Numerical techniques for determining implied volatility in option pricing

DOI10.1016/j.cam.2022.114913zbMath1505.91414OpenAlexW4307125783MaRDI QIDQ2104087

Bashiruddin Nabubie, Songgui Wang

Publication date: 9 December 2022

Published in: Journal of Computational and Applied Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.cam.2022.114913

zbMATH Keywords

finite differenceoption priceimplied volatilityBlack-Scholes equationsteepest descent method

Mathematics Subject Classification ID

Numerical methods (including Monte Carlo methods) (91G60) Finite difference methods for initial value and initial-boundary value problems involving PDEs (65M06) Derivative securities (option pricing, hedging, etc.) (91G20)

Cites Work

• The Pricing of Options and Corporate Liabilities
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• Mathematical models of financial derivatives
• Linear and nonlinear programming.
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• Calibration of the Local Volatility in a Generalized Black--Scholes Model Using Tikhonov Regularization
• Calibrating volatility surfaces via relative-entropy minimization
• Asymptotics and calibration of local volatility models
• A new well-posed algorithm to recover implied local volatility
• The tangential cone condition for the iterative calibration of local volatility surfaces
• Computational Methods for Option Pricing
• A Closed-Form Solution for Options with Stochastic Volatility with Applications to Bond and Currency Options
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