Modeling and forecasting the oil volatility index

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Mostrar el registro sencillo del ítem Mariti, Massimo B. Gonçalves Mazzeu, Joao Henrique Lopes Moreira Da Veiga, María Helena
dc.contributor.other Universidad Carlos III de Madrid. Departamento de Estadística 2017-11-27T16:08:31Z 2017-11-27T16:08:31Z 2017-11
dc.identifier.issn 2387-0303
dc.description.abstract This paper models and forecasts the crude oil ETF volatility index (OVX). Themotivation lies on the evidence that the OVX has been used in the last years as an important alternative measure to track and analyze the volatility of future oil prices. The analysis of the OVX suggests that it presents similar features to those of the daily market volatility index. The main characteristic is the long range dependence that is modeled either by autoregressive fractional integrated moving averaging (ARFIMA) models or by heterogeneous autoregressive (HAR) specifications. Regarding the latter family of models, we first propose extensions of the HAR model that are based on the net and scale measures of oil prices changes. The aim is to improve the HAR model by including predictors that better capture the impact of oil price changes on the economy. Second, we test the forecasting performance of the new proposals and benchmarks with the model confidence set (MCS) and the Generalized-AutoContouR (G-ACR) tests interms of point forecasts and density forecasting, respectively. Our main findings are as follows: the new asymmetric proposals have superior predictive ability than the heterogeneous autoregressive leverage (HARL) model under two known loss functions. Regarding density forecasting, the best model is the one that includes the scale measureas a proxy of oil price changes and considers a flexible distribution for the errors.
dc.description.sponsorship Acknowledgements: The third author acknowledges financial support from Spanish Ministry of Economy and Competitiveness, research projects ECO2015-70331-C2-2-R and ECO2015-65701-P and from Fundação para a Ciência e a Tecnologia, grant UID/GES/00315/2013.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.relation.ispartofseries UC3M Working papers. Statistics and Econometrics
dc.relation.ispartofseries 17-18
dc.rights Atribución-NoComercial-SinDerivadas 3.0 España
dc.subject.other Forecasting OVX
dc.subject.other Heterogeneous autoregression
dc.subject.other Leverage
dc.subject.other Net oil price changes
dc.subject.other OVX
dc.subject.other Scale oil price changes
dc.title Modeling and forecasting the oil volatility index
dc.type workingPaper
dc.subject.jel Q40
dc.subject.jel C51
dc.subject.jel C52
dc.subject.jel C53
dc.relation.projectID Gobierno de España. ECO2015-70331-C2-2-R
dc.relation.projectID Gobierno de España. ECO2015-65701-P
dc.identifier.uxxi DT/0000001595
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