A mathematical model for multi-name credit based on community flocking

We present a new mathematical model for multi-name credit that employs stochastic flocking. Flocking mechanisms have been used in a variety of models of biological, sociological and physical aggregation phenomena. As a direct application of a flocking mechanism, we introduce a credit risk model based on community flocking for a credit worthiness index. Correlations between different credit worthiness indices are explained in terms of communication rates and coupling strengths from the flocking system. Based on the flocking model, we compute credit curves for individual names and default time distributions. We also apply the proposed model to the pricing of credit derivatives such as credit default swaps and collateralized debt obligations.     

An intensity model for credit risk with switching Lévy processes

We develop a switching regime version of the intensity model for credit risk pricing. The default event is specified by a Poisson process whose intensity is modeled by a switching Lévy process. This model presents several interesting features. First, as Lévy processes encompass numerous jump processes, our model can duplicate the sudden jumps observed in credit spreads. Also, due to the presence of jumps, probabilities do not vanish at very short maturities, contrary to models based on Brownian dynamics. Furthermore, as the parameters of the Lévy process are modulated by a hidden Markov chain, our approach is well suited to model changes of volatility trends in credit spreads, related to modifications of unobservable economic factors.     

Pricing defaultable bonds: a middle-way approach between structural and reduced-form models

In this paper we present a valuation model that combines features of both the structural and reduced-form approaches for modelling default risk. We maintain the cause and effect or ‘structural’ definition of default and assume that default is triggered when a state variable reaches a default boundary. However, in our model, the state variable is not interpreted as the assets of the firm, but as a latent variable signalling the credit quality of the firm. Default in our model can also occur according to a doubly stochastic hazard rate. The hazard rate is a linear function of the state variable and the interest rate. We use the Cox et al. (A theory of the term structure of interest rates. Econometrica, 1985, 53(2), 385–407) term structure model to preclude the possibility of negative probabilities of default. We also horse race the proposed valuation model against structural and reduced-form default risky bond pricing models and find that term structures of credit spreads generated using the middle-way approach are more in line with empirical observations.     

The analytic pricing of asymmetric defaultable swaps

Swaps where both parties are exposed to credit risk still lack convincing pricing mechanisms. This article presents a reduced-form model where the event of default is related to structural characteristics of each party. The cash flows submitted to credit risk are identified before the swap is priced. Analytical pricing formulas for interest rate and currency swaps are computed using a Gaussian model for risky bonds. Currency swaps exhibit additional correlation risk. The benefits from netting depend on the balance between exposures and market conditions in valuation. We show that sources of credit risk asymmetries are also likely to impact on credit spreads.     

The Relevance of Accounting Data in the Measurement of Credit Risk

Abstract

Option pricing theory provides a robust and theoretically sound framework for the measurement of credit risk. Assuming perfect market conditions, information relevant to the measurement of a firm’s credit risk is reflected in its equity price, with no role for accounting data. This hypothesis is tested using UK data and credit ratings as a proxy for credit risk. It is found that Merton’s distance-to-default measure is the most significant variable in the measurement of credit risk. However, it is also found that accounting variables are incrementally informative when added to a model that contains only the distance-to-default measure. The incremental informativeness of accounting data varies across industries and depends on firm size. Although it is found that the general level of credit risk depends on the state of the economy, there is no evidence to suggest that the incremental informativeness of the accounting variables depends upon macroeconomic conditions.     

Computing the survival probability in the Madan–Unal credit risk model: application to the CDS market

We obtain a quasi-analytical approximation of the survival probability in the credit risk model proposed in [Madan, D.B. and Unal, H., Pricing the risk of default. Rev. Deriv. Res., 1998, 2(2), 121–160]. Such a formula, which extensive numerical simulations reveal to be accurate and computationally fast, can also be employed for pricing credit default swaps (CDSs). Specifically, we derive a quasi-analytical approximate expression for CDS par spreads, and we use it to estimate the parameters of the model. The results obtained show a rather satisfactory agreement between theoretical and real market data.     

An Empirical Comparison of Credit Spreads between the Bond Market and the Credit Default Swap Market

This paper compares the pricing of credit risk in the bond market and the fast-growing credit default swap (CDS) market. The cointegration test confirms that the theoretical parity relationship between the two credit spreads holds as a long-run equilibrium condition. Nevertheless, substantial deviation from the parity can arise in the short run. The panel data study and the VECM analysis both suggest that the deviation is largely due to the higher responsiveness of CDS premia to changes in credit conditions. Moreover, it exhibits a certain degree of persistence in that only 10% of price discrepancies can be removed within a business day.     

