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Exploiting the Errors: A Simple Approach for Improved Volatility Forecasting

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

We propose a new family of easy-to-implement realized volatility based forecasting models. The models exploit the …

Persistent link: https://www.econbiz.de/10011207425

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

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

Semiparametric Modelling and Estimation: A Selective Overview

Kristensen, Dennis - School of Economics and Management, University of Aarhus - 2009

Semiparametric models are characterized by a finite- and infinite-dimensional (functional) component. As such they allow for added flexibility over fully parametric models, and at the same time estimators of parametric components can be developed that exhibit standard parametric convergence...

Persistent link: https://www.econbiz.de/10008506834

Understanding volatility dynamics in the EU-ETS market

Sanin, Maria Eugenia; Mansanet-Bataller, Maria; … - School of Economics and Management, University of Aarhus - 2015

We study the short-term price behavior of Phase 2 EU emission allowances. We model returns and volatility dynamics, and we demonstrate that a standard ARMAX-GARCH framework is inadequate for this modeling and that the gaussianity assumption is rejected due to a number of outliers. To improve the...

Persistent link: https://www.econbiz.de/10011158461

Outlier Detection in Structural Time Series Models: the Indicator Saturation Approach

Marczak, Martyna; Proietti, Tommaso - School of Economics and Management, University of Aarhus - 2014

Structural change affects the estimation of economic signals, like the underlying growth rate or the seasonally adjusted series. An important issue, which has attracted a great deal of attention also in the seasonal adjustment literature, is its detection by an expert procedure. The...

Persistent link: https://www.econbiz.de/10010885055

Thresholds and Smooth Transitions in Vector Autoregressive Models

Hubrich, Kirstin; Teräsvirta, Timo - School of Economics and Management, University of Aarhus - 2013

This survey focuses on two families of nonlinear vector time series models, the family of Vector Threshold Regression models and that of Vector Smooth Transition Regression models. These two model classes contain incomplete models in the sense that strongly exogeneous variables are allowed in...

Persistent link: https://www.econbiz.de/10010886057

A Mixture Innovation Heterogeneous Autoregressive Model for Structural Breaks and Long Memory

Nonejad, Nima - School of Economics and Management, University of Aarhus - 2013

. Results show that the proposed model is viable and flexible for purposes of forecasting volatility. Model uncertainty is …

Persistent link: https://www.econbiz.de/10010851263

Model Selection in Kernel Ridge Regression

Exterkate, Peter - School of Economics and Management, University of Aarhus - 2012

Kernel ridge regression is gaining popularity as a data-rich nonlinear forecasting tool, which is applicable in many …

Persistent link: https://www.econbiz.de/10010851278

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 component as in Amado and Teräsvirta...

Persistent link: https://www.econbiz.de/10009652370