المستودع الأكاديمي جامعة المدينة

Modelling dynamic portfolio risk using risk drivers of elliptical processes

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dc.creator Schmidt, Rafael
dc.creator Schmieder, Christian
dc.date 2007
dc.date.accessioned 2013-10-16T07:06:44Z
dc.date.available 2013-10-16T07:06:44Z
dc.date.issued 2013-10-16
dc.identifier http://hdl.handle.net/10419/19766
dc.identifier ppn:533619017
dc.identifier RePEc:zbw:bubdp2:5608
dc.identifier.uri http://koha.mediu.edu.my:8181/xmlui/handle/10419/19766
dc.description The situation of a limited availability of historical data is frequently encountered in portfolio risk estimation, especially in credit risk estimation. This makes it, for example, difficult to find temporal structures with statistical significance in the data on the single asset level. By contrast, there is often a broader availability of cross-sectional data, i.e., a large number of assets in the portfolio. This paper proposes a stochastic dynamic model which takes this situation into account. The modelling framework is based on multivariate elliptical processes which model portfolio risk via sub-portfolio specific volatility indices called portfolio risk drivers. The dynamics of the risk drivers are modelled by multiplicative error models (MEM) - as introduced by Engle (2002) - or by traditional ARMA models. The model is calibrated to Moody's KMV Credit Monitor asset returns (also known as firm-value returns) given on a monthly basis for 756 listed European companies at 115 time points from 1996 to 2005. This database is used by financial institutions to assess the credit quality of firms. The proposed risk drivers capture the volatility structure of asset returns in different industry sectors. A characteristic temporal structure of the risk drivers, cyclical as well as a seasonal, is found across all industry sectors. In addition, each risk driver exhibits idiosyncratic developments. We also identify correlations between the risk drivers and selected macroeconomic variables. These findings may improve the estimation of risk measures such as the (portfolio) Value at Risk. The proposed methods are general and can be applied to any series of multivariate asset or equity returns in finance and insurance.
dc.language eng
dc.relation Discussion Paper, Series 2: Banking and Financial Supervision 2007,07
dc.rights http://www.econstor.eu/dspace/Nutzungsbedingungen
dc.subject C13
dc.subject C16
dc.subject C51
dc.subject ddc:330
dc.subject Portfolio risk modelling
dc.subject Elliptical processes
dc.subject Credit risk
dc.subject multiplicative error model
dc.subject volatility clustering
dc.subject Portfolio-Management
dc.subject Risiko
dc.subject Volatilität
dc.subject Stochastischer Prozess
dc.subject Kreditrisiko
dc.subject Schätzung
dc.subject Theorie
dc.subject Welt
dc.title Modelling dynamic portfolio risk using risk drivers of elliptical processes
dc.type doc-type:workingPaper


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