Credit Spreads

This is where we learn how to stop the bleeding from our credit spread going from bad to WORSE. Here, we talk about how we can stop from taking a full loss on a credit spread going against you, using different hedging techniques to turn this trade around.

This work empirically examines six structural models of the term structure of credit risk spreads: Merton (1974), Longstaff & Schwartz (1995) (with and without stochastic interest rates), Leland & Toft (1996), Collin-Dufresne & Goldstein (2001), and a constant elasticity of variance model. The conventional approach to testing structural models has involved the use of observable data to proxy the latent capital structure process, which may introduce additional specification error. This study extends Jones, Mason & Rosenfeld (1983) and Eom, Helwege & Huang (2004) by using implicit estimation of key model parameters resulting in an improved level of model fit. Unlike prior studies, the models are fitted from the observed dynamic term structure of firm-specific credit spreads, thereby providing a pure test of model specification. The models are implemented by adapting the method of Duffee (1999) to structural credit models, thereby treating the capital structure process is truly latent,...

This paper models the default probabilities and credit spreads for select Indian firms in the Black-Scholes-Merton framework. Counter to previous research, we show that the objective (or 'real') probability estimates are higher than the risk-neutral estimates over the sample period. However, the probability measure is found to be robust to the 'default trigger point'. The model output also compares favorably with the default rate reported by CRISIL's Average 1-year rating transitions as well as the Altman Z-score measure.

This paper models the default probabilities and credit spreads for select Indian firms in the Black-Scholes-Merton framework. Counter to previous research, we show that the objective (or 'real') probability estimates are higher than the risk-neutral estimates over the sample period. However, the probability measure is found to be robust to the 'default trigger point'. The model output also compares favorably with the default rate reported by CRISIL's Average 1-year rating transitions as well as the Altman Z-score measure.

This Working Paper should not be reported as representing the views of the IMF. The views expressed in this Working Paper are those of the author(s) and do not necessarily represent those of the IMF or IMF policy. Working Papers describe research in progress by the author(s) and are published to elicit comments and to further debate. We identify global and regional fluctuations in international private debt flows to emerging and developing countries using data on cross border loans and international bond issuance over 1993-2009. We estimate the effects of individual borrower characteristics as well as macroeconomic conditions on the cost of foreign borrowing and test whether these effects differ across phases of the lending cycle. We find that public and financial institutions benefit from lower spreads compared to private and nonfinancial firms and that lenders may differentiate the risk associated with the borrower's industrial sector between good and bad times. The loan (bond) rating has an equally robust spread reduction effect across credit cycle phases. The results also suggest that international reserve holdings and investment ratios have a significant effect on reducing credit spreads for loans, while higher reserve holdings and longer maturities matter more for bond spreads.

We explore whether governments may have faced scenarios of self-fulfilling prophecy and multiple equilibria during Europe’s sovereign debt crisis. To this end, we estimate the effect of interest rates and other macroeconomic variables on sovereign debt ratings, and of ratings on interest rates. We detect a nonlinear effect of ratings on interest rates which is strong enough to permit multiple equilibria. The good equilibrium is stable, ratings are excellent and interest rates are low. A second unstable equilibrium marks a threshold beyond which the country slides towards an insolvency trap. Coefficient estimates suggest that countries should stay well within the A segment of the rating scale in order to remain safe from being driven towards default.

In order to stabilise financial markets, central banks around the world have implemented monetary policies aiming at boosting their country’s economy by lowering interest rates. It is fundamental for policymakers to understand financial markets’ reaction ‘to the release of monetary policy decisions’ (Andersson, 2007) as it reveals how market participants anticipate those decisions and how they ‘adjust their views about future monetary policy’ and important macroeconomic factors (Andersson, 2007).
The purpose of this report is to assess how monetary policy implemented by the Federal Reserve Bank impacts credit spreads for debt denominated in US dollars –issued in the US- and in Euro – the euro domestic or eurobond markets.
Our main findings are twofold. First, we demonstrate that all credit spreads are not equivalent when it comes to receptivity of monetary policy announcements. Indeed, very safe bonds (observed through the TED spread) seem to react to shocks to short term interest rates, while high yield securities appear to be more responsive to changes in long term treasury yields. Secondly, we demonstrate that although the Federal Reserve has undertaken a combination of very low short-term interest rates and large-scale asset purchases, it did not have any significant impact on the credit spreads for low rated bonds that are only responsive to movements in the treasury yields.

