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Anatomy of a Sovereign Debt Crisis: Machine Learning, Real-Time Macro Fundamentals, and CDS Spreads

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Listed:
  • Pierluigi Balduzzi
  • Roberto Savona
  • Lucia Alessi

Abstract

We employ a Least Absolute Shrinkage and Selection Operator (LASSO)-based extension of the Fama–MacBeth procedure to characterize the time-varying dependence of sovereign Credit Default Swap (CDS) spreads on macro indicators during the samples 2009–2013 and 2013–2020. While CDS spreads are mainly reflective of fundamentals, this relationship varies substantially over time, leading to price variation that appears unrelated to fundamentals. The estimated LASSO coefficients are used to endogenously identify macro-sensitivity “regimes” of variation, consistently with a multiple-equilibrium view of the sovereign debt markets.

Suggested Citation

  • Pierluigi Balduzzi & Roberto Savona & Lucia Alessi, 2023. "Anatomy of a Sovereign Debt Crisis: Machine Learning, Real-Time Macro Fundamentals, and CDS Spreads," Journal of Financial Econometrics, Oxford University Press, vol. 21(5), pages 1728-1758.
    • Handle: RePEc:oup:jfinec:v:21:y:2023:i:5:p:1728-1758.
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    File URL: http://hdl.handle.net/10.1093/jjfinec/nbac021
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    More about this item

    Keywords

    CDS spreads; LASSO; macroeconomic fundamentals;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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