Credit Spreads, Rating Downgrades, and Downside Performance: A Market-Informed Approach to Monitoring Credit Risk

We present a novel empirical benchmark for analyzing credit risk using “pseudo firms” that purchase traded assets financed with equity and zero-coupon bonds. By no-arbitrage, pseudo bonds are equivalent to Treasuries minus put options on pseudo firm assets. Empirically, like corporate spreads, pseudo bond spreads are large, countercyclical, and predict lower economic growth. Using this framework, we find that bond market illiquidity, investors' overestimation of default risks, and corporate frictions do not seem to explain excessive observed credit spreads but, instead, a risk premium for tail and idiosyncratic asset risks is the primary determinant of corporate spreads. (JEL E23, E32, E44, G13, G24, G32)

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From default probabilities to credit spreads: Credit risk models do explain market prices

Finance Research Letters ◽

10.1016/j.frl.2006.01.004 ◽

2006 ◽

Vol 3 (2) ◽

pp. 79-95 ◽

Cited By ~ 9

Author(s):

Stefan M. Denzler ◽

Michel M. Dacorogna ◽

Ulrich A. Müller ◽

Alexander J. McNeil

Keyword(s):

Credit Risk ◽

Credit Spreads ◽

Risk Models ◽

Market Prices

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A primer on counterparty valuation adjustments in South Africa

South African Journal of Economic and Management Sciences ◽

10.4102/sajems.v17i5.648 ◽

2014 ◽

Vol 17 (5) ◽

pp. 584-600

Author(s):

Gary Wayne Van Vuuren ◽

Ja'nel Esterhuysen

Keyword(s):

South Africa ◽

Financial Crisis ◽

Credit Risk ◽

South African ◽

Credit Spreads ◽

Basel Iii ◽

Credit Quality ◽

Counterparty Credit Risk ◽

Market Variables

Counterparty valuation adjustment (CVA) risk accounts for losses due to the deterioration in credit quality of derivative counterparties with large credit spreads. Of the losses attributed to counterparty credit risk incurred during the financial crisis of 2008-9 were due to CVA risk; the remaining third were due to actual defaults. Regulatory authorities have acknowledged and included this risk in the new Basel III rules. The capital implications of CVA risk in the South African milieu are explored, as well as the sensitivity of CVA risk components to market variables. Proposed methodologies for calculating changes in CVA are found to be unstable and unreliable at high average spread levels.

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EFFECT OF ASSET VALUE CORRELATION ON CREDIT-LINKED NOTE VALUES

International Journal of Theoretical and Applied Finance ◽

10.1142/s0219024902001535 ◽

2002 ◽

Vol 05 (05) ◽

pp. 455-478 ◽

Cited By ~ 5

Author(s):

C. H. HUI ◽

C. F. LO

Keyword(s):

Interest Rate ◽

Credit Risk ◽

Structural Model ◽

Credit Spreads ◽

Model Parameters ◽

Risk Premiums ◽

Closed Form Solutions ◽

Asset Values ◽

Dependent Model ◽

Payoff Condition

This paper develops a simple model to study the credit risk premiums of credit-linked notes using the structural model. Closed-form solutions of credit risk premiums of the credit-linked notes derived from the model as functions of firm values and the short-term interest rate, with time-dependent model parameters governing the dynamics of the firm values and interest rate. The numerical results show that the credit spreads of a credit-linked note increase non-linearly with the decrease in the correlation between the asset values of the note issuer and the reference obligor when the final payoff condition depends on the asset values of the note issuer and the reference obligor. When the final payoff condition depends on the recovery rate of the note issuer upon default, the credit spreads could increase with the correlation. In addition, the term structures of model parameters and the correlations involving interest rate are clearly the important factors in determining the credit spreads of the notes.

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CREDIT RISK AND INCOMPLETE INFORMATION: FILTERING AND EM PARAMETER ESTIMATION

International Journal of Theoretical and Applied Finance ◽

10.1142/s0219024910005966 ◽

2010 ◽

Vol 13 (05) ◽

pp. 683-715 ◽

Cited By ~ 6

Author(s):

CLAUDIO FONTANA ◽

WOLFGANG J. RUNGGALDIER

Keyword(s):

Parameter Estimation ◽

Credit Risk ◽

Financial Market ◽

Risk Model ◽

Information Filtering ◽

Credit Spreads ◽

Reduced Form ◽

Contagion Effect ◽

Credit Risk Model ◽

Filtering Approach

We consider a reduced-form credit risk model where default intensities and interest rate are functions of a not fully observable Markovian factor process, thereby introducing an information-driven default contagion effect among defaults of different issuers. We determine arbitrage-free prices of OTC products coherently with information from the financial market, in particular yields and credit spreads and this can be accomplished via a filtering approach coupled with an EM-algorithm for parameter estimation.

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Credit Spreads, Recovery Rates and Bond Portfolio Risk Measures in a Hybrid Credit Risk Model

SSRN Electronic Journal ◽

10.2139/ssrn.2130851 ◽

2012 ◽

Author(s):

Genevieve Gauthier ◽

Mathieu Boudreault ◽

Tommy Thomassin

Keyword(s):

Credit Risk ◽

Risk Model ◽

Risk Measures ◽

Credit Spreads ◽

Portfolio Risk ◽

Recovery Rates ◽

Bond Portfolio ◽

Credit Risk Model

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The impact of market sectors and rating agencies on credit ratings: global evidence

The Journal of Risk Finance ◽

10.1108/jrf-09-2017-0145 ◽

2019 ◽

Vol 20 (5) ◽

pp. 389-410

Author(s):

Kerstin Lopatta ◽

Magdalena Tchikov ◽

Finn Marten Körner

Keyword(s):

Credit Risk ◽

Credit Rating ◽

Credit Ratings ◽

Content Type ◽

Rating Agencies ◽

Credit Rating Agency ◽

Rating Agency ◽

Investment Grade ◽

The Impact ◽

Rating Downgrades

Purpose A credit rating, as a single indicator on one consistent scale, is designed as an objective and comparable measure within a credit rating agency (CRA). While research focuses mainly on the comparability of ratings between agencies, this paper additionally questions empirically how CRAs meet their promise of providing a consistent assessment of credit risk for issuers within and between market segments of the same agency. Design/methodology/approach Exhaustive and robust regression analyses are run to assess the impact of market sectors and rating agencies on credit ratings. The examinations consider the rating level, as well as rating downgrades as a further measure of empirical credit risk. Data stems from a large global sample of Bloomberg ratings from 11 market sectors for the period 2010-2018. Findings The analyses show differing effects of sectors and agencies on issuer ratings and downgrade probabilities. Empirical results on credit ratings and rating downgrades can then be attributed to investment grade and non-investment grade ratings. Originality/value The paper contributes to current finance research and practice by examining the credit rating differences between sectors and agencies and providing assistance to investors and other stakeholders, as well as researchers, how issuers’ sector and rating agency affiliations act as relative metrics.

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