Tail Dependence of Eurozone Bond Yields and Sovereign CDS Spreads

Veni Arakelian, Roberto Savona and Marika Vezzoli

Chapter 7 in Artificial Intelligence and Beyond for Finance, 2024, pp 265-287 from World Scientific Publishing Co. Pte. Ltd.

Abstract: Using machine learning techniques, we detect clusters with high tail dependence obtained through a flexible threshold copula model applied pairwise to the Eurozone sovereign bond yields and credit default swap spreads. Our approach is also useful to inspect the evolution of the loss distribution, as we prove by computing a theoretical portfolio based on Clayton and Gumbel copulas for the highest values of the association parameters estimated by the model.

Keywords: Artificial Intelligence; Machine Learning; Deep Learning; Reinforcement Learning; Sentiment Analysis; Portfolio Management; Financial Forecasting (search for similar items in EconPapers)
JEL-codes: C63 C8 G11 G17 (search for similar items in EconPapers)
Date: 2024
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