Bankruptcy Prediction with Industry Effects

This paper investigates the forecasting accuracy of bankruptcy hazard rate models for U.S. companies over the time period 1962–1999 using both yearly and monthly observation intervals. The contribution of this paper is multiple-fold. One, using an expanded bankruptcy database we validate the superior forecasting performance of Shumway's (2001) model as opposed to Altman (1968) and Zmijewski (1984). Two, we demonstrate the importance of including industry effects in hazard rate estimation. Industry groupings are shown to significantly affect both the intercept and slope coefficients in the forecasting equations. Three, we extend the hazard rate model to apply to financial firms and monthly observation intervals. Due to data limitations, most of the existing literature employs only yearly observations. We show that bankruptcy prediction is markedly improved using monthly observation intervals. Fourth, consistent with the notion of market efficiency with respect to publicly available information, we demonstrate that accounting variables add little predictive power when market variables are already included in the bankruptcy model.     

Sovereign default risk premia: Evidence from the default swap market

This study explores the risk premia embedded in sovereign default swaps using a term structure model. The risk premia remunerate investors for unexpected changes in the default intensity. A number of interesting results emerge from the analysis. First, the risk premia contribution to spreads decreases over the sample, 2003–07, and rebounds at the start of the ‘credit crunch.’ Second, daily risk premia co-move with US macro variables and corporate default risk. Third, global factors explain most of Latin American countries' premia, and local factors best explain European and Asian premia. The importance of global factors grows over time. Finally, conditioning on lagged local and global variables at a weekly frequency, sovereign risk premia are highly predictable.     

Covered interest parity with default risk

In this paper we derive a simple model of covered interest parity (CIP) with the assumption that interbank money market rates are risky. The model assumes that the default risk of uncollateralised loans can be hedged perfectly by credit default swap contracts. We show that the no-arbitrage condition is satisfied by a band. The location of this no-arbitrage band depends on the relative riskiness of the two counterparties in the CIP trade. We present evidence on the performance of the model for developed currency pairs in 2008–2011. We find that FX swap spreads (CIP deviations calculated from interbank interest rates of two countries) either fluctuated within the no-arbitrage bands or were close to the edges of the no-arbitrage bands.     

Securitization bubbles: Structured finance with disagreement about default risk

An additional reason for the structured finance boom of the 2000s may have been disagreement about default risk of collateral assets. When risk-neutral investors disagree about average default probabilities, structuring collateral cash flow raises prices by concentrating optimists’ demand on risky tranches. With disagreement about default correlation, low-correlation investors believe in diversification and pay high prices for senior tranches they deem riskless. High-correlation investors value junior tranches they expect to pay whenever aggregate conditions are good. Risk aversion and short selling through credit default swaps reduce the prices of both pass-through and structured securitizations but may increase the return to tranching.     

Pricing inflation-indexed derivatives with default risk

Inflation-indexed derivatives with default risk are modeled using the jump-diffusion processes in the Heath–Jarrow–Morton’s (HJM) [(1992). “Bond Pricing and the Term Structure of Interest Rates: A New Methodology for Contingent Claim Valuation.” Econometrica 60: 77–105] framework. A four-factor HJM model is proposed by incorporating an exogenous intensity function into a foreign currency analogy under the three-factor HJM model proposed by Jarrow and Yildirim [(2003). “Pricing Treasury Inflation Protected Securities and Related Derivatives Using a HJM Model.” Journal of Financial and Quantitative Analysis 38: 337–358]. The proposed model improves the valuation accuracy of zero-coupon inflation-indexed swaps (IIS) through calibrating the model to swap market data. In addition, the valuation formulas of year-on-year IIS and caps with default risk are derived.     

Structural default model with mutual obligations

In this paper we consider mutual obligations in an interconnected bank system and analyze their impact on the joint and marginal survival probabilities for individual banks. We also calculate prices of the corresponding credit default swaps and first-to-default swaps. To make the role of mutual obligations more transparent, we develop a simple structural default model with banks’ assets driven by correlated multidimensional Brownian motion with drift. We calculate closed form expressions for many quantities of interest and use them for the efficient model calibration. We demonstrate that mutual obligations have noticeable impact on the system behavior.     

Pricing of swaps with default risk

In this paper, I study the valuation of interest rate and currency swaps with default risk under the contingent claim analysis framework. I demonstrate that the traditional approach of pricing swap contracts as exchanges of loans underestimates the value of such contracts to the counterparty with higher credit rating and exaggerates the credit spread required to guard against default risk. Numerical simulations show that the swap rate is not sensitive to counterparty credit rating: for a ten year interest rate swap, a one hundred basis point increase in counterparty bond yield spread results in only about one basis point increase in the swap rate. (JEL G10, G12, G13)This paper is based on Chapter 2 of my Ph.D. dissertation at Yale University. I would like to thank my dissertation committee, Kenneth French, Roger Ibbotson, and Jonathan Ingersoll, Jr. (chairman), for helpful advice and guidance. I would also like to thank Keny Back, Richard Lindsey, N. R. Prabhala, Ming Huang, Marti Subrahmanyam, three anonymous referees and especially Bob Jarrow, the editor, for helpful comments and suggestions. Any errors that remain are solely mine. This paper won the 1996 Trefftzs Award for best student paper from the Western Finance Association.     

Dealing with prognostic uncertainty

How do professional futurists contend with prognostic uncertainty? There is an impressive body of medical-sociological research on how medical staff deals with uncertainty. We have used these insights to study patterns and manners in foresight practice that might not be evident otherwise. The question “Do professional futurists use approaches to deal with uncertainty that resemble those of medical staff?” is addressed by ongoing ethnographic research in Dutch foresight practice. The observed manners are grouped into four analytic categories: the construction of solidity, numeric discourse, communication habits and experience as anchor. In this paper, the construction of solidity and experience as anchor are described in detail. It is further more suggested that “certainification” is a possible upshot of these manners in use.     

