تاثیر نوآوری مالی بر ریسک بانک های اروپایی  The effect of financial innovation on European banks’ risk

1. Introduction Recent economic theory presents two opposing views on the effects of securitization and credit derivatives on bank soundness. Some authors argue that both instruments improve financial stability, while others associate these processes with financial fragility. The securitization market could serve as a risk transfer mechanism and could therefore strengthen institutional solvency. Nevertheless, securitization potentially encourages the expansion of poorer quality credit and, therefore, impairs financial stability simultaneously. For credit derivatives in particular, although buying protection may intuitively reduce risk, the effect is not so great for intermediaries or those who sell protection. Norden, Buston, and Wagner (2011) highlight the scant evidence of the channels through which financial innovations affect financial institutions in adverse circumstances. From these two views, and given the scarcity of empirical work, the question arises as to whether the financial innovations of securitization and credit derivatives affect the risk profile of European banks. Basel III, the new capital rules, increase capital requirements for both financial innovations. In this sense, researchers must determine whether empirical analysis supports an increase in capital requirements. Additionally, risk analyses drawing from market indicators or accounting may differ, hence the need to assess the risk of financial innovation considering both measures. This work contributes to the existing literature by presenting unpublished evidence of the effect of securitization and credit derivatives on the default probability of listed European banks. Despite the importance of this issue, most existent studies focus on the US market and have a different focus in their analyses. This study uses Moody’s expected default frequency (EDF) as a continuous measure of the probability of default, and Z-score as a risk-accounting measure. Further, the database of this study uses previously unused data with a more detailed breakdown of derivative positions available in the US market. Finally, the dynamic panel data methodology permits to control for endogeneity problems.