The field of credit risk and corporate bankruptcy prediction has gained considerable momentum following the collapse of many large corporations around the world, and more recently through the sub-prime scandal in the United States. This book provides a thorough compendium of the different modelling approaches available in the field, including several new techniques that extend the horizons of future research and practice. Topics covered include probit models (in particular bivariate probit modelling), advanced logistic regression models (in particular mixed logit, nested logit and latent class models), survival analysis models, non-parametric techniques (particularly neural networks and recursive partitioning models), structural models and reduced form (intensity) modelling. Models and techniques are illustrated with empirical examples and are accompanied by a careful explanation of model derivation issues. This practical and empirically based approach makes the book an ideal resource for all those concerned with credit risk and corporate bankruptcy, including academics, practitioners and regulators.

I show that a congruent, parsimonious, encompassing model discovered using David Hendry’s LSE approach to econometric modelling with Autometrics can overcome the many inadequacies of the typical static models of US Treasury return behavior and macroeconomic announcements that tend to fail most, if not all, specification tests. Further, such modelling techniques are able to expand our knowledge of time varying risk premia and asymmetric news responses in financial markets that were previously studied within a GARCH framework that offered little or no evidence as to the precise sources of the asymmetries. Asymmetric effects are shown to be concentrated in a handful of announcements, such as the Employment Cost Index and Core PPI. Results suggest a place for general-to-specific modelling in financial economics, a place where it has only recently begun to be employed. These results underscore the contributions of David F. Hendry and his collaborators in econometric modelling and demonstrate the need for better models in finance that may be alleviated by employing modelling practices advocated by econometricians doing research in the LSE/Oxford tradition.

Changes in sovereign debt ratings and outlooks affect financial markets in emerging economies. They affect not only the instrument being rated (bonds) but also stocks. They directly impact the markets of the countries rated and generate cross country contagion. The effects of rating and outlook changes are stronger during crises, in nontransparent economies, and in neighboring countries. Upgrades tend to take place during market rallies, whereas downgrades occur during downturns, providing support to the idea that credit rating agencies contribute to the instability in emerging financial markets.

This paper proposes a model for pricing credit derivatives in a defaultable HJM framework. The model features hump-shaped, level dependent, and unspanned stochastic volatility, and accommodates a correlation structure between the stochastic volatility, the default-free interest rates, and the credit spreads. The model is finite-dimensional, and leads (a) to exponentially affine default-free and defaultable bond prices, and (b) to an approximation for pricing credit default swaps and swaptions in terms of defaultable bond prices with varying maturities. A * Corresponding author. 1 numerical study demonstrates that the model captures stylized various features of credit default swaps and swaptions.

This is not the first international banking crisis the world has seen. The previous ones occurred without credit default swaps, special investment vehicles, or even credit ratings. If crises keep repeating themselves, it seems reasonable to argue that policy makers need to carefully consider what they are doing and not just "double up" by superficially reacting to the specific features of today's crisis. While we cannot hope to prevent crises, we can perhaps make them fewer and milder by adopting and implementing better regulation-in particular, more macro-prudential regulation.

