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Forecasting Medium and Large Datasets with Vector Autoregressive Moving Average (VARMA) Models

Dias, Gustavo Fruet; Kapetanios, George - School of Economics and Management, University of Aarhus - 2014

We address the issue of modelling and forecasting macroeconomic variables using medium and large datasets, by adopting …

Persistent link: https://www.econbiz.de/10010940885

Dynamic Factor Models for the Volatility Surface

Wel, Michel van der; Ozturk, Sait R.; Dijk, Dick van - School of Economics and Management, University of Aarhus - 2015

The implied volatility surface is the collection of volatilities implied by option contracts for different strike prices and time-to-maturity. We study factor models to capture the dynamics of this three-dimensional implied volatility surface. Three model types are considered to examine...

Persistent link: https://www.econbiz.de/10011186678

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

Combining Long Memory and Level Shifts in Modeling and Forecasting the Volatility of Asset Returns

Varneskov, Rasmus Tangsgaard; Perron, Pierre - School of Economics and Management, University of Aarhus - 2011

We propose a parametric state space model with accompanying estimation and forecasting framework that combines long … process, the model consistently belongs to the 10% Model Confidence Set when considering out-of-sample forecasting performance … as the only one among four competing dynamic models for all forecasting horizons when applied to high frequency stock …

Persistent link: https://www.econbiz.de/10009150791

Oracle Efficient Estimation and Forecasting with the Adaptive LASSO and the Adaptive Group LASSO in Vector Autoregressions

Kock, Anders Bredahl; Callot, Laurent A.F. - School of Economics and Management, University of Aarhus - 2012

variable selection and estimation in one step. We evaluate the forecasting accuracy of these estimators for a large set of …

Persistent link: https://www.econbiz.de/10010851261

The Value of Multivariate Model Sophistication: An Application to pricing Dow Jones Industrial Average options

Rombouts, Jeroen V.K.; Stentoft, Lars; Violante, Francesco - School of Economics and Management, University of Aarhus - 2012

We assess the predictive accuracy of a large number of multivariate volatility models in terms of pricing options on the Dow Jones Industrial Average. We measure the value of model sophistication in terms of dollar losses by considering a set 248 multivariate models that differ in their...

Persistent link: https://www.econbiz.de/10009492823

Modelling and Forecasting Multivariate Realized Volatility

Chiriac, Roxana; Voev, Valeri - School of Economics and Management, University of Aarhus - 2008

This paper proposes a methodology for modelling time series of realized covariance matrices in order to forecast multivariate risks. The approach allows for flexible dynamic dependence patterns and guarantees positive definiteness of the resulting forecasts without imposing parameter...

Persistent link: https://www.econbiz.de/10005440044

Daily House Price Indices: Construction, Modeling, and Longer-Run Predictions

Bollerslev, Tim; Patton, Andrew J.; Wang, Wenjing - School of Economics and Management, University of Aarhus - 2015

We construct daily house price indices for ten major U.S. metropolitan areas. Our calculations are based on a comprehensive database of several million residential property transactions and a standard repeat-sales method that closely mimics the methodology of the popular monthly Case-Shiller...

Persistent link: https://www.econbiz.de/10011118617

Oracle Inequalities for High Dimensional Vector Autoregressions

Kock, Anders Bredahl; Callot, Laurent A.F. - School of Economics and Management, University of Aarhus - 2012

This paper establishes non-asymptotic oracle inequalities for the prediction error and estimation accuracy of the LASSO in stationary vector autoregressive models. These inequalities are used to establish consistency of the LASSO even when the number of parameters is of a much larger order of...

Persistent link: https://www.econbiz.de/10010851258

On an Estimation Method for an Alternative Fractionally Cointegrated Model

Carlini, Federico; Lasak, Katarzyna - School of Economics and Management, University of Aarhus - 2014

In this paper we consider the Fractional Vector Error Correction model proposed in Avarucci (2007), which is characterized by a richer lag structure than models proposed in Granger (1986) and Johansen (2008, 2009). We discuss the identification issues of the model of Avarucci (2007), following...

Persistent link: https://www.econbiz.de/10010851285

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