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Consistent ranking of multivariate volatility models
LAURENT, Sebastien; ROMBOUTS, Jeroen V.K.; VIOLANTE, … - Center for Operations Research and Econometrics (CORE), … - 2009
framework. This paper examines the ranking of multivariate volatility models in terms of their ability to forecast out … evaluate the distance between the true covariance matrix and its forecast. The evaluation of multivariate volatility models … requires the use of a proxy for the unobservable volatility matrix which may shift the ranking of the models. Therefore, to …
Persistent link: https://www.econbiz.de/10008550212
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Understanding volatility dynamics in the EU-ETS market: lessons from the future
SANIN, Maria Eugenia; VIOLANTE, Francesco - Center for Operations Research and Econometrics (CORE), … - 2009
model returns and volatility dynamics of this price showing that a standard ARMA-GARCH framework is not adequate and that … the gaussianity assumption is rejected due to the occurrence of a number of level and volatility outliers. To improve the … sharp increases in volume increase volatility even in the absence of changes in what recent literature considers as market …
Persistent link: https://www.econbiz.de/10008494369
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The value of multivariate model sophistication: an application to pricing Dow Jones Industrial Average options
ROMBOUTS, Jeroen V. K.; STENTOFT, Lars; VIOLANTE, Francesco - Center for Operations Research and Econometrics (CORE), … - 2012
We assess the predictive accuracy of a large number of multivariate volatility models in terms of pricing options on …
Persistent link: https://www.econbiz.de/10010610494
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On the forecasting accuracy of multivariate GARCH models
LAURENT, Sébastien; ROMBOUTS, Jeroen V. K.; VIOLANTE, … - Center for Operations Research and Econometrics (CORE), … - 2010
This paper addresses the question of the selection of multivariate GARCH models in terms of variance matrix forecasting accuracy with a particular focus on relatively large scale problems. We consider 10 assets from NYSE and NASDAQ and compare 125 model based one-step-ahead conditional variance...
Persistent link: https://www.econbiz.de/10008642224
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Estimation and empirical performance of non-scalar dynamic conditional correlation models
BAUWENS, Luc; GRIGORYEVA, Lyudmila; ORTEGA, Juan-Pablo - Center for Operations Research and Econometrics (CORE), … - 2014
This paper presents a method capable of estimating richly parametrized versions of the dynamic conditional correlation (DCC) model that go beyond the standard scalar case. The algorithm is based on the maximization of a Gaussian quasi-likelihood using a Bregman-proximal trust-region method to...
Persistent link: https://www.econbiz.de/10011094065
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Clustered panel data models: an efficient approach for nowcasting from poor data
MOUCHART, Michel; ROMBOUTS, Jeroen - Center for Operations Research and Econometrics (CORE), … - 2003
Nowcasting regards the inference on the present realization of random variables, on the basis of information available until a recent past. This paper proposes a modelling strategy aimed at a best use of the data for nowcasting based on panel data with severe deficiencies, namely short times...
Persistent link: https://www.econbiz.de/10005008511
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Specification, estimation and evaluation of vector smooth transition autoregressive models with applications
Terasvirta, Timo; Yang, Yukai - Center for Operations Research and Econometrics (CORE), … - 2014
We consider a nonlinear vector model called the logistic vector smooth transition autoregressive model. The bivariate single-transition vector smooth transition regression model of Camacho (2004) is generalised to a multivariate and multitransition one. A modelling strategy consisting of...
Persistent link: https://www.econbiz.de/10011246311
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Intra-daily FX optimal portfolio allocation
BAUWENS, Luc; BEN OMRANE, Walid; RENGIFO, Erick - Center for Operations Research and Econometrics (CORE), … - 2006
We design and implement optimal foreign exchange portfolio allocations. An optimal allocation maximizes the expected return sub ject to a Value-at-Risk (VaR) constraint. Based on intradaily data, the optimization procedure is carried out at regular time intervals. For the estimation of the...
Persistent link: https://www.econbiz.de/10005065278
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Asymmetric CAPM dependence for large dimensions: the Canonical Vine Autoregressive Model
HEINEN, Andréas; VALDESOGO, Alfonso - Center for Operations Research and Econometrics (CORE), … - 2009
We propose a new dynamic model for volatility and dependence in high dimensions, that allows for departures from the …
Persistent link: https://www.econbiz.de/10008550163
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Multivariate volatility modeling of electricity futures
bauwens, Luc; hafner, Christian; pierret, Diane - Center for Operations Research and Econometrics (CORE), … - 2011
The deregulation of European electricity markets has led to an increasing need in understanding the volatility and …
Persistent link: https://www.econbiz.de/10010610461