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

S. Sapna () and Biju R. Mohan ()
Additional contact information
S. Sapna: National Institute of Technology Karnataka
Biju R. Mohan: National Institute of Technology Karnataka

Computational Economics, 2024, vol. 64, issue 1, No 19, 515-550

Abstract: Abstract 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.

Keywords: Implied volatility; Cryptocurrency; Ethereum options; Hybrid algorithms; Black–Scholes model (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s10614-023-10446-8 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:kap:compec:v:64:y:2024:i:1:d:10.1007_s10614-023-10446-8

Ordering information: This journal article can be ordered from
http://www.springer. ... ry/journal/10614/PS2

DOI: 10.1007/s10614-023-10446-8

Access Statistics for this article

Computational Economics is currently edited by Hans Amman

More articles in Computational Economics from Springer, Society for Computational Economics Contact information at EDIRC.
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().