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Credit risk
About: Credit risk is a research topic. Over the lifetime, 18595 publications have been published within this topic receiving 382866 citations.
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TL;DR: A new simulation methodology for quantitative risk analysis of large multi-currency portfolios that discretizes the multivariate distribution of market variables into a limited number of scenarios, resulting in a high degree of computational efficiency when there are many sources of risk and numerical accuracy dictates a large Monte Carlo sample.
Abstract: This paper presents a new simulation methodology for quantitative risk analysis of large multi-currency portfolios The model discretizes the multivariate distribution of market variables into a limited number of scenarios This results in a high degree of computational efficiency when there are many sources of risk and numerical accuracy dictates a large Monte Carlo sample Both market and credit risk are incorporated The model has broad applications in financial risk management, including value at risk Numerical examples are provided to illustrate some of its practical applications
166 citations
TL;DR: In this first large-scale LGD benchmarking study, various regression techniques for modeling and predicting LGD are investigated and there is a clear trend that non-linear techniques, and in particular support vector machines and neural networks, perform significantly better than more traditional linear techniques.
166 citations
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TL;DR: In this paper, the authors present new econometric estimates for a panel of 25 emerging market countries over 1970-2001, breaking down aggregate volatility into its external and domestic policy components and find that countries with historically higher macroeconomic volatility are more prone to default, and particularly so if part of this volatility is policy-induced.
Abstract: While the relationship between volatility and credit risk is central to much of the literature on finance and banking, it has been largely neglected in empirical macro studies on sovereign defaults. This paper presents new econometric estimates for a panel of 25 emerging market countries over 1970-2001, breaking down aggregate volatility into its external and domestic policy components. We find that countries with historically higher macroeconomic volatility are more prone to default, and particularly so if part of this volatility is policy-induced. Reducing policy volatility thus appears to be key to improving a country`s credit standing.
166 citations
TL;DR: In this article, the role of risk in determining the cost efficiency of international banks in eight emerging Asian countries was investigated, and three distinct risk aspects under a total of eight risk measures: credit risk, operational risk, and market risk.
Abstract: This study investigates the role of risk in determining the cost efficiency of international banks in eight emerging Asian countries. Researchers of this paper consider three distinct risk aspects under a total of eight risk measures: credit risk, operational risk, and market risk. We apply a heteroscedastic stochastic frontier model to estimate bank cost efficiency in our analysis. Additionally, this study analyzes the marginal effects of all risk measures on the inefficiency effect in order to explore a more detailed relationship between risks and efficiency. The empirical results indicate that the risk measures represent significant effects on both the level and variability of bank efficiency. We also find that these effects vary across countries and over time.
165 citations
TL;DR: In this paper, the authors compute risk neutral probabilities or default (RNPD) using the diffusion models of Merton (1974) and Geske (1977) and show that the Geske model produces a term structure of RNPDs, and the shape of this term structure may forecast impending credit events.
Abstract: Default probabilities are important to the credit markets. Changes in default probabilities may forecast credit rating migrations to other rating levels or to default. Such rating changes can affect the firm’s cost of capital, credit spreads, bond returns, and the prices and hedge ratios of credit derivatives. While rating agencies such as Moodys and Standard & Poors compute historical default frequencies, option models can also be used to calculate forward looking or expected default frequencies. In this paper, we compute risk neutral probabilities or default (RNPD) using the diffusion models of Merton (1974) and Geske (1977). It is shown that the Geske model produces a term structure of RNPD’s, and the shape of this term structure may forecast impending credit events. Next, it is shown that these RNPD’s serve as bounds to estimates of actual default probabilities. Furthermore, the RNPD’s exhibit the same comparative statics as the estimates of actual default probabilities. Also, the risk neutral default probabilities may be more accurately estimated than actual default probabilities because they do not require an estimate of the firm’s drift. Given these similarities and advantages of RNPD’s, their estimates may possess significant information about credit events. To confirm this an event study of the relation between RNPD and rating migrations is conducted. We first show that these RNPD’s from both the Merton and Geske models do possess significant and very early information about credit rating migrations.While the sample of firms that actually default during this time period is small, changes in the shape of the term structure of default probabilities appears to detect impending migrations to default. This is shown to be consistent with an inverted term structure of default probabilities, where prior to an impending default, the short term default probability is higher than the forward default probability. Finally, since rating migrations to either lower ratings or to default can be detected months in advance these credit events may not be a surprise.
165 citations