Credit Rating Agencies (CRAs) report information about the credit risk of fixed income securities. The various ways the information is used by financial, legal and regulatory entities may potentially influence the nature of the information production process. Bond ratings are not only used to assess risk, they are also used for regulatory certification, e.g. to classify securities into investment grade (IG) and high yield (HY, or junk) status. These classifications in turn influence institutional demand and serve as bright-line triggers in corporate credit arrangements and regulatory oversight. Regulations may mandate insurance companies and banks to keep much higher reserve capital for high yield issues than for investment grade corporate bonds. Other institutions like pension funds and mutual funds are often restricted by their charters in the amount of HY debt they can hold. Taken together, more than half of all corporate bonds are held by institutions that are subject to rating-based restrictions on their holdings of risky credit assets (Campbell and Taksler (2003)). Lower demand for high yield bond can significantly increase the cost of borrowing for those issuers and is related to capital structure decisions (see Ellul, Jotikasthira and Lundblad (2009), Kisgen and Strahan (2009), Kisgen (2006, 2009)). The institutional and regulatory importance of credit ratings to issuers and investors has raised questions about whether the current system provides the proper incentives for issuers to fully disclose value-relevant information, and for investors to invest in research about credit risk. Using a sample from 2000-2008, we document that almost all large, liquid US corporate bond issues are rated by both S&P and Moody's. Fitch typically plays the role of a "third opinion" for large bond issues 1. During the time period the most prevalent institutional rule used for classifying rated bonds was that, if an issue has two ratings, only the lower rating could be used to classify the issue (e.g. into investment-grade or non-investment grade). However, for issues with three ratings, the middle rating should be used (see, for example, the NAIC guidelines or the Basel II accord). 2 Therefore, if S&P and Moody's ratings are on opposite sides of the investment grade boundary, the Fitch rating (assuming it is the marginal, third rating) is the 'tie-breaker' and will decide into which class the issue falls. Moreover, this rule directly implies that adding a third rating cannot worsen the regulatory rating classification, but could potentially lead to a higher one. Consistent with this option, we find that in about 25% of Fitch rating additions, the addition leads to a regulatory rating improvement, i.e., the resulting middle rating is higher than the lowest rating before the Fitch rating addition. Ex ante, such an improvement would be particularly important when S&P and Moody's ratings are on opposite sides of the investment grade boundary. Absent the improving third rating, the split between S&P and Moody's would result in a classification of high yield. Thus, the value of the Fitch rating is that

The payoff of many credit derivatives is subject to spread risk, i.e., it depends on the evolution of credit spreads through time. To motivate our analysis we consider the leveraged credit-linked note, which is par-ticularly sensitive to jumps in credit spreads. In the framework of first-passage time models we define a credit quality process with stochastic volatility. Using a representation of the credit quality process as a time-changed Brownian motion, we derive a formula for the dynamics of default probabilities, which in turn provides the dynamics of credit spreads. As an example for a volatility process we consider the square root of a Lévy-driven Ornstein-Uhlenbeck process and we show that jumps in the volatility translate into jumps in credit spreads. We show that the dynamics can be computed efficiently, and we demonstrate that the

This paper investigates the determinants of the iTraxx CDS Europe indices, finding strong evidence that they are regime dependent. During volatile periods credit spreads become highly sensitive to stock volatility and more sensitive to this than to stock returns. They are also almost immune to interest rates changes. During tranquil periods credit spreads are more sensitive to stock returns than to volatility and most indices are sensitive to interest rate moves. However for companies in the financial sector interest rates have no significant influence in either regime. We also found some evidence that raising interest rates can decrease the probability of credit spreads entering a volatile period. Our findings are useful for policy makers and, since equity hedge ratios based on single-state models cannot capture the regime dependent behaviour of credit spreads, our results may also help traders to improve the efficiency of hedging credit default swaps. Finally, the volatility clustering and autocorrelation that we have identified in the price dynamics of iTraxx indices should prove useful for pricing the iTraxx options that are now being actively traded over-the-counter.

The paper analyzes a barrier exchange option that is knocked out the first time the two underlying assets have identical market values. Under rather general conditions regarding the price processes for the underlying assets, probably the world's simplest option pricing formula is derived. It applies both to options of American and European type and has implications for credit spreads and for static hedging of barrier options.

