ON CONDITIONAL MOMENTS OF GARCH MODELS, WITH APPLICATIONS TO MULTIPLE PERIOD VALUE AT RISK ESTIMATION
In this article, the exact conditional second, third and fourth moments of returns and their temporal aggregates are derived under Quadratic GARCH models. Three multiple period Value at Risk estimation methods are proposed. Two methods are based on the exact second to fourth moments and the other ad...
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Veröffentlicht in: | Statistica Sinica 2003-10, Vol.13 (4), p.1015-1044 |
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description | In this article, the exact conditional second, third and fourth moments of returns and their temporal aggregates are derived under Quadratic GARCH models. Three multiple period Value at Risk estimation methods are proposed. Two methods are based on the exact second to fourth moments and the other adopts a Monte Carlo approach. Some simulations show that the multiple period Value at Risk calculated from an asymmetric t-distribution with the variance, skewness parameter and the degrees of freedom chosen to match the second to fourth moments of the aggregate returns is close to the one obtained by Monte Carlo simulations. Using some market indices for illustration, the proposed Value at Risk estimation methods are found to be superior to some standard approaches such as RiskMetrics. |
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P.</creatorcontrib><title>ON CONDITIONAL MOMENTS OF GARCH MODELS, WITH APPLICATIONS TO MULTIPLE PERIOD VALUE AT RISK ESTIMATION</title><title>Statistica Sinica</title><description>In this article, the exact conditional second, third and fourth moments of returns and their temporal aggregates are derived under Quadratic GARCH models. Three multiple period Value at Risk estimation methods are proposed. Two methods are based on the exact second to fourth moments and the other adopts a Monte Carlo approach. Some simulations show that the multiple period Value at Risk calculated from an asymmetric t-distribution with the variance, skewness parameter and the degrees of freedom chosen to match the second to fourth moments of the aggregate returns is close to the one obtained by Monte Carlo simulations. Using some market indices for illustration, the proposed Value at Risk estimation methods are found to be superior to some standard approaches such as RiskMetrics.</description><subject>Analytical forecasting</subject><subject>Estimation methods</subject><subject>Estimators</subject><subject>Kurtosis</subject><subject>Mathematical moments</subject><subject>Modeling</subject><subject>Monte Carlo methods</subject><subject>Skewed distribution</subject><subject>Statistical Applications in Financial Econometrics</subject><subject>Statistical variance</subject><subject>T distribution</subject><issn>1017-0405</issn><issn>1996-8507</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2003</creationdate><recordtype>article</recordtype><sourceid/><recordid>eNotjF1rgzAYRmVssNL1JwzeHzDhjTEmuRRNa1g0onG7LNootGxsaG_27-c-rp7Dw-HcBBsiZRIKhvx2ZSQ8xBjZfbBblvOAKJERgXQTjLaCzFa5dtpWqYHSlqpyLdg9HNImK9YjV6Z9glftCkjr2ugs_XFbcBbKzjhdGwW1arTN4SU1nYLUQaPbZ1Ct0-Wv_BDcTf3bMu7-dxt0e-WyIjT2sPZMeCGcXUNOIi9jRILMezp5SQYRYcKEiPl4GqaJnCSjsReiT2I2ksTTaIoSOQyS96tCt8HjX_eyXD_m4-d8fu_nr2MUU-SESfoNPpZH6Q</recordid><startdate>20031001</startdate><enddate>20031001</enddate><creator>Wong, Chi-Ming</creator><creator>So, Mike K. P.</creator><general>Institute of Statistical Science, Academia Sinica and International Chinese Statistical Association</general><scope/></search><sort><creationdate>20031001</creationdate><title>ON CONDITIONAL MOMENTS OF GARCH MODELS, WITH APPLICATIONS TO MULTIPLE PERIOD VALUE AT RISK ESTIMATION</title><author>Wong, Chi-Ming ; So, Mike K. P.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-j175t-712d9400105dd3fd91b820658847ecbff1c9534d88a645e16d32f269bb97a47e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2003</creationdate><topic>Analytical forecasting</topic><topic>Estimation methods</topic><topic>Estimators</topic><topic>Kurtosis</topic><topic>Mathematical moments</topic><topic>Modeling</topic><topic>Monte Carlo methods</topic><topic>Skewed distribution</topic><topic>Statistical Applications in Financial Econometrics</topic><topic>Statistical variance</topic><topic>T distribution</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wong, Chi-Ming</creatorcontrib><creatorcontrib>So, Mike K. P.</creatorcontrib><jtitle>Statistica Sinica</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Wong, Chi-Ming</au><au>So, Mike K. P.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>ON CONDITIONAL MOMENTS OF GARCH MODELS, WITH APPLICATIONS TO MULTIPLE PERIOD VALUE AT RISK ESTIMATION</atitle><jtitle>Statistica Sinica</jtitle><date>2003-10-01</date><risdate>2003</risdate><volume>13</volume><issue>4</issue><spage>1015</spage><epage>1044</epage><pages>1015-1044</pages><issn>1017-0405</issn><eissn>1996-8507</eissn><abstract>In this article, the exact conditional second, third and fourth moments of returns and their temporal aggregates are derived under Quadratic GARCH models. Three multiple period Value at Risk estimation methods are proposed. Two methods are based on the exact second to fourth moments and the other adopts a Monte Carlo approach. Some simulations show that the multiple period Value at Risk calculated from an asymmetric t-distribution with the variance, skewness parameter and the degrees of freedom chosen to match the second to fourth moments of the aggregate returns is close to the one obtained by Monte Carlo simulations. Using some market indices for illustration, the proposed Value at Risk estimation methods are found to be superior to some standard approaches such as RiskMetrics.</abstract><pub>Institute of Statistical Science, Academia Sinica and International Chinese Statistical Association</pub><tpages>30</tpages></addata></record> |
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source | Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; JSTOR Mathematics & Statistics; Jstor Complete Legacy |
subjects | Analytical forecasting Estimation methods Estimators Kurtosis Mathematical moments Modeling Monte Carlo methods Skewed distribution Statistical Applications in Financial Econometrics Statistical variance T distribution |
title | ON CONDITIONAL MOMENTS OF GARCH MODELS, WITH APPLICATIONS TO MULTIPLE PERIOD VALUE AT RISK ESTIMATION |
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