Abstract
We propose a comprehensive approach for the analysis of real economy and government sector risk transmission to the banking system and apply it in ten Euro-Area countries from 2005 to 2017. A flexible methodology is developed to model banks’ assets according to the risk-adjusted balance sheet of the counterparts. The use of distance to distress as a popular risk metric shows that Contingent Claims Analysis underestimates banks risk in stable periods and overstates it during crisis. Furthermore, the approach succeeds in detecting spillovers from households, non-financial corporations and sovereign sectors: for the countries examined the main source of instability comes from the Non-Financial Corporation sector and its increased assets volatility.
Highlights
The 2008 financial crisis, together with the subsequent sovereign debt crisis, showed the key role of banks in the world’s economy and the relevance of sector interconnections in risk transmission
The analysis focuses on the three main borrower sectors highlighted previously: government (GVT), non-financial corporations (NFC) and households (HH)
The second reason is that since for the banks we are rejecting the usual log-normal hypothesis on the assets returns, we depart from the full Merton practice. This implies that if we were using the Standard Normal distribution to map the DtD to probability of default/distress (PD), we would have biased results for the credit institutions sector
Summary
The 2008 financial crisis, together with the subsequent sovereign debt crisis, showed the key role of banks in the world’s economy and the relevance of sector interconnections in risk transmission. In this paper we present a new comprehensive approach for measuring banking sector risks This methodology exploits the results from previous works on sectors’ risk analysis and combines them with the scope of becoming a useful tool to predict credit institution’s vulnerability. This approach uses Contingent Claims Analysis (CCA) to infer the market value of banks’ assets, accounting for the banks’ portfolio structure mainly composed by credits to other sectors. This evaluation leads to the calculation of banks’ risk indicators according to credit institution liabilities. The methodology does not apply CCA on the banking balance sheet because it rejects the common assumption that the bank assets follow a log-normal distribution
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