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

被引:2
作者
Balduzzi, Pierluigi [1 ]
Savona, Roberto [2 ]
Alessi, Lucia [3 ]
机构
[1] Boston Coll, Newton, MA USA
[2] Univ Brescia, Dept Econ & Management, Brescia, Italy
[3] European Commiss, Joint Res Ctr, Ispra, Italy
关键词
CDS spreads; LASSO; macroeconomic fundamentals; POST-SELECTION INFERENCE; MONETARY-POLICY; RISK; NEWS; BANK; REGULARIZATION; REGRESSION; SPARSITY; MARKETS; RETURN;
D O I
10.1093/jjfinec/nbac021
中图分类号
F8 [财政、金融];
学科分类号
0202 ;
摘要
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.
引用
收藏
页码:1728 / 1758
页数:31
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