Comparative Analysis of Root Finding Algorithms for Implied Volatility Estimation of Ethereum Options
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| Xuất bản năm: | Computational Economics vol. 64, no. 1 (Jul 2024), p. 515 |
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| Tác giả chính: | |
| Tác giả khác: | |
| Được phát hành: |
Springer Nature B.V.
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| Những chủ đề: | |
| Truy cập trực tuyến: | Citation/Abstract Full Text - PDF |
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| 100 | 1 | |a Sapna, S. |u National Institute of Technology Karnataka, Department of Information Technology, Surathkal, India (GRID:grid.444525.6) (ISNI:0000 0000 9398 3798) | |
| 245 | 1 | |a Comparative Analysis of Root Finding Algorithms for Implied Volatility Estimation of Ethereum Options | |
| 260 | |b Springer Nature B.V. |c Jul 2024 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a In this paper, a comparative analysis of traditional and hybrid root finding algorithms is performed in estimating implied volatility for Ethereum Options using the Black–Scholes model. Results indicate the efficiency of Newton–Raphson method in terms of algorithmic convergence as well as computational time. Since Newton–Raphson method may not always lead to convergence, the best approximation technique is chosen from the convergent bracketed methods. The hybrid Bisection–Regula Falsi method serves as the best choice for root estimation among the bracketed methods under consideration. | |
| 653 | |a Newton-Raphson method | ||
| 653 | |a Algorithms | ||
| 653 | |a Bisection | ||
| 653 | |a Convergence | ||
| 653 | |a Comparative analysis | ||
| 653 | |a Computing time | ||
| 653 | |a Volatility | ||
| 653 | |a Estimation | ||
| 653 | |a Futures | ||
| 653 | |a Monte Carlo simulation | ||
| 653 | |a Hedging | ||
| 653 | |a Institutional investments | ||
| 653 | |a Derivatives | ||
| 653 | |a Digital currencies | ||
| 653 | |a Securities prices | ||
| 653 | |a Stochastic models | ||
| 653 | |a Methods | ||
| 653 | |a Financial analysis | ||
| 700 | 1 | |a Mohan, Biju R. |u National Institute of Technology Karnataka, Department of Information Technology, Surathkal, India (GRID:grid.444525.6) (ISNI:0000 0000 9398 3798) | |
| 773 | 0 | |t Computational Economics |g vol. 64, no. 1 (Jul 2024), p. 515 | |
| 786 | 0 | |d ProQuest |t ABI/INFORM Global | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3098443690/abstract/embedded/H09TXR3UUZB2ISDL?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3098443690/fulltextPDF/embedded/H09TXR3UUZB2ISDL?source=fedsrch |