kock, Anders Bredahl; Teräsvirta, Timo - School of Economics and Management, University of Aarhus - 2011
In this work we consider forecasting macroeconomic variables dur- ing an economic crisis. The focus is on a specific class of models, the so-called single hidden-layer feedforward autoregressive neural net- work models. What makes these models interesting in the present context is that they form...
Persistent link: https://www.econbiz.de/10009283381
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Global Hemispheric Temperature Trends and Co–Shifting: A Shifting Mean Vector Autoregressive Analysis
Holt, Matthew T.; Teräsvirta, Timo - School of Economics and Management, University of Aarhus - 2012
This paper examines trends in annual temperature data for the northern and southern hemisphere (1850-2010) by using variants of the shifting-mean autoregressive (SM-AR) model of González and Teräsvirta (2008). Univariate models are first fitted to each series by using the so called QuickShift...
Persistent link: https://www.econbiz.de/10010851222
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Modelling Changes in the Unconditional Variance of Long Stock Return Series
Amado, Cristina; Teräsvirta, Timo - School of Economics and Management, University of Aarhus - 2012
In this paper we develop a testing and modelling procedure for describing the long-term volatility movements over very … long return series. For the purpose, we assume that volatility is multiplicatively decomposed into a conditional and an … unconditional variance. Second, the results show that the long-memory property in volatility may be explained by ignored changes in …
Persistent link: https://www.econbiz.de/10009652370
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Forecasting inflation with gradual regime shifts and exogenous information
González, Andrés; Hubrich, Kirstin; Teräsvirta, Timo - School of Economics and Management, University of Aarhus - 2009
In this work, we make use of the shifting-mean autoregressive model which is a flexible univariate nonstationary model. It is suitable for describing characteristic features in inflation series as well as for medium-term forecasting. With this model we decompose the inflation process into a...
Persistent link: https://www.econbiz.de/10005787545
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Forecasting with nonlinear time series models
Kock, Anders Bredahl; Teräsvirta, Timo - School of Economics and Management, University of Aarhus - 2010
In this paper, nonlinear models are restricted to mean nonlinear parametric models. Several such models popular in time series econometrics are presented and some of their properties discussed. This includes two models based on universal approximators: the Kolmogorov-Gabor polynomial model and...
Persistent link: https://www.econbiz.de/10008556269
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The cyclical component factor model
Dahl, Christian M.; Hansen, Henrik; Smidt, John - School of Economics and Management, University of Aarhus - 2008
Forecasting using factor models based on large data sets have received ample attention due to the models’ ability to increase forecast accuracy with respect to a range of key macroeconomic variables in the US and the UK. However, forecasts based on such factor models do not uniformly...
Persistent link: https://www.econbiz.de/10005440058
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Modeling and Forecasting the Distribution of Energy Forward Returns - Evidence from the Nordic Power Exchange
Lunde, Asger; Olesen, Kasper V. - School of Economics and Management, University of Aarhus - 2014
analyze empirical results for a selection of existing realized measures of volatility and incorporate them in a Realized GARCH … framework for the joint modeling of returns and realized measures of volatility. An influential bias in these measures is … over time, which stresses the importance of careful modeling and forecasting of volatility. We show that improved model fit …
Persistent link: https://www.econbiz.de/10010945126
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Return Predictability, Model Uncertainty, and Robust Investment
Lukas, Manuel - School of Economics and Management, University of Aarhus - 2011
Stock return predictability is subject to great uncertainty. In this paper we use the model confidence set approach to quantify uncertainty about expected utility from investment, accounting for potential return predictability. For monthly US data and six representative return prediction models,...
Persistent link: https://www.econbiz.de/10009371458
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EuroMInd-D: A Density Estimate of Monthly Gross Domestic Product for the Euro Area
Proietti, Tommaso; Marczak, Martyna; Mazzi, Gianluigi - School of Economics and Management, University of Aarhus - 2015
EuroMInd-D is a density estimate of monthly gross domestic product (GDP) constructed according to a bottom–up approach, pooling the density estimates of eleven GDP components, by output and expenditure type. The components density estimates are obtained from a medium-size dynamic factor model...
Persistent link: https://www.econbiz.de/10011186679