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Evaluating interest rate covariance models within a value-at-risk framework

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  • Miguel A. Ferreira
  • Jose A. Lopez

Abstract

We find that covariance matrix forecasts for an international interest rate portfolio generated by a model that incorporates interest-rate level volatility effects perform best with respect to statistical loss functions. However, within a value-at-risk (VaR) framework, the relative performance of the covariance matrix forecasts depends greatly on the VaR distributional assumption. Simple forecasts based just on weighted averages of past observations perform best using a VaR framework. In fact, we find that portfolio variance forecasts that ignore the individual assets in the portfolio generate the lowest regulatory capital charge, a key economic decision variable for commercial banks. Our results provide empirical support for the commonly-used VaR models based on simple covariance matrix forecasts and distributional assumptions.

Suggested Citation

  • Miguel A. Ferreira & Jose A. Lopez, 2004. "Evaluating interest rate covariance models within a value-at-risk framework," Working Paper Series 2004-03, Federal Reserve Bank of San Francisco.
  • Handle: RePEc:fip:fedfwp:2004-03
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    Cited by:

    1. Louzis, Dimitrios P. & Xanthopoulos-Sisinis, Spyros & Refenes, Apostolos P., 2011. "Are realized volatility models good candidates for alternative Value at Risk prediction strategies?," MPRA Paper 30364, University Library of Munich, Germany.
    2. Saker Sabkha & Christian De Peretti & Dorra Hmaied, 2017. "The Credit Default Swap market contagion during recent crises: International evidence," Working Papers hal-01572510, HAL.
    3. Dimitrios P. Louzis & Spyros Xanthopoulos‐Sisinis & Apostolos P. Refenes, 2013. "The Role of High‐Frequency Intra‐daily Data, Daily Range and Implied Volatility in Multi‐period Value‐at‐Risk Forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(6), pages 561-576, September.
    4. Louzis, Dimitrios P. & Xanthopoulos-Sisinis, Spyros & Refenes, Apostolos P., 2014. "Realized volatility models and alternative Value-at-Risk prediction strategies," Economic Modelling, Elsevier, vol. 40(C), pages 101-116.
    5. Massimiliano Caporin & Michael McAleer, 2010. "Ranking Multivariate GARCH Models by Problem Dimension," CARF F-Series CARF-F-219, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    6. Chkili, Walid & Aloui, Chaker & Nguyen, Duc Khuong, 2012. "Asymmetric effects and long memory in dynamic volatility relationships between stock returns and exchange rates," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 22(4), pages 738-757.
    7. Caporin, Massimiliano & McAleer, Michael, 2014. "Robust ranking of multivariate GARCH models by problem dimension," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 172-185.
    8. de Goeij, P. C. & Marquering, W., 2004. "Modeling the conditional covariance between stock and bond returns : A multivariate GARCH approach," Other publications TiSEM 94fe5ada-715a-4339-b94c-f, Tilburg University, School of Economics and Management.
    9. Andrew J. Patton & Kevin Sheppard, 2008. "Evaluating Volatility and Correlation Forecasts," OFRC Working Papers Series 2008fe22, Oxford Financial Research Centre.
    10. Kalbaska, A. & Gątkowski, M., 2012. "Eurozone sovereign contagion: Evidence from the CDS market (2005–2010)," Journal of Economic Behavior & Organization, Elsevier, vol. 83(3), pages 657-673.
    11. repec:eee:empfin:v:45:y:2018:i:c:p:243-268 is not listed on IDEAS
    12. Massimiliano Caporin & Michael McAleer, 2011. "Ranking Multivariate GARCH Models by Problem Dimension: An Empirical Evaluation," Documentos de Trabajo del ICAE 2011-20, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    13. João Caldeira & Guilherme Moura & André Santos, 2015. "Measuring Risk in Fixed Income Portfolios using Yield Curve Models," Computational Economics, Springer;Society for Computational Economics, vol. 46(1), pages 65-82, June.
    14. Vasiliki D. Skintzi & Spyros Xanthopoulos-Sisinis, 2007. "Evaluation of correlation forecasting models for risk management," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(7), pages 497-526.
    15. Coudert, Virginie & Gex, Mathieu, 2010. "Contagion inside the credit default swaps market: The case of the GM and Ford crisis in 2005," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 20(2), pages 109-134, April.
    16. Mitra, Sovan & Date, Paresh & Mamon, Rogemar & Wang, I-Chieh, 2013. "Pricing and risk management of interest rate swaps," European Journal of Operational Research, Elsevier, vol. 228(1), pages 102-111.
    17. de Goeij, Peter & Marquering, Wessel, 2009. "Stock and bond market interactions with level and asymmetry dynamics: An out-of-sample application," Journal of Empirical Finance, Elsevier, vol. 16(2), pages 318-329, March.
    18. repec:spt:apfiba:v:7:y:2017:i:5:f:7_5_6 is not listed on IDEAS
    19. Saker Sabkha & Christian De Peretti & Dorra Hmaied, 2018. "The Credit Default Swap market contagion during recent crises: International evidence," Post-Print hal-01572510, HAL.
    20. Wang, Kai-Li & Fawson, Christopher & Chen, Mei-Ling & Wu, An-Chi, 2014. "Characterizing information flows among spot, deliverable forward and non-deliverable forward exchange rate markets: A cross-country comparison," Pacific-Basin Finance Journal, Elsevier, vol. 27(C), pages 115-137.
    21. Wang Yu-Jen & Chung Huimin & Guo Jia-Hau, 2013. "A value-at-risk analysis of carry trades using skew-GARCH models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(4), pages 439-459, September.
    22. de Goeij, P. C. & Marquering, W., 2009. "Stock and bond market interactions with level and asymmetry dynamics : An out-of-sample application," Other publications TiSEM fa1d33b9-7e68-4e15-b211-e, Tilburg University, School of Economics and Management.

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    Keywords

    Interest rates ; Forecasting ; Risk management;

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