Comparative Analysis of Root Finding Algorithms for Implied Volatility Estimation of Ethereum Options

Đã lưu trong:
Chi tiết về thư mục
Xuất bản năm:Computational Economics vol. 64, no. 1 (Jul 2024), p. 515
Tác giả chính: Sapna, S.
Tác giả khác: Mohan, Biju R.
Được phát hành:
Springer Nature B.V.
Những chủ đề:
Truy cập trực tuyến:Citation/Abstract
Full Text - PDF
Các nhãn: Thêm thẻ
Không có thẻ, Là người đầu tiên thẻ bản ghi này!

MARC

LEADER 00000nab a2200000uu 4500
001 3098443690
003 UK-CbPIL
022 |a 0927-7099 
022 |a 1572-9974 
022 |a 0921-2736 
024 7 |a 10.1007/s10614-023-10446-8  |2 doi 
035 |a 3098443690 
045 2 |b d20240701  |b d20240731 
084 |a 53284  |2 nlm 
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