Currency risk is one of the two components of the total interest rate differential. Hard pegs, such as currency boards, are meant to reduce or even eliminate currency risk, thus, reducing domestic interest rates. This paper investigates the patterns and determinants of the currency risk premium in two currency boards-Argentina and Hong Kong. Despite the presumed rigidity of currency boards, the currency premium is almost always positive and at times very large. Its term structure is usually upward sloping, but flattens out or even becomes inverted at times of turbulence. The premium and its term structure depend on domestic and global factors related to devaluation expectations and risk perceptions. D

Recent literature has documented a link between institutional equity ownership (IO) and cost of debt capital, and interpreted it as a corporate governance effect. However, institutional equity investors may also affect cost of debt through their influence on information asymmetry condition of firms. To distinguish between the two effects, we break down institutional investors into different groups: transient institutional investors (T RA) who are sensitive to information asymmetry but unlikely to participate in corporate governance, and the dedicated ones (DED)who act oppositely. Based on a most up-to-date and comprehensive bond data spanning the past 20 years, we find that credit spreads narrow (widen) with an increase in equity ownership by T RA (DED). The effects are most prominent among short-term bonds, bonds with lower ratings, higher leverage and higher volatilities. The results persist after controlling for potential endogeneity and other information asymmetry measures, and are unlikely due to an asset substitution effect. Overall, our findings provide strong support for the effect of information asymmetry on credit spread, and highlight the importance of distinguishing various types of institutional investors.

Recent literature has documented a link between institutional equity ownership (IO) and cost of debt capital, and interpreted it as a corporate governance effect. However, institutional equity investors may also affect cost of debt through their influence on information asymmetry condition of firms. To distinguish between the two effects, we break down institutional investors into different groups: transient institutional investors (T RA) who are sensitive to information asymmetry but unlikely to participate in corporate governance, and the dedicated ones (DED)who act oppositely. Based on a most up-to-date and comprehensive bond data spanning the past 20 years, we find that credit spreads narrow (widen) with an increase in equity ownership by T RA (DED). The effects are most prominent among short-term bonds, bonds with lower ratings, higher leverage and higher volatilities. The results persist after controlling for potential endogeneity and other information asymmetry measures, and are unlikely due to an asset substitution effect. Overall, our findings provide strong support for the effect of information asymmetry on credit spread, and highlight the importance of distinguishing various types of institutional investors.

ABSTRACT Gibson’s et al. (2013) provide evidence that credit ratings have exerted an independent influence on credit (sovereign) spreads for Greece beyond that implied by economic fundamentals. Based on the Markov Regime-switching model of Hamilton (1989), we show that this happens during the recent financial crisis regime, characterized by a higher mean and volatility of credit spreads. It is also true for Ireland and Portugal, also bailed out by their EU partners and IMF. We show that, for Greece and Portugal, the shift of credit spreads to their higher mean-volatility regime occurred before the collapse of Lehman brothers, thus discounting a higher price of sovereign credit risk for these two countries. In contrast to Ireland, this regime shift has not been triggered by a rating downgrades for Greece and Portugal. In this higher volatility regime, credit ratings seem to significantly influence future changes in credit spreads independently of economic fundamentals, for Greece and Portugal. For Ireland, they constitute the main factor of determining credit spreads.

This paper uses credit spread data on Japanese bond indices to examine the possibility of a change in the determinants of daily credit spreads after the outbreak of the global financial crisis of 2007. A set of variables identified by prior research are used in a GARCH setting to explain credit spread changes both before and after the start of the crisis. The findings indicate that, overall, the coefficient estimates of the two bond market factors, namely changes in the spot rate and changes in the slope of the treasury yield curve, are consistent with prior literature. Moreover, the direction of the relationship is the same during the two periods. On the other hand, the relationship between credit spread changes and the two stock market factors, namely stock market index returns and changes in the implied index option volatility, is weak and sensitive to the period examined. Finally, the liquidity factor has a weak impact in both periods. It is also notable that the explanatory pow...

