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dc.contributor.authorHärdle, Wolfgang Karlen_US
dc.contributor.authorMungo, Juliusen_US
dc.date.accessioned2008-02-21en_US
dc.date.accessioned2009-07-23T15:03:31Z-
dc.date.available2009-07-23T15:03:31Z-
dc.date.issued2008en_US
dc.identifier.urihttp://hdl.handle.net/10419/25248-
dc.description.abstractEmpirical studies have shown that a large number of financial asset returns exhibit fat tails and are often characterized by volatility clustering and asymmetry. Also revealed as a stylized fact is Long memory or long range dependence in market volatility, with significant impact on pricing and forecasting of market volatility. The implication is that models that accomodate long memory hold the promise of improved long-run volatility forecast as well as accurate pricing of long-term contracts. On the other hand, recent focus is on whether long memory can affect the measurement of market risk in the context of Value-at- Risk (V aR). In this paper, we evaluate the Value-at-Risk (V aR) and Expected Shortfall (ESF) in financial markets under such conditions. We examine one equity portfolio, the British FTSE100 and three stocks of the German DAX index portfolio (Bayer, Siemens and Volkswagen). Classical V aR estimation methodology such as exponential moving average (EMA) as well as extension to cases where long memory is an inherent characteristics of the system are investigated. In particular, we estimate two long memory models, the Fractional Integrated Asymmetric Power-ARCH and the Hyperbolic-GARCH with different error distribution assumptions. Our results show that models that account for asymmetries in the volatility specifications as well as fractional integrated parametrization of the volatility process, perform better in predicting the one-step as well as five-step ahead V aR and ESF for short and long positions than short memory models. This suggests that for proper risk valuation of options, the degree of persistence should be investigated and appropriate models that incorporate the existence of such characteristic be taken into account.en_US
dc.language.isoengen_US
dc.publisherSFB 649, Economic Risk Berlinen_US
dc.relation.ispartofseriesSFB 649 discussion paper 2008,006en_US
dc.subject.jelC14en_US
dc.subject.jelC32en_US
dc.subject.jelC52en_US
dc.subject.jelC53en_US
dc.subject.jelG12en_US
dc.subject.ddc330en_US
dc.subject.keywordBacktestingen_US
dc.subject.keywordValue-at-Risken_US
dc.subject.keywordExpected Shortfallen_US
dc.subject.keywordLong Memoryen_US
dc.subject.keywordFractional Integrated Volatility Modelsen_US
dc.subject.stwValue at Risken_US
dc.subject.stwZeitreihenanalyseen_US
dc.subject.stwBörsenkursen_US
dc.subject.stwVolatilitäten_US
dc.subject.stwARCH-Modellen_US
dc.subject.stwTheorieen_US
dc.subject.stwSchätzungen_US
dc.subject.stwAktienindexen_US
dc.subject.stwGroßbritannienen_US
dc.subject.stwDeutschlanden_US
dc.titleValue-at-risk and expected shortfall when there is long range dependenceen_US
dc.typeWorking Paperen_US
dc.identifier.ppn558749348en_US
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungen-
Appears in Collections:SFB 649 Discussion Papers, HU Berlin

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