Show simple item record

2008-01-07Buch DOI: 10.18452/4097
Value-at-Risk and Expected Shortfall when there is long range dependence
dc.contributor.authorHärdle, Wolfgang Karl
dc.contributor.authorMungo, Julius
dc.date.accessioned2017-06-15T23:36:31Z
dc.date.available2017-06-15T23:36:31Z
dc.date.created2008-01-10
dc.date.issued2008-01-07
dc.identifier.issn1860-5664
dc.identifier.urihttp://edoc.hu-berlin.de/18452/4749
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.eng
dc.language.isoeng
dc.publisherHumboldt-Universität zu Berlin, Wirtschaftswissenschaftliche Fakultät
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/
dc.subjectLong Memoryeng
dc.subjectValue-at-Riskeng
dc.subjectExpected Shortfalleng
dc.subjectFractional Integrated Volatility Modelseng
dc.subjectBacktestingeng
dc.subject.ddc330 Wirtschaft
dc.titleValue-at-Risk and Expected Shortfall when there is long range dependence
dc.typebook
dc.identifier.urnurn:nbn:de:kobv:11-10083078
dc.identifier.doihttp://dx.doi.org/10.18452/4097
local.edoc.container-titleSonderforschungsbereich 649: Ökonomisches Risiko
local.edoc.pages40
local.edoc.type-nameBuch
local.edoc.container-typeseries
local.edoc.container-type-nameSchriftenreihe
local.edoc.container-volume2008
local.edoc.container-issue6
local.edoc.container-year2008
local.edoc.container-erstkatid2195055-6

Show simple item record