Wavelets optimization method for evaluation of fractional partial differential equations: an application to financial modelling
Abstract In the present paper, we employ a wavelets optimization method is employed for the elucidations of fractional partial differential equations of pricing European option accompanied by a Lévy model. We apply the Legendre wavelets optimization method (LWOM) to optimize the governing problem. The novelty of the proposed method is the inclusion of differential evolution algorithm (DE) in the Legendre wavelets method for the optimized approximations of the unknown terms of the Legendre wavelets. Sequentially, the functions and components of the pricing models are discretized by utilizing the operational matrix of fractional integration of Legendre wavelets. Illustratively, the implementation of the LWOM is exemplified on a pricing European option Lévy model and successfully depicted the stock paths. Moreover, comparison analysis of the Black-Scholes model with a class of Lévy model and LWOM with q-homotopy analysis transform method (q-HATM) is also deliberated out. Accordingly, the technique is found to be appropriate for financial models that can be expressed as partial differential equations of integer and fractional orders, subjected to initial or boundary conditions..
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2018 |
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| Erschienen: |
2018 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:2018 |
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| Enthalten in: |
Advances in difference equations - 2018(2018), 1 vom: 10. Jan. |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Ara, Asmat [VerfasserIn] |
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| Links: |
Volltext [kostenfrei] |
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| BKL: | |
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| Themen: |
Lévy processes |
| doi: |
10.1186/s13662-017-1461-2 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
SPR032106009 |
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| 520 | |a Abstract In the present paper, we employ a wavelets optimization method is employed for the elucidations of fractional partial differential equations of pricing European option accompanied by a Lévy model. We apply the Legendre wavelets optimization method (LWOM) to optimize the governing problem. The novelty of the proposed method is the inclusion of differential evolution algorithm (DE) in the Legendre wavelets method for the optimized approximations of the unknown terms of the Legendre wavelets. Sequentially, the functions and components of the pricing models are discretized by utilizing the operational matrix of fractional integration of Legendre wavelets. Illustratively, the implementation of the LWOM is exemplified on a pricing European option Lévy model and successfully depicted the stock paths. Moreover, comparison analysis of the Black-Scholes model with a class of Lévy model and LWOM with q-homotopy analysis transform method (q-HATM) is also deliberated out. Accordingly, the technique is found to be appropriate for financial models that can be expressed as partial differential equations of integer and fractional orders, subjected to initial or boundary conditions. | ||
| 650 | 4 | |a pricing models |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Lévy processes |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a wavelets approximation |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a optimization |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Khan, Najeeb Alam |e verfasserin |4 aut | |
| 700 | 1 | |a Razzaq, Oyoon Abdul |e verfasserin |4 aut | |
| 700 | 1 | |a Hameed, Tooba |e verfasserin |4 aut | |
| 700 | 1 | |a Raja, Muhammad Asif Zahoor |e verfasserin |4 aut | |
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