The Basel III framework for liquidity standards and monetary policy implementation

Basel III introduces for the first time an international framework for liquidity risk regulation, reflecting the experience of excessive liquidity risk taking of banks in the run up to the financial crisis that erupted in August 2007, and associated negative externalities. As central banks play a crucial role in the liquidity provision to banks during normal times and in a financial crisis, the treatment of central bank operations in the regulation is obviously important. To ensure internalisation of liquidity risks (i.e. pricing of liquidity risk) and to address excessive reliance ex ante on central bank liquidity support by the banks, the regulation deliberately does not establish a direct close link with the monetary policy operational framework. While this reflects the purpose of the regulation and is also natural outcome of an international rule being applied under a multitude of very different monetary policy operational frameworks, this paper shows that the interaction between the two areas can be substantial, depending on the operational and collateral framework of the central bank. This implies the need for further study and the development of policies at the central bank and regulatory/supervisory side on how to handle these potential interactions in practice.Basle III, Liquidity Risk, Banking Regulation, monetary policy implementation

The Basel III framework for liquidity standards and monetary policy implementation

Basel III introduces for the first time an international framework for liquidity risk regulation, reflecting the experience of excessive liquidity risk taking of banks in the run up to the financial crisis that erupted in August 2007, and associated negative externalities. As central banks play a crucial role in the liquidity provision to banks during normal times and in a financial crisis, the treatment of central bank operations in the regulation is obviously important. To ensure internalisation of liquidity risks (i.e. pricing of liquidity risk) and to address excessive reliance ex ante on central bank liquidity support by the banks, the regulation deliberately does not establish a direct close link with the monetary policy operational framework. While this reflects the purpose of the regulation and is also natural outcome of an international rule being applied under a multitude of very different monetary policy operational frameworks, this paper shows that the interaction between the two areas can be substantial, depending on the operational and collateral framework of the central bank. This implies the need for further study and the development of policies at the central bank and regulatory/supervisory side on how to handle these potential interactions in practice

Don’t fall from the saddle: The importance of higher moments of credit loss distributions

The original Panjer recursion of the CreditRisk+ model is said to be unstable and therefore to yield inaccurate results of the tail distribution of credit portfolios. A much-hailed solution for the flaws of the Panjer recursion is the saddlepoint approximation method. In this paper we show that the saddlepoint approximation is an accurate and robust tool only for credit portfolios with low skewness and kurtosis of the loss distribution. However, often credit portfolios are heterogeneous with large skewness and kurtosis. We show that for such portfolios the commonly applied saddlepoint approximations (the Lugannani-Rice and the Barndorff-Nielsen formulas) are not reliable. We explain it by the dependence of the high-order standardized cumulants and the relative error on the saddlepoint. The more the cumulants and the relative error fluctuate for variations in the value of the saddlepoint (from 0 to the upper bound) the less accurate the saddlepoint approximation is. Hence, the saddlepoint approximations are not a universal substitute to the Panjer recursion algorithm. We also provide users of CR+ with a set of diagnostics to identify beforehand when the saddlepoint approximations are prone to failure.CreditRisk+, Saddlepoint approximations, Lugannani-Rice formula, Barndorff-Nielsen formula, Credit VaR