Dynamic credit contagion and aggregate loss in networks

We develop a dynamic model to illustrate the credit risk contagion mechanism caused by interaction between firms. Specifically, we formulate the sources of risk into idiosyncratic risk and contagion risk, and introduce recovery ability to model the scenario of a firm changing from default into normal status. Our result shows that there always exists a steady state in a network under some trivial conditions. For quasi-regular networks and bipartite networks, the expected aggregate loss remains unchanged as long as the product of the contagion probability and the partner number is fixed.     

It takes more than two to tango: Multiple bank lending,asset commonality and risk

Multiple-bank lending is the most prevalent form of bank-firm credit relationships in nearly all countries. It results in high asset commonality and interconnectedness, allows idiosyncratic risks to become systemic, and makes the banking system more fragile and vulnerable to shocks. Using detailed, granular-level, supervisory data on large corporate loans, we show that multiple bank lending is driven, inter alia, by regulatory limits on large credit exposures. These limits, aimed at mitigating an individual bank's concentration risk, force firms to explore alternative sources of funding, making the common borrowers' phenomenon more prominent. We find that multiple bank lending is determined endogenously, and its likelihood increases with the level of portfolio similarity between lenders. The size of the original lender and its systemic importance magnifies this effect. We argue that banks do not internalize the systemic effect of their lending decisions and that multiple bank lending constitutes an insurance mechanism related to an implicit "too-many-to-fail" guarantee. Its externalities are suboptimal and should be reinforced with better monitoring by the related authorities.