The recent financial crisis offered an interesting opportunity to analyze the markets’ behavior in a high-volatility framework. In this paper, we analyzed the price discovery process of the Italian banks’ Credit Default Swap (CDS) spreads through the Merton model, extended with the inclusion of a redenomination risk proxy, as to say, the risk that Italy could leave the eurozone. This paper contributes to the literature by integrating the classic Merton model with a political-sensitive market variable able to explain the greatest variance in the Italian banks’ CDS spreads during the most relevant and commonly recognized periods of socio-political and financial distress. Results show that the redenomination risk is progressively becoming the main driver of the process during crises, in particular for the sovereign debt crisis and in 2018.

Hedging and speculative strategies play a key role in periods of financial market volatility particularly during economic crises. In such contexts, liquidity problems tend to evolve into potential credit risk events that amplifies the volatility of several markets such as the CDS and the government bond markets. The former, however, generally embodies a higher sensitivity to volatility due to the operators’ uncertainty about unstable and countercyclical counterparty risk. The aim of this paper is to analyze the long-lasting dynamic relationship between credit default swap (CDS) premia and government bond yield spreads (GBS), by focusing particularly on sovereign credit risk, in order to evaluate the lead-lag markets in the price discovery process against the backdrop of a deep financial crisis. The focus of this study concerns the country of Italy, one of the major European countries that suffers from both weak GDP growth and high public debt, which subjects it to volatility and speculation during periods of financial stress. JEL classification numbers: G01, G12, G14, G20. Keywords: CDS spreads, Government bond spreads, Credit risk, Cointegration, Vector error correction model, Granger-causality.

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