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Abstract: Russia had more-or-less completed the privatization of its manufacturing and natural resource sectors by the end of 1997. And in February 1998, the annual inflation rate at last dipped into the single digits. Privatization should have helped with stronger micro-...

This work empirically examines six structural models of the term structure of credit risk spreads: Merton (1974), Longstaff & Schwartz (1995) (with and without stochastic interest rates), Leland & Toft (1996), Collin-Dufresne & Goldstein (2001), and a constant elasticity of variance model. The conventional approach to testing structural models has involved the use of observable data to proxy the latent capital structure process, which may introduce additional specification error. This study extends Jones, Mason & Rosenfeld (1983) and Eom, Helwege & Huang (2004) by using implicit estimation of key model parameters resulting in an improved level of model fit. Unlike prior studies, the models are fitted from the observed dynamic term structure of firm-specific credit spreads, thereby providing a pure test of model specification. The models are implemented by adapting the method of Duffee (1999) to structural credit models, thereby treating the capital structure process is truly latent,...

The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent.

Wood and seminar participants at the Bank of England and Banco de España for useful comments. Karen Goff and Andrew Paterson provided very able research assistance. CreditTrade and J.P. Morgan Securities kindly allowed us to use their credit default swap data. Numerous people at Banc of America Securities, Bloomberg, BNP Paribas, CreditTrade, Deutsche Bank and J.P. Morgan answered our questions and corrected our misunderstandings. They know who they are and that we are very grateful. BANCO DE ESPAÑA SERVICIO DE ESTUDIOS The Working Paper Series seeks to disseminate original research in economics and finance. All papers have been anonymously refereed. By publishing these papers, the Banco de España aims to contribute to economic analysis and, in particular, to knowledge of the Spanish economy and its international environment. The opinions and analyses in the Working Paper Series are the responsibility of the authors and, therefore, do not necessarily coincide with those of the Banco de España or the Eurosystem. The Banco de España disseminates its main reports and most of its publications via the INTERNET at the following website: http://www.bde.es Reproduction for educational and non-commercial purposes is permitted provided that the source is acknowledged

This paper analyses the role of liquidity in the price discovery process. Specifically, we focus on the credit derivatives markets in the context of the subprime crisis. We present a theoretical price discovery model for the asset swap packages (ASPs), bond and credit default swap (CDS) markets and then we test the model with data from 2005 to 2009 on

Although the general risk taxonomy and definitions have been refined over the years, market risk can be broadly defined as the risk of financial loss due to movements in market prices such as interest rates, foreign exchange (currency) rates, equity prices, credit spreads and commodity prices that can adversely affect banks’ on- and off-balance sheet positions.
Interest rate risk (IRR) is a form of market risk that is especially relevant to various on- and off-balance sheet items whose cash flows are sensitive to interest rates (eg loans, bonds, deposits, interest rate derivatives). IRR can be analysed as a gap risk (arising from timing differences in maturity or repricing among a bank’s positions), basis risk (arising due to different interest rate indices, eg Libor, Euribor or some future risk free rates) and option risk (related to option derivative positions or embedded options). Furthermore, foreign exchange (FX) risk arises from currency fluctuations, equity risk is the risk of losses due to the adverse changes in equity prices, credit spread risk is driven by the changes in the credit quality of a debtor or counterparty, while commodity risk depends on the movements in commodity prices (eg grains, metals or oil). 
For this purpose, the market risk scope will be aligned with the definition used for minimum regulatory capital requirements, which is underpinned by the delineation between banking and trading book. From the European Banking Authority’s (EBA) perspective, ‘market risk stems from all the positions included in banks' trading book as well as from commodity...

