<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-06-07T21:21:41Z</responseDate><request verb="GetRecord" identifier="oai:docta.ucm.es:20.500.14352/49255" metadataPrefix="mods">https://docta.ucm.es/rest/oai/request</request><GetRecord><record><header><identifier>oai:docta.ucm.es:20.500.14352/49255</identifier><datestamp>2023-11-14T07:19:17Z</datestamp><setSpec>com_20.500.14352_14</setSpec><setSpec>col_20.500.14352_17</setSpec></header><metadata><mods:mods xmlns:mods="http://www.loc.gov/mods/v3" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:doc="http://www.lyncode.com/xoai" xsi:schemaLocation="http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-1.xsd">
   <mods:name>
      <mods:namePart>Caporin, Massimiliano</mods:namePart>
   </mods:name>
   <mods:name>
      <mods:namePart>McAleer, Michael</mods:namePart>
   </mods:name>
   <mods:extension>
      <mods:dateAvailable encoding="iso8601">2023-06-20T09:17:42Z</mods:dateAvailable>
   </mods:extension>
   <mods:extension>
      <mods:dateAccessioned encoding="iso8601">2023-06-20T09:17:42Z</mods:dateAccessioned>
   </mods:extension>
   <mods:originInfo>
      <mods:dateIssued encoding="iso8601">2009-03</mods:dateIssued>
   </mods:originInfo>
   <mods:identifier type="uri">https://hdl.handle.net/20.500.14352/49255</mods:identifier>
   <mods:identifier type="relatedurl">https://www.ucm.es/icae</mods:identifier>
   <mods:abstract>DAMGARCH is a new model that extends the VARMA-GARCH model of Ling and McAleer (2003) by introducing multiple thresholds and time-dependent structure in the asymmetry of the conditional variances. Analytical expressions for the news impact surface implied by the new model are also presented. DAMGARCH models the shocks affecting the conditional variances on the basis of an underlying multivariate distribution. It is possible to model explicitly asset-specific shocks and common innovations by partitioning the multivariate density support. This paper presents the model structure, describes the implementation issues, and provides the conditions for the existence of a unique stationary solution, and for consistency and asymptotic normality of the quasi-maximum likelihood estimators. The paper also presents an empirical example to highlight the usefulness of the new model.</mods:abstract>
   <mods:language>
      <mods:languageTerm>eng</mods:languageTerm>
   </mods:language>
   <mods:accessCondition type="useAndReproduction">open access</mods:accessCondition>
   <mods:titleInfo>
      <mods:title>Thresholds, News Impact Surfaces and Dynamic Asymmetric Multivariate GARCH</mods:title>
   </mods:titleInfo>
   <mods:genre>technical report</mods:genre>
</mods:mods></metadata></record></GetRecord></OAI-PMH>