The delivery option in credit default swaps

Under standard assumptions the reduced-form credit risk model is not capable of accurately pricing the two fundamental credit risk instruments – bonds and credit default swaps (CDS) – simultaneously. Using a data set of euro-denominated corporate bonds and CDS our paper quantifies this mispricing by calibrating such a model to bond data, and subsequently using it to price CDS, resulting in model CDS spreads up to 50% lower on average than observed in the market. An extended model is presented which includes the delivery option implicit in CDS contracts emerging since a basket of bonds is deliverable in default. By using a constant recovery rate standard models assume equal recoveries for all bonds and hence zero value for the delivery option. Contradicting this common assumption, case studies of Chapter 11 filings presented in the paper show that corporate bonds do not necessarily trade at equal levels following default. Our extension models the implied expected recovery rate of the cheapest-to-deliver bond and, applied to data, largely eliminates the mispricing. Calibrated recovery values lie between 8% and 47% for different obligors, exhibiting strong variation among rating classes and industries. A cross-sectional analysis reveals that the implied recovery parameter depends on proxies for the delivery option, primarily the number of available bonds and bond pricing errors. No evidence is found for a direct influence of the bid-ask spread, notional amount, coupon, or rating used as proxies for bond market liquidity.     

A Unified Approach for Pricing Contingent Claims on Multiple Term Structures

This paper provides a unified approach for pricing contingent claims on multiple term structures using a foreign currency analogy. All existing option pricing applications are seen to be special cases of this unified approach. This approach is used to price options on financial securities subject to credit risk.     

Credit risk transfer and financial sector stability

In this paper, we study credit risk transfer (CRT) in an economy with endogenous financing (by both banks and non-bank institutions). Our analysis suggests that the incentive of banks to transfer credit risk is aligned with the regulatory objective of improving stability, and so the recent development of credit derivative instruments is to be welcomed. Moreover, we find the transfer of credit risk from banks to non-banks to be more beneficial than CRT within the banking sector. Intuitively, this is because it allows for the shedding of aggregate risk which must otherwise remain within the relatively more fragile banking sector. Therefore, regulators should act to maximize the benefits from CRT by encouraging the development of instruments favorable to the cross-sectoral transfer of aggregate credit risk (including basket credit derivatives such as collateralized debt obligations). Finally, we derive the optimal regulatory stance for banks relative to non-bank financial institutions. We show that a level playing field approach is sub-optimal. Regulatory stances should be set to actively encourage cross-sector CRT, first because of the higher fragility of the banking sector and second to induce banks to incur the costs of CRT which otherwise lead them to undertake an insufficient amount of CRT.     

A dynamic programming approach for pricing CDS and CDS options

We propose a flexible framework for pricing single-name knock-out credit derivatives. Examples include Credit Default Swaps (CDSs) and European, American and Bermudan CDS options. The default of the underlying reference entity is modelled within a doubly stochastic framework where the default intensity follows a CIR++ process. We estimate the model parameters through a combination of a cross sectional calibration-based method and a historical estimation approach. We propose a numerical procedure based on dynamic programming and a piecewise linear approximation to price American-style knock-out credit options. Our numerical investigation shows consistency, convergence and efficiency. We find that American-style CDS options can complete the credit derivatives market by allowing the investor to focus on spread movements rather than on the default event.     

Pricing credit derivatives under incomplete information: a nonlinear-filtering approach

This paper considers a general reduced-form pricing model for credit derivatives where default intensities are driven by some factor process X. The process X is not directly observable for investors in secondary markets; rather, their information set consists of the default history and of noisy price observations for traded credit products. In this context the pricing of credit derivatives leads to a challenging nonlinear-filtering problem. We provide recursive updating rules for the filter, derive a finite-dimensional filter for the case where X follows a finite-state Markov chain, and propose a novel particle-filtering algorithm. A numerical case study illustrates the properties of the proposed algorithms.     

Pricing currency risk in the stock market: Evidence from Finland and Sweden 1970-2009

We investigate the role of currency risk on stock markets in two interlinked Nordic countries exhibiting a gradual move from fixed to floating exchange rates. We apply the Ding and Engle (2001) covariance stationary specification in a multivariate GARCH-M setup to test a conditional international asset pricing model. Using a sample period from 1970 to 2009, we find that the currency risk is priced in both stock markets, and that the price and the risk premium are lower after the floatation of the currencies, especially for Finland. We also find the cross-country exchange rate shock from Finland to affect the price of currency risk in Sweden, but not vice versa. Finally, we discuss some of the potential issues in applying multivariate GARCH-M specifications in tests of asset pricing models.     

