Nonlinear Term Structure Dependence: Copula Functions, Empirics, and Risk Implications
AbstractThis paper documents nonlinear cross-sectional dependence in the term structure of U.S. Treasury yields and points out risk management implications. The analysis is based on a Kalman filter estimation of a two-factor affine model which specifies the yield curve dynamics. We then apply a broad class of copula functions for modeling dependence in factors spanning the yield curve. Our sample of monthly yields in the 1982 to 2001 period provides evidence of upper tail dependence in yield innovations; i.e., large positive interest rate shocks tend to occur under increased dependence. In contrast, the best fitting copula model coincides with zero lower tail dependence. This asymmetry has substantial risk management implications. We give an example in estimating bond portfolio loss quantiles and report the biases which result from an application of the normal dependence model.
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Bibliographic InfoPaper provided by EconWPA in its series Econometrics with number 0401007.
Length: 50 pages
Date of creation: 30 Jan 2004
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affine term structure models; nonlinear dependence; copula functions; tail dependence; value-at-risk;
Find related papers by JEL classification:
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
- G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
This paper has been announced in the following NEP Reports:
- NEP-ALL-2004-02-01 (All new papers)
- NEP-FMK-2004-02-01 (Financial Markets)
- NEP-MAC-2004-02-01 (Macroeconomics)
- NEP-RMG-2004-02-01 (Risk Management)
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