Energy risk management through self-exciting marked point process

dc.creatorHerrera, R.
dc.date2013-10-24T21:02:06Z
dc.date2013-10-24T21:02:06Z
dc.date2013-07
dc.date.accessioned2017-03-07T15:00:15Z
dc.date.available2017-03-07T15:00:15Z
dc.identifierENERGY ECONOMICS Volume: 38 Pages: 64-76 DOI: 10.1016/j.eneco.2013.03.003
dc.identifier0140-9883
dc.identifierhttp://dspace.utalca.cl/handle/1950/9426
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/376435
dc.descriptionHerrera, R (reprint author) Univ Talca, Fac Ingn, Dept Modelac & Gest Ind, Camino Los Niches Km 1, Curico, Chile.
dc.descriptionCrude oil is a dynamically traded commodity that affects many economies. We propose a collection of marked self-exciting point processes with dependent arrival rates for extreme events in oil markets and related risk measures. The models treat the time among extreme events in oil markets as a stochastic process. The main advantage of this approach is its capability to capture the short, medium and long-term behavior of extremes without involving an arbitrary stochastic volatility model or a prefiltration of the data, as is common in extreme value theory applications. We make use of the proposed model in order to obtain an improved estimate for the Value at Risk in oil markets. Empirical findings suggest that the reliability and stability of Value at Risk estimates improve as a result of finer modeling approach. This is supported by an empirical application in the representative West Texas Intermediate (WTI) and Brent crude oil markets. (C) 2013 Elsevier B.V. All rights reserved.
dc.languageen
dc.publisherELSEVIER SCIENCE BV, PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS
dc.subjectExtreme value theory
dc.subjectEnergy market risk
dc.subjectEnergy forecasting
dc.subjectValue at Risk
dc.subjectMarked self-exciting point process
dc.titleEnergy risk management through self-exciting marked point process
dc.typeArtículos de revistas


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