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Default Probabilities (default + probability)

Distribution by Scientific Domains
Business, Economics, Finance and Accounting77%

Selected Abstracts

Pricing Loans Using Default Probabilities

ECONOMIC NOTES, Issue 2 2003
Stuart M. Turnbull
This paper examines the pricing of loans using the term structure of the probability of default over the life of the loan. We describe two methodologies for pricing loans. The first methodology uses the term structure of credit spreads to price a loan, after adjusting for the difference in recovery rates between bonds and loans. In loan origination, it is common practice to estimate the probability of default for a loan over a specified time horizon and the loss given default. The second methodology shows how to incorporate this information into the arbitrage free pricing of a loan. We also show how to derive an estimate of the credit spread due to liquidity risk. For both methodologies, we show how to calculate a break,even credit spread, taking into account the fee structure of a loan and the costs associated with the term structure of marginal economic capital. The break,even spread is the minimum spread for the loan to be EVA neutral in a multi,period setting. (J.E.L.: G12, G33). [source]

Financial Frictions and Risky Corporate Debt

ECONOMIC NOTES, Issue 1 2007
Doriana Ruffino
We offer clarifications on Cooley and Quadrini (2001) regarding financial frictions and risky corporate debt pricing. Even in a frictionless world, the promised rate on corporate debt is not identical across firms and across capital structures and it is not equal to the risk-free rate. Frictions are unnecessary for credit spreads to arise. Only if the macroeconomy is in actuality risk free or risk neutral do interest rates on corporate debt reflect default probabilities. To the extent that the firm's entire financial structure is traded, a bias in credit spreads introduces an exploitable arbitrage opportunity. Re-establishing no-arbitrage, firm dynamics move in the opposite direction to Cooley and Quadrini's. [source]

The Risk-Adjusted Cost of Financial Distress

THE JOURNAL OF FINANCE, Issue 6 2007
HEITOR ALMEIDA
ABSTRACT Financial distress is more likely to happen in bad times. The present value of distress costs therefore depends on risk premia. We estimate this value using risk-adjusted default probabilities derived from corporate bond spreads. For a BBB-rated firm, our benchmark calculations show that the NPV of distress is 4.5% of predistress value. In contrast, a valuation that ignores risk premia generates an NPV of 1.4%. We show that marginal distress costs can be as large as the marginal tax benefits of debt derived by Graham (2000). Thus, distress risk premia can help explain why firms appear to use debt conservatively. [source]

Economic determinants of default risks and their impacts on credit derivative pricing,

THE JOURNAL OF FUTURES MARKETS, Issue 11 2010
Szu-Lang Liao
This study constructs a credit derivative pricing model using economic fundamentals to evaluate CDX indices and quantify the relationship between credit conditions and the economic environment. Instead of selecting specific economic variables, numerous economic and financial variables have been condensed into a few explanatory factors to summarize the noisy economic system. The impacts on default intensity processes are then examined based on no-arbitrage pricing constraints. The approximated results show that economic factors indicated credit problems even before the recent subprime mortgage crisis, and economic fundamentals strongly influenced credit conditions. Testing of out-of-sample data shows that credit evolution can be identified by dynamic explanatory factors. Consequently, the factor-based pricing model can either facilitate the evaluation of default probabilities or manage default risks more effectively by quantifying the relationship between economic environment and credit conditions. © 2010 Wiley Periodicals, Inc. Jrl Fut Mark [source]

Modeling dependencies between rating categories and their effects on prediction in a credit risk portfolio

APPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY, Issue 3 2008
Claudia Czado
Abstract The internal-rating-based Basel II approach increases the need for the development of more realistic default probability models. In this paper, we follow the approach taken in McNeil A and Wendin J 7 (J. Empirical Finance 2007) by constructing generalized linear mixed models for estimating default probabilities from annual data on companies with different credit ratings. The models considered, in contrast to McNeil A and Wendin J 7 (J. Empirical Finance 2007), allow parsimonious parametric models to capture simultaneously dependencies of the default probabilities on time and credit ratings. Macro-economic variables can also be included. Estimation of all model parameters are facilitated with a Bayesian approach using Markov chain Monte Carlo methods. Special emphasis is given to the investigation of predictive capabilities of the models considered. In particular, predictable model specifications are used. The empirical study using default data from Standard and Poor's gives evidence that the correlation between credit ratings further apart decreases and is higher than the one induced by the autoregressive time dynamics. Copyright © 2008 John Wiley & Sons, Ltd. [source]

Bank Mergers, Information, Default and the Price of Credit

ECONOMIC NOTES, Issue 1 2006
Margarida Catalão- Lopes
This paper addresses the impact of bank mergers on the price of firm credit, through an information channel. It is shown that, as bank mergers imply a wider spreading of information among banks concerning firms' past defaults, they may increase the expected revenue from lending. Therefore, interest rates may decline as long as a sufficiently competitive environment is preserved. A fall in interest rates, in turn, reduces the incentives for firms to strategically default, which reinforces the downward effect on the price of credit. The results are a function of the level of information sharing and of the sensitivity of the default probability to the interest rate. [source]

Credit Risk Models , Do They Deliver Their Promises?

ECONOMIC NOTES, Issue 2 2003
A Quantitative Assessment
We develop a framework to assess the statistical significance of expected default frequency calculated by credit risk models. This framework is then used to analyse the quality of two commercially available models that have become popular among practitioners: KMV Credit Monitor and RiskCalc from Moody's. Using a unique database of expected default probability from both vendors, we study both the consistency of the prediction and its timeliness. We introduce the concept of cumulative accuracy profile (CAP) that allows to see in one curve the percentage of defaulting companies captured by the models one year in advance. We also use the Miller's information test to see if the models add information to the S&P rating. The result of the analysis indicates that these models indeed add relevant information not accounted for by rating alone. Moreover, with respect to rating agencies, the models predict defaults more than ten months in advance on average. (J.E.L.: C52). [source]

Residual income, non-earnings information, and information content

JOURNAL OF FORECASTING, Issue 6 2009
Ruey S. Tsay
Abstract We extend Ohlson's (1995) model and examine the relationship between returns and residual income that incorporate analysts' earnings forecasts and other non-earnings information variables in the balance sheet, namely default probability and agency cost of a debt covenant contract. We further divide the sample based on bankruptcy (agency) costs, earnings components and growth opportunities of a firm to explore how these factors affect the returns,residual income link. We find that the relative predictive ability for contemporaneous stock price by considering other earnings and non-earnings information is better than that of models without non-earnings information. If the bankruptcy (agency) cost of a firm is higher, its information role in the firm's equity valuation becomes more important and the accuracy of price prediction is therefore higher. As for non-earnings information, if bankruptcy (agency) cost is lower, the information role becomes more relevant, and the earnings response coefficient is hence higher. Moreover, the decomposition of unexpected residual income into permanent and transitory components induces more information than that of the unexpected residual income alone. The permanent component has a larger impact than the transitory component in explaining abnormal returns. The market and industry properties and growth opportunity also have incremental explanatory power in valuation. Copyright © 2008 John Wiley & Sons, Ltd. [source]