This paper investigates the nature of the credit risk premium adjustments in the Jarrow-Lando-Turnbull model of credit risk spreads. The adjustments relate the equivalent martingale measures to the empirical measures of unconditional transition probabilities. We provide a modified version of the risk adjustment that allows a linear partition of the credit spread into an unconditional default component, a recovery component, and the risk premium adjustment. The risk adjustments are related to conditional default risk, illiquidity risk, and other factors not related to recovery effects. The log-transform of these risk adjustments can be specified as linear regressions on a set of macroeconomic variables. Some new insights are gained pertaining to these conditional risks such as a typical upward sloping term structure and sensitivity to short-term Treasury rates and increasing forward rates. The conditional risks appear to be insensitive to market returns.

This paper investigates the nature of the credit risk premium adjust-ments in the Jarrow-Lando-Turnbull model of credit risk spreads. The adjustments relate the equivalent martingale measures to the empirical measures of unconditional transition probabilities. We provide ...

The risk neutral credit migration process captures quantitative information which is relevant to the pricing theory and risk management of credit derivatives. In this article, we derive implied migration rates by means of a recently introduced credit barrier model which is calibrated on the basis of aggregate information such as credit migration rates and credit spread curves. The model is characterized by an underlying stochastic process that represents credit quality and default events are associated to barrier crossings. The stochastic process has state dependent volatility and jumps which are estimated by using empirical migration and default rates. A risk-neutralizing drift and forward liquidity spreads are estimated to consistently match the average spread curves corresponding to all the various ratings. The implied migration rates obtained with our credit barrier model are then compared with those obtained via the Jarrow-Lando-Turnbull model by the Kijima-Komoribayashi model in a detailed example.

This is not the first international banking crisis the world has seen. The previous ones occurred without credit default swaps, special investment vehicles, or even credit ratings. If crises keep repeating themselves, it seems reasonable to argue that policy makers need to carefully consider what they are doing and not just "double up" by superficially reacting to the specific features of today's crisis. While we cannot hope to prevent crises, we can perhaps make them fewer and milder by adopting and implementing better regulation-in particular, more macro-prudential regulation.

The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent.

Credit Rating Agencies (CRAs) report information about the credit risk of fixed income securities. The various ways the information is used by financial, legal and regulatory entities may potentially influence the nature of the information production process. Bond ratings are not only used to assess risk, they are also used for regulatory certification, e.g. to classify securities into investment grade (IG) and high yield (HY, or junk) status. These classifications in turn influence institutional demand and serve as bright-line triggers in corporate credit arrangements and regulatory oversight. Regulations may mandate insurance companies and banks to keep much higher reserve capital for high yield issues than for investment grade corporate bonds. Other institutions like pension funds and mutual funds are often restricted by their charters in the amount of HY debt they can hold. Taken together, more than half of all corporate bonds are held by institutions that are subject to rating-based restrictions on their holdings of risky credit assets (Campbell and Taksler (2003)). Lower demand for high yield bond can significantly increase the cost of borrowing for those issuers and is related to capital structure decisions (see Ellul, Jotikasthira and Lundblad (2009), Kisgen and Strahan (2009), Kisgen (2006, 2009)). The institutional and regulatory importance of credit ratings to issuers and investors has raised questions about whether the current system provides the proper incentives for issuers to fully disclose value-relevant information, and for investors to invest in research about credit risk. Using a sample from 2000-2008, we document that almost all large, liquid US corporate bond issues are rated by both S&P and Moody's. Fitch typically plays the role of a "third opinion" for large bond issues 1. During the time period the most prevalent institutional rule used for classifying rated bonds was that, if an issue has two ratings, only the lower rating could be used to classify the issue (e.g. into investment-grade or non-investment grade). However, for issues with three ratings, the middle rating should be used (see, for example, the NAIC guidelines or the Basel II accord). 2 Therefore, if S&P and Moody's ratings are on opposite sides of the investment grade boundary, the Fitch rating (assuming it is the marginal, third rating) is the 'tie-breaker' and will decide into which class the issue falls. Moreover, this rule directly implies that adding a third rating cannot worsen the regulatory rating classification, but could potentially lead to a higher one. Consistent with this option, we find that in about 25% of Fitch rating additions, the addition leads to a regulatory rating improvement, i.e., the resulting middle rating is higher than the lowest rating before the Fitch rating addition. Ex ante, such an improvement would be particularly important when S&P and Moody's ratings are on opposite sides of the investment grade boundary. Absent the improving third rating, the split between S&P and Moody's would result in a classification of high yield. Thus, the value of the Fitch rating is that

