The calibration of volatility for option pricing models with jump diffusion processes
DOI10.1080/00036811.2017.1403588zbMath1407.91278OpenAlexW2768632108MaRDI QIDQ4622837
Publication date: 18 February 2019
Published in: Applicable Analysis (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/00036811.2017.1403588
iterative algorithmfinite difference methodTikhonov regularizationEuler-Lagrange equationjump-diffusion model
Numerical methods (including Monte Carlo methods) (91G60) Statistical methods; risk measures (91G70) Probabilistic models, generic numerical methods in probability and statistics (65C20) Finite difference methods for initial value and initial-boundary value problems involving PDEs (65M06) Derivative securities (option pricing, hedging, etc.) (91G20)
Related Items (4)
Cites Work
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- The Pricing of Options and Corporate Liabilities
- A Jump-Diffusion Model for Option Pricing
- Exact solutions for bond and option prices with systematic jump risk
- Jump-diffusion processes: volatility smile fitting and numerical methods for option pricing
- Mathematical models of financial derivatives
- An inverse finance problem for estimation of the volatility
- Non-parametric calibration of the local volatility surface for European options using a second-order Tikhonov regularization
- Robust numerical methods for contingent claims under jump diffusion processes
- Pricing and hedging derivative securities in markets with uncertain volatilities
- Option pricing when underlying stock returns are discontinuous
- An introduction to the mathematical theory of inverse problems
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