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Cointegration test with stationary covariates and the CDS-bond basis during the financial crisis

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  • Aaron L. Game
  • Jason J. Wu

Abstract

This paper proposes a residual based cointegration test with improved power. Based on the idea of Hansen (1995) and Elliott & Jansson (2003) in the unit root testing case, stationary covariates are used to improve the power of the residual based Augmented Dickey Fuller (ADF) test. The asymptotic null distribution contains difficult to estimate nuisance parameters for which there is no obvious method of estimation, therefore we propose a bootstrap methodology to obtain test critical values. Local-to-unity asymptotics and Monte Carlo simulations are used to evaluate the power of the test in large and small samples, respectively. These exercises show that the addition of covariates increases power relative to the ADF and Johansen tests, and that the power depends on the long-run correlation between the covariates and the cointegration candidates. The new test is used to test for cointegration between Credit Default Swap (CDS) and corporate bond spreads for a panel of U.S. firms during the 2007-2009 financial crisis. The new test finds stronger evidence for cointegration between the two spreads for more firms, relative to ADF and Johansen tests.

Suggested Citation

  • Aaron L. Game & Jason J. Wu, 2011. "Cointegration test with stationary covariates and the CDS-bond basis during the financial crisis," Finance and Economics Discussion Series 2011-18, Board of Governors of the Federal Reserve System (U.S.).
  • Handle: RePEc:fip:fedgfe:2011-18
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    References listed on IDEAS

    as
    1. Jan De Wit, 2006. "Exploring the CDS-Bond Basis," Working Paper Research 104, National Bank of Belgium.
    2. Didier Cossin & Tomas Hricko & Daniel Aunon-Nerin & Zhijiang Huang, 2002. "Exploring for the Determinants of Credit Risk in Credit Default Swap Transaction Data: Is Fixed-Income Markets’ Information Suffcient to Evaluate Credit Risk?," FAME Research Paper Series rp65, International Center for Financial Asset Management and Engineering.
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    Keywords

    Swaps (Finance); Corporate bonds; Econometric models;
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