The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
A Markov Model for the Term Structure of Credit Risk Spreads
Abstract
This article provides a Markov model for the term structure of credit risk spreads. The model is based on Jarrow and Turnbull (1995), with the bankruptcy process following a discrete state space Markov chain in credit ratings. The parameters of this process are easily estimated using observable data. This model is useful for pricing and hedging corporate debt with imbedded options, for pricing and hedging OTC derivatives with counterparty risk, for pricing and hedging (foreign) government bonds subject to default risk (e.g., municipal bonds), for pricing and hedging credit derivatives, and for risk management.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
The pricing of options and corporate liabilities
Black, F., & Scholes, M. (1973) · Journal of Political Economy · doi:10.1086/260062 · Cited by 29,074
The Theory of Stochastic Processes
Cox, D. R., Miller, H. D., Weiss, G., & Shuler, K. (1966) · Physics Today · doi:10.1063/1.3047872 · Cited by 3,324
Cited by
Prospect Theory and Asset Prices
Barberis, N., Huang, M., & Santos, T. (2001) · The Quarterly Journal of Economics · doi:10.1162/003355301556310 · Cited by 1,895
On cox processes and credit risky securities
Lando, D. (1998) · Review of Derivatives Research · doi:10.1007/bf01531332 · Cited by 1,208
Self-citationArbitrage Theory in Continuous Time
Björk, T. (2004) · doi:10.1093/0199271267.001.0001 · Cited by 940
Metadata
- Authors
- Jarrow, R. A., Lando, D., & Turnbull, S. M.
- Venue
- Review of Financial Studies
- Publisher
- Oxford University Press (OUP)
- Published
- 1997-04
- Volume
- 10
- Issue
- 2
- Pages
- 481-523
- ISSN
- 0893-9454 (ISSN-L)
- 1465-7368
- OpenAlex
- W3023478198
- Cited by
- 1,475
- References
- 2
- FWCI
- 67.00
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: A Markov Model for the Term Structure of Credit Risk Spreads. https://app.cochat.ai/papers/10.1093/rfs/10.2.481
- The paper
- Jarrow, R. A., Lando, D., & Turnbull, S. M. (1997). A Markov Model for the Term Structure of Credit Risk Spreads. Review of Financial Studies. https://doi.org/10.1093/rfs/10.2.481
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
