Maximum likelihood estimation with dynamic measurement errors and application to interest rate modeling
Stochastic volatility (SV) model is widely applied in the extension of the constant volatility in Black-Scholes option pricing.In this paper, we extend the SV model driven by fractional Brownian motion (FBM). A crucial problem in its application is how the unknown parameters in the model are to be e...
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| Format: | Article |
| Language: | English |
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Academic Publications, Ltd.
2016
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| Online Access: | https://repo.uum.edu.my/id/eprint/21562/1/IJPAM%20110%203%202016%20433%20446.pdf |
| _version_ | 1825804582900465664 |
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| author | Misiran, Masnita |
| author_facet | Misiran, Masnita |
| author_sort | Misiran, Masnita |
| collection | UUM |
| description | Stochastic volatility (SV) model is widely applied in the extension of the constant volatility in Black-Scholes option pricing.In this paper, we extend the SV model driven by fractional Brownian motion (FBM). A crucial problem in its application is how the unknown parameters in the model are to be estimated. We propose the innovation algorithm, and follow
by the maximum likelihood estimation approach, which enables us to derive the estimators of parameters involved in this model.We will also present the simulation outcomes to illustrate the efficiency and reliability of the proposed method. |
| first_indexed | 2024-07-04T06:17:54Z |
| format | Article |
| id | uum-21562 |
| institution | Universiti Utara Malaysia |
| language | English |
| last_indexed | 2024-07-04T06:17:54Z |
| publishDate | 2016 |
| publisher | Academic Publications, Ltd. |
| record_format | eprints |
| spelling | uum-215622017-04-13T07:18:00Z https://repo.uum.edu.my/id/eprint/21562/ Maximum likelihood estimation with dynamic measurement errors and application to interest rate modeling Misiran, Masnita QA Mathematics Stochastic volatility (SV) model is widely applied in the extension of the constant volatility in Black-Scholes option pricing.In this paper, we extend the SV model driven by fractional Brownian motion (FBM). A crucial problem in its application is how the unknown parameters in the model are to be estimated. We propose the innovation algorithm, and follow by the maximum likelihood estimation approach, which enables us to derive the estimators of parameters involved in this model.We will also present the simulation outcomes to illustrate the efficiency and reliability of the proposed method. Academic Publications, Ltd. 2016 Article PeerReviewed application/pdf en cc4_by https://repo.uum.edu.my/id/eprint/21562/1/IJPAM%20110%203%202016%20433%20446.pdf Misiran, Masnita (2016) Maximum likelihood estimation with dynamic measurement errors and application to interest rate modeling. International Journal of Pure and Apllied Mathematics, 110 (3). pp. 433-446. ISSN 1311-8080 http://doi.org/10.12732/ijpam.v110i3.5 doi:10.12732/ijpam.v110i3.5 doi:10.12732/ijpam.v110i3.5 |
| spellingShingle | QA Mathematics Misiran, Masnita Maximum likelihood estimation with dynamic measurement errors and application to interest rate modeling |
| title | Maximum likelihood estimation with dynamic measurement errors and application to interest rate modeling |
| title_full | Maximum likelihood estimation with dynamic measurement errors and application to interest rate modeling |
| title_fullStr | Maximum likelihood estimation with dynamic measurement errors and application to interest rate modeling |
| title_full_unstemmed | Maximum likelihood estimation with dynamic measurement errors and application to interest rate modeling |
| title_short | Maximum likelihood estimation with dynamic measurement errors and application to interest rate modeling |
| title_sort | maximum likelihood estimation with dynamic measurement errors and application to interest rate modeling |
| topic | QA Mathematics |
| url | https://repo.uum.edu.my/id/eprint/21562/1/IJPAM%20110%203%202016%20433%20446.pdf |
| work_keys_str_mv | AT misiranmasnita maximumlikelihoodestimationwithdynamicmeasurementerrorsandapplicationtointerestratemodeling |