In some options markets (e.g. commodities), options are listed with only a single maturity for each underlying. In others, (e.g. equities, currencies), options are listed with multiple maturities. In this paper, we analyze a special class of pure jump Markov martingale models and provide an algorithm for calibrating such model to match the market prices of European options of multiple strikes a...

We show that for the originally ill-posed inverse problem of calibrating a localized jump-diffusion process to given option price data, Tikhonov regularization can be used to get a well-posed optimization problem. Furthermore we prove stability as well as convergence of the regularized parameters using the forward partial integrodifferential equation associated to the European call price. By pr...

The quality of point correspondences is crucial for the successful application of multi camera self-calibration procedures. There are several interest point detectors, local descriptors and matching algorithms, which can be combined almost arbitrarily. In this paper, we compare the point correspondences produced by several such combinations. In contrast to previous comparisons, we evaluate the ...

Non-invasive optoacoustic mapping of temperature in tissues with low blood content can be enabled by administering external contrast agents. Some important clinical applications of such approach include temperature mapping during thermal therapies in a prostate or a mammary gland. However, the technique would require a calibration that establishes functional relationship between the measured no...

Robotic C-arms are capable of complex orbits that can increase field of view, reduce artifacts, improve image quality, and/or reduce dose; however, it can be challenging to obtain accurate, reproducible geometric calibration required for image reconstruction for such complex orbits. This work presents a method for geometric calibration for an arbitrary source-detector orbit by registering 2D pr...

Accurate and detailed spatial soil information about within-field variability is essential for variable-rate applications of farm resources. Soil total nitrogen (TN) and total carbon (TC) are important fertility parameters that can be measured with on-line (mobile) visible and near infrared (vis-NIR) spectroscopy. This study compares the performance of local farm scale calibrations with those b...

The use of an ensemble of local Common Spatial Patterns (CSP) patches (CSPP) is proposed, which can be considered as a compromise between Laplacians and CSP: CSPP reaches a robust performance with less training data than CSP, while being superior to Laplacian filtering. This property is shown to be particularly useful for the co-adaptive calibration design and is demonstrated in combination wit...

For the calibration of laser induced plasma spectrometers robust and eecient local search methods are required. Therefore, several local optimizers from nonlinear optimization, random search and evolutionary computation are compared. It is shown that evolutionary algorithms are superior with respect to reliability and eeciency. To enhance the local search of an evolutionary algorithm a new meth...

We propose an optimization formulation using the l1 norm to ensure accuracy and stability in calibrating a local volatility function for option pricing. Using a regularization parameter, the proposed objective function balances calibration accuracy with model complexity. Motivated by the support vector machine learning, the unknown local volatility function is represented by a spline kernel fun...

The Gauss–Marquardt–Levenberg (GML)method of computer-based parameter estimation, in commonwith other gradient-based approaches, suffers from the drawback that it may become trapped in local objective functionminima, and thus report ‘‘optimized’’ parameter values that are not, in fact, optimized at all. This can seriously degrade its utility in the calibration of watershed models where local op...