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Banks increasingly recognize the need to measure and manage the credit risk of their loans on a portfolio basis. We address the subportfolio "middle market". Due to their specific lending policy for this market segment it is an important task for banks to systematically identify regional and industrial credit concentrations and reduce the detected concentrations through diversification. In recent years, the development of markets for credit securitization and credit derivatives has provided new credit risk management tools. However, in the addressed market segment adverse selection and moral hazard problems are quite severe. A potential successful application of credit securitization and credit derivatives for managing credit risk of middle market commercial loan portfolios depends on the development of incentive-compatible structures which solve or at least mitigate the adverse selection and moral hazard problems. In this paper we identify a number of general requirements and describe two possible solution concepts.
The paper analyses the effects of three sets of accounting rules for financial instruments - Old IAS before IAS 39 became effective, Current IAS or US GAAP, and the Full Fair Value (FFV) model proposed by the Joint Working Group (JWG) - on the financial statements of banks. We develop a simulation model that captures the essential characteristics of a modern universal bank with investment banking and commercial banking activities. We run simulations for different strategies (fully hedged, partially hedged) using historical data from periods with rising and falling interest rates. We show that under Old IAS a fully hedged bank can portray its zero economic earnings in its financial statements. As Old IAS offer much discretion, this bank may also present income that is either positive or negative. We further show that because of the restrictive hedge accounting rules, banks cannot adequately portray their best practice risk management activities under Current IAS or US GAAP. We demonstrate that - contrary to assertions from the banking industry - mandatory FFV accounting adequately reflects the economics of banking activities. Our detailed analysis identifies, in addition, several critical issues of the accounting models that have not been covered in previous literature. December 2002. Revised: June 2003. Later version: http://publikationen.ub.uni-frankfurt.de/volltexte/2005/1026/ with the title: "Accounting for financial instruments in the banking industry : conclusions from a simulation model"
Accounting for financial instruments in the banking industry: conclusions from a simulation model
(2003)
The paper analyses the effects of three sets of accounting rules for financial instruments - Old IAS before IAS 39 became effective, Current IAS or US GAAP, and the Full Fair Value (FFV) model proposed by the Joint Working Group (JWG) - on the financial statements of banks. We develop a simulation model that captures the essential characteristics of a modern universal bank with investment banking and commercial banking activities. We run simulations for different strategies (fully hedged, partially hedged) using historical data from periods with rising and falling interest rates. We show that under Old IAS a fully hedged bank can portray its zero economic earnings in its financial statements. As Old IAS offer much discretion, this bank may also present income that is either positive or negative. We further show that because of the restrictive hedge accounting rules, banks cannot adequately portray their best practice risk management activities under Current IAS or US GAAP. We demonstrate that - contrary to assertions from the banking industry - mandatory FFV accounting adequately reflects the economics of banking activities. Our detailed analysis identifies, in addition, several critical issues of the accounting models that have not been covered in previous literature.
We take a simple time-series approach to modeling and forecasting daily average temperature in U.S. cities, and we inquire systematically as to whether it may prove useful from the vantage point of participants in the weather derivatives market. The answer is, perhaps surprisingly, yes. Time-series modeling reveals conditional mean dynamics, and crucially, strong conditional variance dynamics, in daily average temperature, and it reveals sharp differences between the distribution of temperature and the distribution of temperature surprises. As we argue, it also holds promise for producing the long-horizon predictive densities crucial for pricing weather derivatives, so that additional inquiry into time-series weather forecasting methods will likely prove useful in weather derivatives contexts.
This paper analyzes the empirical relationship between credit default swap, bond and stock markets during the period 2000-2002. Focusing on the intertemporal comovement, we examine weekly and daily lead-lag relationships in a vector autoregressive model and the adjustment between markets caused by cointegration. First, we find that stock returns lead CDS and bond spread changes. Second, CDS spread changes Granger cause bond spread changes for a higher number of firms than vice versa. Third, the CDS market is significantly more sensitive to the stock market than the bond market and the magnitude of this sensitivity increases when credit quality becomes worse. Finally, the CDS market plays a more important role for price discovery than the corporate bond market. JEL Klassifikation: G10, G14, C32.