Modelling Dynamic Portfolio Risk Using Risk Drivers of Elliptical Processes

40 Pages Posted: 8 Jun 2016

See all articles by Rafael Schmidt

Rafael Schmidt

University of Cologne

Christian Schmieder

International Monetary Fund (IMF)

Date Written: 2007

Abstract

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.

Keywords: Portfolio risk modelling, Elliptical processes, Credit risk, multiplicative error model, volatility clustering

JEL Classification: C13, C16, C51

Suggested Citation

Schmidt, Rafael and Schmieder, Christian, Modelling Dynamic Portfolio Risk Using Risk Drivers of Elliptical Processes (2007). Bundesbank Series 2 Discussion Paper No. 2007,07, Available at SSRN: https://ssrn.com/abstract=2793992 or http://dx.doi.org/10.2139/ssrn.2793992

Rafael Schmidt (Contact Author)

University of Cologne ( email )

Albertus-Magnus-Platz
Cologne, 50923
Germany

Christian Schmieder

International Monetary Fund (IMF) ( email )

700 19th Street, N.W.
Washington, DC 20431
United States

Do you have negative results from your research you’d like to share?

Paper statistics

Downloads
49
Abstract Views
662
PlumX Metrics