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How to calibrate Gaussian two-factor model using swaption

We propose an efficient approximation of the swaption normal volatility to estimate the mean reversion separately from the other volatility parameters in the Gaussian two-factor model. We compare our two-step approach with a one-step method that calibrates all parameters simultaneously. The comparis...

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Detalles Bibliográficos
Autores principales: Choi, Myeongsu, Kang, Hyoung-Goo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9949672/
https://www.ncbi.nlm.nih.gov/pubmed/36821632
http://dx.doi.org/10.1371/journal.pone.0280829
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author Choi, Myeongsu
Kang, Hyoung-Goo
author_facet Choi, Myeongsu
Kang, Hyoung-Goo
author_sort Choi, Myeongsu
collection PubMed
description We propose an efficient approximation of the swaption normal volatility to estimate the mean reversion separately from the other volatility parameters in the Gaussian two-factor model. We compare our two-step approach with a one-step method that calibrates all parameters simultaneously. The comparison is based on the data from interest rate market of Korea and the US. The parameter estimates of our proposed two-step method are more stable than those of the one-step method in that the latter is overly sensitive to market changes whereas the former is not. The proposed approach also eliminates many existing problems in the Gaussian two-factor model.
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spelling pubmed-99496722023-02-24 How to calibrate Gaussian two-factor model using swaption Choi, Myeongsu Kang, Hyoung-Goo PLoS One Research Article We propose an efficient approximation of the swaption normal volatility to estimate the mean reversion separately from the other volatility parameters in the Gaussian two-factor model. We compare our two-step approach with a one-step method that calibrates all parameters simultaneously. The comparison is based on the data from interest rate market of Korea and the US. The parameter estimates of our proposed two-step method are more stable than those of the one-step method in that the latter is overly sensitive to market changes whereas the former is not. The proposed approach also eliminates many existing problems in the Gaussian two-factor model. Public Library of Science 2023-02-23 /pmc/articles/PMC9949672/ /pubmed/36821632 http://dx.doi.org/10.1371/journal.pone.0280829 Text en © 2023 Choi, Kang https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Choi, Myeongsu
Kang, Hyoung-Goo
How to calibrate Gaussian two-factor model using swaption
title How to calibrate Gaussian two-factor model using swaption
title_full How to calibrate Gaussian two-factor model using swaption
title_fullStr How to calibrate Gaussian two-factor model using swaption
title_full_unstemmed How to calibrate Gaussian two-factor model using swaption
title_short How to calibrate Gaussian two-factor model using swaption
title_sort how to calibrate gaussian two-factor model using swaption
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9949672/
https://www.ncbi.nlm.nih.gov/pubmed/36821632
http://dx.doi.org/10.1371/journal.pone.0280829
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