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Default and liquidity regimes in the bond market during the 2002-2012 period

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  • Georges Dionne
  • Olfa Maalaoui Chun

Abstract

Using a realtime random regime shift technique, we identify and discuss two different regimes in the dynamics of credit spreads during 2002-2012: a liquidity regime and a default regime. Both regimes contribute to the patterns observed in credit spreads. The liquidity regime seems to explain the predictive power of credit risk on the 2007-2009 NBER recession, whereas the default regime drives the persistence of credit spreads over the same recession. Our results complement the recent dynamic structural models as well as monetary and credit supply effects models by empirically supporting two important patterns in credit spreads: the persistence and the predictive ability toward economic downturns.

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  • Georges Dionne & Olfa Maalaoui Chun, 2013. "Default and liquidity regimes in the bond market during the 2002-2012 period," Canadian Journal of Economics, Canadian Economics Association, vol. 46(4), pages 1160-1195, November.
  • Handle: RePEc:cje:issued:v:46:y:2013:i:4:p:1160-1195
    DOI: 10.1111/caje.12057
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    Cited by:

    1. Beaupain, Renaud & Durré, Alain, 2016. "Excess liquidity and the money market in the euro area," Journal of Macroeconomics, Elsevier, vol. 47(PA), pages 33-44.
    2. Anténor-Habazac, Cassandre & Dionne, Georges & Guesmi, Sahar, 2018. "Cyclical variations in liquidity risk of corporate bonds," Working Papers 18-3, HEC Montreal, Canada Research Chair in Risk Management.
    3. Stephanie Heck, 2022. "Corporate bond yields and returns: a survey," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 36(2), pages 179-201, June.
    4. Díaz, Antonio & Escribano, Ana, 2020. "Measuring the multi-faceted dimension of liquidity in financial markets: A literature review," Research in International Business and Finance, Elsevier, vol. 51(C).
    5. Maalaoui Chun, Olfa & Dionne, Georges & François, Pascal, 2014. "Credit spread changes within switching regimes," Journal of Banking & Finance, Elsevier, vol. 49(C), pages 41-55.
    6. Okou, Cedric & Maalaoui Chun, Olfa & Dionne, Georges & Li, Jingyuan, 2016. "Can Higher-Order Risks Explain the Credit Spread Puzzle?," Working Papers 16-1, HEC Montreal, Canada Research Chair in Risk Management.
    7. Guesmi, Sahar & Ben-Abdallah, Ramzi & Breton, Michèle & Dionne, Georges, 2019. "The CDS-bond Basis: Negativity Persistence and Limits to Arbitrage," Working Papers 19-4, HEC Montreal, Canada Research Chair in Risk Management.

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    More about this item

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing

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