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The Use of Mortgage Covered Bonds
The rapid mortgage credit growth experienced in recent years in mature and emerging countries has raised some stability concerns. Many European credit institutions in mature markets have reacted by increasing securitization, particularly via mortgage covered bonds. From the issuer's perspective, these instruments have become an attractive funding source and a tool for assetliability management; from the investor's perspective, covered bonds enjoy a favorable risk-return profile and a very liquid market. In this paper, we examine the two largest "jumbo" covered bond markets, Germany and Spain. We show how movements in covered bond prices can be used to analyze the credit developments of the underlying issuer and the quality of its mortgage portfolio. Our analysis also suggests that mortgage covered bonds could be of interest to other mature and emerging markets facing similar risks related to mortgage credit.
Numerical Methods in Finance
Numerical Methods in Finance describes a wide variety of numerical methods used in financial analysis.
A New Risk Indicator and Stress Testing Tool: A Multifactor Nth-to-Default CDS Basket
This paper generalizes a market-based indicator for financial sector surveillance using a multifactor latent structure in the determination of the default probabilities of an nth-todefault credit default swap (CDS) basket of large complex financial institutions (LCFIs). To estimate the multifactor latent structure, we link the market risk (the covariance of the LCFIs' equity) to credit risk (the default probability of the CDS basket) in a coherent manner. In addition, to analyze the response of the probabilities of default to changing macroeconomic conditions, we run a stress test by generating shocks to the latent multifactor structure. The results unveil a rich set of default probability dynamics and help in identifying the most relevant sources of risk. We anticipate that this approach could be of value to financial supervisors and risk managers alike.
FIRST
This paper presents background work that has been the basis for the development of the market and credit risk indicators (MRI and CRI, respectively) as published in the IMF's Global Financial Stability Report (GFSR) since September 2004. The fundamental idea was to build a set of Financial Indicators on Risk and Stability (FIRST) that could reflect the market perceptions for current and future stress on financial institutions. The focus of the analysis is mainly on large, complex financial institutions (LCFIs) operating in the most advanced financial markets, MRI and CRI have also been applied to internationally active commercial banks and insurance companies.
Nonlinear Econometric Modeling in Time Series
This book presents some of the more recent developments in nonlinear time series, including Bayesian analysis and cointegration tests.
Review and Implementation of Credit Risk Models of the Financial Sector Assessment Program (FSAP)
The paper presents the basic Credit Risk+ model, and proposes some modifications. This model could be useful in the stress-testing financial sector assessments process as a benchmark for credit risk evaluations. First, we present the setting and basic definitions common to all the model specifications used in this paper. Then, we proceed from the simplest model based on Bernoulli-distributed default events and known default probabilities to the fully-fledged Credit Risk+ implementation. The latter is based on the Poisson approximation and uncertain default probabilities determined by mutually independent risk factors. As an extension we present a Credit Risk+ specification with correlated risk factors as in Giese (2003). Finally, we illustrate the characteristics and the results obtained from the different models using a specific portfolio of obligors.
