The impact of default risk on the prices of options and other derivative securities

Hull, John C.; White, Alan

doi:10.1016/0378-4266(94)00050-d

Cited by 265 publications

(238 citation statements)

References 19 publications

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“…Thus, if there is a cyclical component built into asset valuations, then it also impacts recovery rates. Despite this, most structural models [e.g., Kim, Ramaswamy and Sundaresan (1993), Hull and White (1995), and Longstaff and Schwartz (1995)] assume that LGD is exogenously determined. An exception to this is a series of papers by Frye.…”

Section: Structural Models Of Cyclical Effects On Lgdmentioning

confidence: 99%

A Survey of Cyclical Effects in Credit Risk Measurement Models

2002

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We survey both academic and proprietary models to examine how macroeconomic and systematic risk effects are incorporated into measures of credit risk exposure. Many models consider the correlation between the probability of default (PD) and cyclical factors. Few models adjust loss rates (loss given default) to reflect cyclical effects. We find that the possibility of systematic correlation between PD and LGD is also neglected in currently available models. 3 A Survey of Cyclical Effects in Credit Risk Measurement ModelsIt has long been recognized that banking is a procyclical business. That is, banks tend to contract their lending activity when business turns down because of their concern about loan quality and repayment probability. This exacerbates the economic downturn as credit constrained businesses and individuals cut back on their real investment activity.In contrast, banks expand their lending activity during boom periods, thereby contributing to a possible overheating of the economy that may transform an economic expansion into an inflationary spiral.The proliferation of credit risk measurement models in banking may accentuate the procyclical tendencies of banking, with potential macroeconomic consequences. That is, the models' overly optimistic estimates of default risk during boom times reinforces the natural tendency of banks to overlend just at the point in the business cycle that the central bank prefers restraint. Moreover, if credit risk models are unduly pessimistic during recessions, then even the most expansionary monetary policy may not encourage banks to lend to obligors that are perceived to be poor credit risks. Recent BIS proposals to utilize credit risk models such as CreditMetrics as a basis for bank capital requirements may further accentuate the procyclical nature of banking unless the credit cycle and its effect on credit risk are appropriately recognized in the model structure. If banks are constrained by risk sensitive (as measured by internal models) capital allocations and regulatory requirements, they may be unable to lend during low points in the business cycle and overly encouraged to lend during boom periods.1 This is because risk sensitive 1 To the extent that external credit ratings provide "through the cycle" estimates of default risk smoothed across the entire business cycle, it is the internal ratings-based approaches of the New Basel Capital Accord In this paper, we examine the treatment of cyclical factors in both academic and proprietary credit risk measurement models. 4 In section 2, we begin by discussing what is meant by procyclicality. We then divide our survey of credit risk measurement models into four sections. Section 3 surveys how various credit risk measurement models incorporate cyclical effects into the estimation of default probability (PD). In Section 4, that is most likely to exacerbate the procylical tendencies of banking. However, if credit ratings behave procyclically [as shown by Ferri, Liu and Majnoni (2000), Monfort and Mulder (2000) and...

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Section: Structural Models Of Cyclical Effects On Lgdmentioning

confidence: 99%

A Survey of Cyclical Effects in Credit Risk Measurement Models

2002

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“…Second, exposures on derivatives contracts are correlated with the probabilities of default. The incorporation of default risk into the valuation of derivatives contracts was first considered by Hull and White (1995) and has since been re-examined by Collin-Dufresne and Hugonnier (2007) and others for a rather broad class of instruments.…”

Section: Literature Reviewmentioning

confidence: 99%

Margining in derivatives markets and the stability of the banking sector

Gibson

Murawski

2013

Journal of Banking & Finance

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a b s t r a c tWe investigate the effects of margining, a widely-used mechanism for attaching collateral to derivatives contracts, on derivatives trading volume, default risk, and on the welfare in the banking sector. First, we develop a stylized banking sector equilibrium model to develop some basic intuition of the effects of margining. We find that a margin requirement can be privately and socially sub-optimal. Subsequently, we extend this model into a dynamic simulation model that captures some of the essential characteristics of over-the-counter derivatives markets. Contrarily to the common belief that margining always reduces default risk, we find that there exist situations in which margining increases default risk, reduces aggregate derivatives' trading volume, and has an ambiguous effect on welfare in the banking sector. The negative effects of margining are exacerbated during periods of market stress when margin rates are high and collateral is scarce. We also find that central counterparties only lift some of the inefficiencies caused by margining.

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“…We distinguish between two cases: (i) a stochastic risk-free interest rate and (ii) a constant risk-free rate as a stochastic average (level) of a fitted distribution of observed daily 12-month LIBOR rates over an eight-year period, which have been transformed to end-of-the week quotes. We adapt the interest rate model proposed by Hull and White (1995) for logarithmic interest rates at weak level stationarity (Yule-Walker estimator). On the basis of a maximum likelihood (ML) estimation of the probability distribution for AR(1) we simulate one million paths of estimated over seven years, i.e.…”

Section: Pricing Of Clo Tranches For Risk-neutral Investorsmentioning

confidence: 99%

Asset Pricing and Investor Risk in Subordinated Asset Securitisation

Jobst

2005

SSRN Journal

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As a sign of ambivalence in the regulatory definition of capital adequacy for credit risk and the quest for more efficient refinancing sources collateral loan obligations (CLOs) have become a prominent securitisation mechanism. This paper presents a loss-based asset pricing model for the valuation of constituent tranches within a CLO-style security design. The model specifically examines how tranche subordination translates securitised credit risk into investment risk of issued tranches as beneficial interests on a designated loan pool typically underlying a CLO transaction. We obtain a tranchespecific term structure from an intensity-based simulation of defaults under both robust statistical analysis and extreme value theory (EVT). Loss sharing between issuers and investors according to a simplified subordination mechanism allows issuers to decompose securitised credit risk exposures into a collection of default sensitive debt securities with divergent risk profiles and expected investor returns. Our estimation results suggest a dichotomous effect of loss cascading, with the default term structure of the most junior tranche of CLO transactions ("first loss position") being distinctly different from that of the remaining, more senior "investor tranches". The first loss position carries large expected loss (with high investor return) and low leverage, whereas all other tranches mainly suffer from loss volatility (unexpected loss). These findings might explain why issuers retain the most junior tranche as credit enhancement to attenuate asymmetric information between issuers and investors. At the same time, the issuer discretion in the configuration of loss subordination within particular security design might give rise to implicit investment risk in senior tranches in the event of systemic shocks.

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The impact of default risk on the prices of options and other derivative securities

Cited by 265 publications

References 19 publications

A Survey of Cyclical Effects in Credit Risk Measurement Models

A Survey of Cyclical Effects in Credit Risk Measurement Models

Margining in derivatives markets and the stability of the banking sector

Asset Pricing and Investor Risk in Subordinated Asset Securitisation

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