Evaluating Credit Counterparty Risk of American Options via Monte Carlo Methods: A Comparison of Tilley Bundling and Longstaff-Schwartz LSM
Monte Carlo methods have become a staple use in risk departments of many financial institutions as these methods are relatively fast to compute even at higher dimensions and provide risk metrics such as percentile values. Two classical methods used for derivatives with early exercise features are th...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2019-12-01
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| Series: | Frontiers in Applied Mathematics and Statistics |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/article/10.3389/fams.2019.00060/full |
| _version_ | 1818959029561458688 |
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| author | Dominic Cortis |
| author_facet | Dominic Cortis |
| author_sort | Dominic Cortis |
| collection | DOAJ |
| description | Monte Carlo methods have become a staple use in risk departments of many financial institutions as these methods are relatively fast to compute even at higher dimensions and provide risk metrics such as percentile values. Two classical methods used for derivatives with early exercise features are the Longstaff Schwartz Least-Squares method and Tilley bundling. This paper explains clearly the steps involved in evaluating the value of an American option and how these can be extended to evaluate risk metrics. While best estimate values are known to be fairly similar, discrepancies in risk pricing are noticed. |
| first_indexed | 2024-12-20T11:35:09Z |
| format | Article |
| id | doaj.art-ce50197e2782450d863d8adf79842cd2 |
| institution | Directory Open Access Journal |
| issn | 2297-4687 |
| language | English |
| last_indexed | 2024-12-20T11:35:09Z |
| publishDate | 2019-12-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Applied Mathematics and Statistics |
| spelling | doaj.art-ce50197e2782450d863d8adf79842cd22022-12-21T19:42:08ZengFrontiers Media S.A.Frontiers in Applied Mathematics and Statistics2297-46872019-12-01510.3389/fams.2019.00060499687Evaluating Credit Counterparty Risk of American Options via Monte Carlo Methods: A Comparison of Tilley Bundling and Longstaff-Schwartz LSMDominic CortisMonte Carlo methods have become a staple use in risk departments of many financial institutions as these methods are relatively fast to compute even at higher dimensions and provide risk metrics such as percentile values. Two classical methods used for derivatives with early exercise features are the Longstaff Schwartz Least-Squares method and Tilley bundling. This paper explains clearly the steps involved in evaluating the value of an American option and how these can be extended to evaluate risk metrics. While best estimate values are known to be fairly similar, discrepancies in risk pricing are noticed.https://www.frontiersin.org/article/10.3389/fams.2019.00060/fullAmerican optionscredit counterparty riskexpected potential exposureMonte Carlo methodspotential future exposureTilley bundling |
| spellingShingle | Dominic Cortis Evaluating Credit Counterparty Risk of American Options via Monte Carlo Methods: A Comparison of Tilley Bundling and Longstaff-Schwartz LSM Frontiers in Applied Mathematics and Statistics American options credit counterparty risk expected potential exposure Monte Carlo methods potential future exposure Tilley bundling |
| title | Evaluating Credit Counterparty Risk of American Options via Monte Carlo Methods: A Comparison of Tilley Bundling and Longstaff-Schwartz LSM |
| title_full | Evaluating Credit Counterparty Risk of American Options via Monte Carlo Methods: A Comparison of Tilley Bundling and Longstaff-Schwartz LSM |
| title_fullStr | Evaluating Credit Counterparty Risk of American Options via Monte Carlo Methods: A Comparison of Tilley Bundling and Longstaff-Schwartz LSM |
| title_full_unstemmed | Evaluating Credit Counterparty Risk of American Options via Monte Carlo Methods: A Comparison of Tilley Bundling and Longstaff-Schwartz LSM |
| title_short | Evaluating Credit Counterparty Risk of American Options via Monte Carlo Methods: A Comparison of Tilley Bundling and Longstaff-Schwartz LSM |
| title_sort | evaluating credit counterparty risk of american options via monte carlo methods a comparison of tilley bundling and longstaff schwartz lsm |
| topic | American options credit counterparty risk expected potential exposure Monte Carlo methods potential future exposure Tilley bundling |
| url | https://www.frontiersin.org/article/10.3389/fams.2019.00060/full |
| work_keys_str_mv | AT dominiccortis evaluatingcreditcounterpartyriskofamericanoptionsviamontecarlomethodsacomparisonoftilleybundlingandlongstaffschwartzlsm |