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Enhanced LSMC for Valuation of Options
In the world of finance, whether you are a hedger or a speculator, a risk-adverse or a risk-advocate, the use of financial instruments and derivatives will remain pertinent to providing new opportunities for mitigating risks as well as generating profit. Among these instruments are Options, which re...
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AUC Knowledge Fountain
2024
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| _version_ | 1867613424372940800 |
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| access_status_str | Open Access |
| author | Mekawy, Amr |
| author_browse | Mekawy, Amr |
| author_facet | Mekawy, Amr |
| author_sort | Mekawy, Amr |
| collection | Thesis |
| description | In the world of finance, whether you are a hedger or a speculator, a risk-adverse or a risk-advocate, the use of financial instruments and derivatives will remain pertinent to providing new opportunities for mitigating risks as well as generating profit. Among these instruments are Options, which regardless of their complexity, can be an extremely versatile tool to be utilized across a wide range of different markets.
An option is a derivative that gives the holder the right, but not the obligation to buy or sell the underlying asset either before or at the maturity date of the contract. There are 2 main types of options the European option which allows the user to exercise only at the date of maturity, and the American option in which the user can exercise the option at any time before maturity.
Pricing the option has always been a major mathematical problem in Finance, and the problem is mainly due to a typical optimal stopping problem (Lin & Almeida, 2021). Especially in American option where there is there is a possibility to either exercise or to hold the option.
With the leap in technological tools and dynamic programming, different models were introduced to present the algorithms used to value the option price. |
| format | Thesis |
| id | oai:fount.aucegypt.edu:etds-3478 |
| institution | American University in Cairo (Egypt) |
| last_indexed | 2026-06-10T12:35:55.364Z |
| license_str | Not specified — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from AUC Knowledge Fountain — bepress |
| publishDate | 2024 |
| publishDateRange | 2024 |
| publishDateSort | 2024 |
| publisher | AUC Knowledge Fountain |
| publisherStr | AUC Knowledge Fountain |
| record_format | dspace |
| source_str | AUC Knowledge Fountain — bepress |
| spelling | oai:fount.aucegypt.edu:etds-3478 Enhanced LSMC for Valuation of Options Mekawy, Amr In the world of finance, whether you are a hedger or a speculator, a risk-adverse or a risk-advocate, the use of financial instruments and derivatives will remain pertinent to providing new opportunities for mitigating risks as well as generating profit. Among these instruments are Options, which regardless of their complexity, can be an extremely versatile tool to be utilized across a wide range of different markets. An option is a derivative that gives the holder the right, but not the obligation to buy or sell the underlying asset either before or at the maturity date of the contract. There are 2 main types of options the European option which allows the user to exercise only at the date of maturity, and the American option in which the user can exercise the option at any time before maturity. Pricing the option has always been a major mathematical problem in Finance, and the problem is mainly due to a typical optimal stopping problem (Lin & Almeida, 2021). Especially in American option where there is there is a possibility to either exercise or to hold the option. With the leap in technological tools and dynamic programming, different models were introduced to present the algorithms used to value the option price. 2024-12-18T08:00:00Z thesis application/pdf https://fount.aucegypt.edu/etds/2432 https://fount.aucegypt.edu/context/etds/article/3478/viewcontent/auto_convert.pdf https://fount.aucegypt.edu/context/etds/article/3478/filename/0/type/additional/viewcontent/IRB_approval_form_Amr.pdf https://fount.aucegypt.edu/context/etds/article/3478/filename/1/type/additional/viewcontent/Amr_Mekawy_Forms_20241219234421.pdf Theses and Dissertations AUC Knowledge Fountain Machine Learning Options Valuation |
| spellingShingle | Machine Learning Options Valuation Mekawy, Amr Enhanced LSMC for Valuation of Options |
| title | Enhanced LSMC for Valuation of Options |
| title_full | Enhanced LSMC for Valuation of Options |
| title_fullStr | Enhanced LSMC for Valuation of Options |
| title_full_unstemmed | Enhanced LSMC for Valuation of Options |
| title_short | Enhanced LSMC for Valuation of Options |
| title_sort | enhanced lsmc for valuation of options |
| topic | Machine Learning Options Valuation |
| url | https://fount.aucegypt.edu/etds/2432 https://fount.aucegypt.edu/context/etds/article/3478/viewcontent/auto_convert.pdf https://fount.aucegypt.edu/context/etds/article/3478/filename/0/type/additional/viewcontent/IRB_approval_form_Amr.pdf https://fount.aucegypt.edu/context/etds/article/3478/filename/1/type/additional/viewcontent/Amr_Mekawy_Forms_20241219234421.pdf |
| work_keys_str_mv | AT mekawyamr enhancedlsmcforvaluationofoptions |