Pricing default swaps: Empirical evidence

In this paper we compare market prices of credit default swaps with model prices. We show that a simple reduced form model outperforms directly comparing bonds' credit spreads to default swap premiums. We find that the model yields unbiased premium estimates for default swaps on investment grade issuers, but only if we use swap or repo rates as proxy for default-free interest rates. This indicates that the government curve is no longer seen as the reference default-free curve. We also show that the model is relatively insensitive to the value of the assumed recovery rate.     

阿根廷的教训

阿根廷政府停止偿还债务或许将改变国际上处理类似经济崩溃事物的惯例,然而变革对于阿根廷却将为时过晚.苏珊·米勒从纽约报道为什么国际货币基金组织最终会对它的老朋友失去信心.     

Pricing credit card loans with default risks: a discrete-time approach

The main purpose of this paper is to modify the Jarrow and van Deventer model by using Das and Sundaram (Manag Sci 46:46–62, 2000) model to extend the Heath–Jarrow–Morton (J Finan Quant Anal 25:419–440, 1990) term-structure model to facilitate the consideration of default risks for pricing credit card loans. Furthermore, we derive closed-form solutions within a continuous-time framework. In addition, we also provide a numerical method for the evaluation of credit card loans within a discrete-time framework. Using the market segmentation argument to describe the characteristics of the credit card industry, our simulation results show that the shapes of the forward rate and forward spread (default risk premium) term structures play extremely important roles in determining the value of credit card loans.     

Multi-period credit default prediction with time-varying covariates

In credit default prediction models, the need to deal with time-varying covariates often arises. For instance, in the context of corporate default prediction a typical approach is to estimate a hazard model by regressing the hazard rate on time-varying covariates like balance sheet or stock market variables. If the prediction horizon covers multiple periods, this leads to the problem that the future evolution of these covariates is unknown. Consequently, some authors have proposed a framework that augments the prediction problem by covariate forecasting models. In this paper, we present simple alternatives for multi-period prediction that avoid the burden to specify and estimate a model for the covariate processes. In an application to North American public firms, we show that the proposed models deliver high out-of-sample predictive accuracy.     

“临时扣押”：应对韩国买家拖欠的利器

中国国内出口企业A公司主营石材的加工和出口业务,同韩国买家B公司有数年的贸易关系。美国的金融危机蔓延全球,韩国经济受到较大影响,B公司表示,由于资金链紧张以及韩元贬值,无力还款,同时居然要求A公司继续放账供货,A公司未同意继续供货,并在多次催讨无效后于2008年底将案件报送至中国信保应收账款管理中心,     

Multi-period corporate default prediction with stochastic covariates

We provide maximum likelihood estimators of term structures of conditional probabilities of corporate default, incorporating the dynamics of firm-specific and macroeconomic covariates. For US Industrial firms, based on over 390,000 firm-months of data spanning 1980 to 2004, the term structure of conditional future default probabilities depends on a firm's distance to default (a volatility-adjusted measure of leverage), on the firm's trailing stock return, on trailing S&P 500 returns, and on US interest rates. The out-of-sample predictive performance of the model is an improvement over that of other available models.     

From equity to default correlation with taxes

For fixed income investment, the preponderant risk is the clustering of defaults in the portfolio. Accurate prediction of such clustering depends on the knowledge of default correlation. We develop models with exogenous debt and endogenous debt to predict default correlations from equity correlations based on a self-consistent structural framework. We also examine how taxes affect the prediction of default correlations based on the two models. The empirical analysis shows that the corporate taxes tend to decrease default correlations, while personal taxes could increase or decrease default correlations. Our default correlation model with exogenous debt does a better job of predicting default correlations for high quality bonds, while the one with endogenous debt predicts more accurately for lower rated bonds. Our studies not only theoretically improve the modeling of default correlation in the structural setting but also shed new light on various aspects of default correlations and thereby help financial practitioners price credit derivatives more accurately and formulate more effective strategies to manage default risk of credit portfolios.     

Modeling default risk with support vector machines

Predicting default risk is important for firms and banks to operate successfully. There are many reasons to use nonlinear techniques for predicting bankruptcy from financial ratios. Here we propose the so-called Support Vector Machine (SVM) to predict the default risk of German firms. Our analysis is based on the Creditreform database. In all tests performed in this paper the nonlinear model classified by SVM exceeds the benchmark logit model, based on the same predictors, in terms of the performance metric, AR. The empirical evidence is in favor of the SVM for classification, especially in the linear non-separable case. The sensitivity investigation and a corresponding visualization tool reveal that the classifying ability of SVM appears to be superior over a wide range of SVM parameters. In terms of the empirical results obtained by SVM, the eight most important predictors related to bankruptcy for these German firms belong to the ratios of activity, profitability, liquidity, leverage and the percentage of incremental inventories. Some of the financial ratios selected by the SVM model are new because they have a strong nonlinear dependence on the default risk but a weak linear dependence that therefore cannot be captured by the usual linear models such as the DA and logit models.     

不良贷款迷局

追本溯源,我们在处理不良贷款的问题还是走着从前“头痛医头、脚痛医脚”的治理经济问题的老路。     

在卢森堡与会计师打交道

编者按:作者于1992年至1997年在中国银行卢森堡分行主持工作期间,与外部会计师打交道成为一项重要的工作内容.这种全新的经历经常让这位在国内银行从业三十多年的"老银行"产生特别的体会.本文是作者海外工作经历的系列文章之一.