This paper provides a new methodology for estimating the term structure of corporate debt using a semiparametric penalized spline model. The method is applied to a case study of AT&T bonds. Typically, very little data is available on individual corporate bond prices, too little to find a nonparametric estimate of term structure from these bonds alone. This problem is solved by "borrowing strength" from Treasury bond data. More specifically, we combine a nonparametric model for the term structure of Treasury bonds with a parametric component for the credit spread. Our methodology generalizes the work of Fisher, Nychka, and Zervos (1995) in several ways. First, their model was developed for only Treasury bonds and cannot be applied directly to corporate bonds. Second, we more fully investigate the problem of choosing the smoothing parameter, a problem that is complicated because the forward rate is the derivative − log{D(t)}, where the discount function D is the function fit to the data. In our case study estimation of the derivative requires substantially more smoothing than selected by generalized cross-validation (GCV). Another problem for smoothing parameter selection is possible correlations of the errors. We compare three methods of choosing the penalty parameter: linearized GCV, the residual spatial autocorrelation (RSA) method of Ellner and Seifu (2002), and a modification of Ruppert's (1997) EBBS. Third, we provide approximate sampling distributions based on both large-sample and small-noise asymptotics. The latter are novel and are motivated by the application to corporate bond prices where the sample sizes are small but the noise is very low. Confidence bands and tests of interesting hypotheses, e.g., about the functional form of the spreads, are also discussed.

We study the consistency of the credit-risk orderings implicit in ratings and bond market yields. By analyzing errors in term structure estimates for bonds with particular ratings, we show that for significant periods, a quarter of some categories of high credit quality bonds are rated in a manner that is inconsistent with their pricing. Adjusting for economic determinants of spreads (tax, liquidity and risk premiums) and allowing for the dynamic adjustment of ratings and spreads largely eliminates the inconsistencies, however.

We use economic indicators to improve the prediction of the number of incurred but not recorded disability insurance claims, assuming that there is a link between the number of claims and the chosen economic indicators. We propose a Bayesian model where we model the claims development in three directions: along incurred periods, recording lag periods and calendar periods. A stochastic model of the economic indicators is incorporated into the calendar period development direction. Thus we allow for the impact of the economic environment on the number of claims. Applying the proposed model to data, we illustrate how the inclusion of economic indicators affects the prediction of the number of incurred but not recorded disability claims.

In most circumstances such relation is verified in practice, as different financial assets tend to move in the same direction at similar speed. However, occasional deviations from the theoretical fair values occur, especially in times of financial turmoil. Understanding how the dynamics of the theoretical fair values of various assets compares to that of their market values is crucial to a number of market participants. This paper investigates whether a popular structural model, the CreditGrades approach proposed by Finger (2002), , succeeds in explaining the dynamic relation between equity/option variables and Credit Default Swap (CDS) premia at individual company level. We find that CDS model spreads display a significant correlation with CDS market spreads. However, the gap between the two is time varying and widens substantially in times of financial turbulence. The analysis of the gap dynamics reveals that this is partly due to episodes of decoupling between equity and credit markets, and partly due to shortcomings of the model. Finally, we observe that model spreads tend to predict market spreads.

Relative price effects arise from the fact that the standard ratio implicitly compares nominal output and outstanding financial holdings. Thus, for example, an equity market boom raises the equity FG-to-GDP ratio regardless of changes in portfolio composition. To the extent that cross-border debt liabilities are denominated in hard currency, the same applies to debt FG ratios in the event of a real depreciation.