Variance reduction via empirical variance minimization: convergence and complexity
This proceedings publication is a compilation of selected contributions from the “Third International Conference on the Dynamics of Information Systems” which took place at the University of Florida, Gainesville, February 16–18, 2011. The purpose of this conference was to bring together scientists and engineers from industry, government, and academia in order to exchange new discoveries and results in a broad range of topics relevant to the theory and practice of dynamics of information systems. Dynamics of Information Systems: Mathematical Foundation presents state-of-the art research and is intended for graduate students and researchers interested in some of the most recent discoveries in information theory and dynamical systems. Scientists in other disciplines may also benefit from the applications of new developments to their own area of study.
In the given paper the aggregated randomized indices method is modified for credit scoring. Coefficients of the modified method can be calibrated on a massive training set in comparison with a standard version. Different credit scoring models are analyzed, i.e. with a binary scale and a continuous one. The Monte Carlo method is applied to measure the efficiency of models.
We observe the self-assembling of the dipolar hard sphere particles at low temperature by Monte Carlo simulation. We find different types of stable structures of dipolar particles which appear when the isotropic phase of the system becomes unstable. Specifically, we find an interesting case of parallel cylindrical domains. The value of the total dipole moment of each domain is significantly large compared to the average value of the whole system. Models with dipolar interactions may form structures comprised of layers with anti-parallel dipole orientation.
In this paper we present a novel approach towards variance reduction for discretised diffusion processes. The proposed approach involves specially constructed control variates and allows for a significant reduction in the variance for the terminal functionals. In this way the complexity order of the standard Monte Carlo algorithm (ε−3) can be reduced down to ε−2 log(ε−1) in case of the Euler scheme with ε being the precision to be achieved. These theoretical results are illustrated by several numerical examples.
The paper suggests an original credit-risk based model for deposit insurance fund adequacy assessment. The fund is treated as a portfolio of contingent liabilities to the insured deposit-holders. The fund adequacy assessment problem is treated as an economic capital adequacy problem. Implied credit rating is used as the target indicator of solvency. This approach is consistent with the contemporary risk management paradigm and the recommendations of the Basel II Capital Accord. The target level of the fund corresponding to the target solvency standard is estimated in a Monte Carlo simulation framework using the actual data on the Russian banking system covering 1998-2005. Author acknowledges the generous support and fruitful discussions with representatives of the Russian Deposit Insurance Agency. The author expresses his personal views and not the views of the Agency.
A model for organizing cargo transportation between two node stations connected by a railway line which contains a certain number of intermediate stations is considered. The movement of cargo is in one direction. Such a situation may occur, for example, if one of the node stations is located in a region which produce raw material for manufacturing industry located in another region, and there is another node station. The organization of freight traﬃc is performed by means of a number of technologies. These technologies determine the rules for taking on cargo at the initial node station, the rules of interaction between neighboring stations, as well as the rule of distribution of cargo to the ﬁnal node stations. The process of cargo transportation is followed by the set rule of control. For such a model, one must determine possible modes of cargo transportation and describe their properties. This model is described by a ﬁnite-dimensional system of diﬀerential equations with nonlocal linear restrictions. The class of the solution satisfying nonlocal linear restrictions is extremely narrow. It results in the need for the “correct” extension of solutions of a system of diﬀerential equations to a class of quasi-solutions having the distinctive feature of gaps in a countable number of points. It was possible numerically using the Runge–Kutta method of the fourth order to build these quasi-solutions and determine their rate of growth. Let us note that in the technical plan the main complexity consisted in obtaining quasi-solutions satisfying the nonlocal linear restrictions. Furthermore, we investigated the dependence of quasi-solutions and, in particular, sizes of gaps (jumps) of solutions on a number of parameters of the model characterizing a rule of control, technologies for transportation of cargo and intensity of giving of cargo on a node station.
A form for an unbiased estimate of the coefficient of determination of a linear regression model is obtained. It is calculated by using a sample from a multivariate normal distribution. This estimate is proposed as an alternative criterion for a choice of regression factors.