A simple nonparametric approach to pricing credit default swaps

This study introduces a nonparametric approach to pricing credit default swaps (CDSs) and other single-name credit-risky securities. This method is notable for its simplicity, estimation speed, and flexibility. That is, it relies exclusively on closed-form solutions, which provide instantaneous resu...

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Author: Forte, Santiago
Format: Article
Publication date:2025
Country:España
Institution:Universitat Ramon Llull (URL)
Repository:DAU Arxiu Digital de la Universitat Ramon Llull
OAI Identifier:oai:dau.url.edu:20.500.14342/6011
Online Access:https://hdl.handle.net/20.500.14342/6011
https://doi.org/10.1016/j.jedc.2025.105198
Access Level:Open access
Keyword:Credit risk pricing
No-arbitrage conditions
Bootstrapping
CDS contracts
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author Forte, Santiago
author_browse Forte, Santiago
author_facet Forte, Santiago
author_role author
collection DAU Arxiu Digital de la Universitat Ramon Llull
description This study introduces a nonparametric approach to pricing credit default swaps (CDSs) and other single-name credit-risky securities. This method is notable for its simplicity, estimation speed, and flexibility. That is, it relies exclusively on closed-form solutions, which provide instantaneous results, and allows the user to reproduce any term structure of CDS spreads. I empirically assess its pricing performance by comparing it with an otherwise equivalent semiparametric (piecewise constant default probability) model that requires a series of root-search algorithms and represents the current market convention for marking-to-market CDS contracts. This analysis demonstrates that the new method also implies a reduction in mean percentage absolute pricing errors.
eu_rights_str_mv openAccess
format article
id ES_ee95faa5ce7790cb8f00a6f1f1732d6d
institution Universitat Ramon Llull (URL)
instname_str Universitat Ramon Llull (URL)
network_acronym_str ES
network_name_str España
oai_identifier_str oai:dau.url.edu:20.500.14342/6011
publishDate 2025
publishDateSort 2025
publisher Elsevier B.V.
publisherStr Elsevier B.V.
reponame_str DAU Arxiu Digital de la Universitat Ramon Llull
spelling A simple nonparametric approach to pricing credit default swaps Forte, Santiago Credit risk pricing No-arbitrage conditions Bootstrapping CDS contracts This study introduces a nonparametric approach to pricing credit default swaps (CDSs) and other single-name credit-risky securities. This method is notable for its simplicity, estimation speed, and flexibility. That is, it relies exclusively on closed-form solutions, which provide instantaneous results, and allows the user to reproduce any term structure of CDS spreads. I empirically assess its pricing performance by comparing it with an otherwise equivalent semiparametric (piecewise constant default probability) model that requires a series of root-search algorithms and represents the current market convention for marking-to-market CDS contracts. This analysis demonstrates that the new method also implies a reduction in mean percentage absolute pricing errors. info:eu-repo/semantics/publishedVersion Elsevier B.V. https://hdl.handle.net/20.500.14342/6011 https://doi.org/10.1016/j.jedc.2025.105198
spellingShingle A simple nonparametric approach to pricing credit default swaps
Forte, Santiago
Credit risk pricing
No-arbitrage conditions
Bootstrapping
CDS contracts
title A simple nonparametric approach to pricing credit default swaps
title_full A simple nonparametric approach to pricing credit default swaps
title_fullStr A simple nonparametric approach to pricing credit default swaps
title_full_unstemmed A simple nonparametric approach to pricing credit default swaps
title_short A simple nonparametric approach to pricing credit default swaps
title_sort A simple nonparametric approach to pricing credit default swaps
topic Credit risk pricing
No-arbitrage conditions
Bootstrapping
CDS contracts
topic_facet Credit risk pricing
No-arbitrage conditions
Bootstrapping
CDS contracts
url https://hdl.handle.net/20.500.14342/6011
https://doi.org/10.1016/j.jedc.2025.105198