Specifying time-dependent correlation matrices is a problem that occurs in several important areas of finance and risk management. The goal this work to tackle by applying techniques geometric integration financial mathematics, i.e., combine two fields numerical mathematics have not been studied yet jointly. Based on isospectral flows we create valid matrices, so called flows, solving stochasti...

The multivariate lognormal model is a basic pricing model for derivatives with multiple underlying processes, for example, spread options. However, the market observation of implied correlation skew examplifies how inaccurate the constant correlation assumption in the multivariate lognormal model can be. In this paper, we study alternative modeling approaches that generate implied correlation s...

This paper aims to estimate the joint default probability under the structuralform model with a random environment; namely stochastic correlation. By means of a singular perturbation method, we obtain an asymptotic expansion of a two-name joint default probability under a fast mean-reverting stochastic correlation model. The leading order term in the expansion is a joint default probability wit...

Closed orbit theory is generalized to the semiclassical calculation of cross-correlated recurrence functions for atoms in external fields. The cross-correlation functions are inverted by a high resolution spectral analyzer to obtain the semiclassical eigenenergies and transition matrix elements. The method is demonstrated for dipole transitions of the hydrogen atom in a magnetic field. This is ...

We examine seasonal and spatial variations of stochastic-weather-generator (SWG) parameters and their impact on simulated weather sequences. Using daily weather observations from 29 stations across the contiguous United States, we estimate monthly station-specific parameters that are compared with the constant parameters that frequently are used in SWG applications. A WGENtype SWG is then used ...

The correlation approach is considered for the model-following problem using closed-loop noisy data. The idea is to tune the controller parameters such that the output error between the real closed-loop system and the designed one be uncorrelated with the reference signal. This way, the controller parameters will not be influenced by noise. Since perfect decorrelation is not always possible, th...

the discharge data used for hydrological modeling should be the long-term suitable random data without trend and jump which is followed a specific statistical distribution. in this study, the above mentioned conditions were evaluated for 31 years period (1974-2004) of annual mean discharge data of 10 gauging stations of west azarbaijan province. for this purpose, the non-parametric spearman cor...