Non-parametric calibration of jump–diffusion option pricing models
نویسندگان
چکیده
منابع مشابه
Non-parametric calibration of jump–diffusion option pricing models
generally, exponential Lévy models to a finite set of observed option prices. We show that the usual formulations of the inverse problem via non-linear least squares are ill-posed and propose a regularization method based on relative entropy: we reformulate our calibration problem into a problem of finding a risk-neutral exponential Lévy model that reproduces the observed option prices and has ...
متن کاملNon-parametric option pricing models
The goal of non-parametric option pricing models is to price and risk mange financial derivatives in a model-free approach. Standard option pricing models need to assume a certain dynamics for the underlying. Model parameters are calibrated (or bootstrapped) to match certain conditions. These can be an exact fit to some market instruments whenever possible, a best fit otherwise, or some risk mi...
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We present a non-parametric method for calibrating jump-diffusion models to a finite set of observed option prices. We show that the usual formulations of the inverse problem via nonlinear least squares are illposed and propose a regularization method based on relative entropy: we reformulate our calibration problem into a problem of finding a risk neutral jump-diffusion model that reproduces t...
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A well-studied topic in finance is fitting pricing models to available market information; this is the inverse of the option pricing problem. The accuracy of least squares calibration using option premiums and particle filtering of price data to find model parameters is determined. Derivative models using exponential Lévy processes are calibrated using regularized weighted least squares with re...
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ژورنال
عنوان ژورنال: The Journal of Computational Finance
سال: 2004
ISSN: 1460-1559
DOI: 10.21314/jcf.2004.123