International house price cycles,monetary policy and credit

We evaluate three alternative predictors of house price corrections: anticipated tightenings of monetary policy, deviations of house prices from fundamentals, and rapid credit growth. A new cross-country measure of monetary policy expectations based on an international term structure model with time-varying risk premiums is constructed. House price overvaluation is estimated via an asset pricing model. The variables are incorporated into a panel logit regression model that estimates the likelihood of a large house price correction in 18 OECD countries. The results show that corrections are predicted by increases in the market’s forecast of higher policy rates. The estimated degree of house price overvaluation also contains significant information about subsequent price reversals. In contrast to the financial crisis literature, credit growth is less important. All of these variables help forecast recessions.     

Credit derivatives and loan pricing

This paper examines the relation between the new markets for credit default swaps (CDS) and banks’ pricing of syndicated loans to US corporates. We find that changes in CDS spreads have a significantly positive coefficient and explain about 25% of subsequent monthly changes in aggregate loan spreads during 2000–2005. Moreover, when compared to traditional explanatory factors, they turn out to be the dominant determinant of loan spreads. In particular, they explain loan rates much better than same rated bonds. This suggests that CDS prices contain, beyond general credit risk, to a substantial extent information relevant for bank lending. We also find that, over time, new information from CDS markets is faster incorporated into loans, but information from other markets is not. Overall, our results indicate that the markets for CDS have gained an important role for banks.     

金融危机前后国际信用衍生产品市场的发展及启示

信用衍生产品自问世以来在分散金融机构信用风险、完善信用风险定价机制、提高债券市场流动性等方面发挥了积极的作用。该文介绍了信用衍生产品的主要功能及其在本次金融危机前、中、后三个时期的发展特点,肯定了基础信用衍生产品对金融市场的重要作用,指出中国应推动金融创新,建立有中国特色的信用衍生产品市场。     

The market for credit default swaps: new insights into investors' use of accounting information?

The market for credit default swaps has developed into a well‐functioning, global multi‐trillion dollar market, wherein investors price and transfer corporate financial instruments on the basis of credit risk. This paper first summarizes the structure and growth of the market. Next, I introduce theory and evidence on how investors price credits risk and explain how the quality of financial statement information plays a unique role in the determination of credit spread. I then review the nascent empirical accounting literature on this topic. This review sheds light on several accounting research questions that might be understood better in the setting of the credit default swap market. The final section summarizes suggestions for future work.     

Exchange Rates and the Conversion of Currency‐Specific Risk Premia

How do the risk factors that drive asset prices influence exchange rates? Are the parameters of asset price processes relevant for specifying exchange rate processes? Most international asset pricing models focus on the analysis of asset returns given exchange rate processes. Little work has been done on the analysis of exchange rates dependent on asset returns. This paper uses an international stochastic discount factor (SDF) framework to analyse the interplay between asset prices and exchange rates. So far, this approach has only been implemented in international term structure models. We find that exchange rates serve to convert currency‐specific discount factors and currency‐specific prices of risk – a result linked to the international arbitrage pricing theory (IAPT). Our empirical investigation of exchange rates and stock markets of four countries presents evidence for the conversion of currency‐specific risk premia by exchange rates.     

How well do classical credit risk pricing models fit swap transaction data?

Currency and interest rate swaps are subject to a complex, two-sided default risk. Several theoretical papers have recently addressed the problem of pricing this swap credit risk. We implement a recent credit risk pricing model in an attempt to evaluate one of the main lines of research in theoretical credit risk analysis. We compare the model's analytical results to actual transaction data thanks to a unique academic database on swap transaction data.     

Anomalies and financial distress

This paper explores commonalities across asset pricing anomalies. In particular, we assess implications of financial distress for the profitability of anomaly-based trading strategies. Strategies based on price momentum, earnings momentum, credit risk, dispersion, idiosyncratic volatility, and capital investments derive their profitability from taking short positions in high credit risk firms that experience deteriorating credit conditions. In contrast, the value-based strategy derives most of its profitability from taking long positions in high credit risk firms that survive financial distress and subsequently realize high returns. The accruals anomaly is an exception. It is robust among high and low credit risk firms in all credit conditions.