Abstract:
The increasing integration of financial markets has caused heightened connections among countries. In the aftermaths of the financial crisis the European Union has recognised the importance of containing systemic risk not only at the micro level but also at the macro level to contain the propagation of financial instability in the intertwined international network.
This paper analyses the interconnections among major European countries (Germany, France, Italy, UK, Spain, Portugal, Netherlands, Belgium, and Finland) through the investigation of Credit Default Swaps data denominated in US dollar, downloaded from the Bloomberg platform. The period under investigation ranges from 2009 to June 2020
The method adopted for the analysis is the vectorized autoregressive model used to predict multiple timeseries. The resulting forecast error decomposition is transformed into measures of connectedness that characterize the state of the network in a static framework, by adopting the full sample, and in a dynamic overview, achieved by analysing the forecast error variance in a rolling window applied all through the time series (Diebold & Yilmaz).
The results of the analysis revealed that connectedness measures are useful indicators of the relevant factors that affect the system and they capture dynamically the underlying changes in the network, giving a concise feedback of the risk interlinkages among countries as they evolve in time. Measures of connectedness are not limited to the observation of past events, such as the escalation of the sovereign crisis in the period between 2009 and 2012, but they may also be used to pin down relevant events and their direct effects on the network connections as they occur through a quantitative lens.
