Discrete and Continuous Models and Applied Computational ScienceDiscrete and Continuous Models and Applied Computational Science2658-46702658-7149Peoples' Friendship University of Russia named after Patrice Lumumba (RUDN University)8505Hybrid Information System for Estimation of Risks in Financial MarketsBogdanovA VInstitute for High Performance Computing and Information Systemsbogdanov@csa.ruDegtyarevA BКафедра компьютерного моделирования и многопроцессорных систем; Санкт-Петербургский государственный университет; Saint-Petersburg State Universitydeg@csa.ruGaraevI Atigersp@mail.ruInstitute for High Performance Computing and Information SystemsSaint-Petersburg State University020320103.2515708092016Copyright © 2010,2010Nowadays there exists a large variety of forecasting methods based on neural networks technologies which allow to adequately simulate the nonlinear processes with noisy data in slowly varying markets. However, in the conditions of strong turbulence they are not capable to promptly response to swiftly changing environment, and, hence, to market conjuncture changes. It has grown in a very serious problem, as the decisions accepted on the basis of these technologies can be resulted in movement of hundreds billion dollars in the financial markets, and any incorrectly revealed tendency can lead to large losses.We will notice that this problem has recently arisen due to joining of new world players to the common economics, and due to, as a consequence, decrease in controllability of the international system. In the presented work the dynamic approach will be considered which properly operates in swiftly changing markets. It is based on a combination of neural networks technologies with algorithms of quantum mechanics calculations.forecasting methodsneural networks technologiesdynamicapproachquantum mechanics calculationsметоды прогнозированиянейросетевые технологиидинамический подходквантовые вычисления[Voit J. The Statistical Mechanics of Financial Markets (Texts and Monographs in Physics). - Springer-Verlag, Berlin, 2001.][Huang Z.-F. The First 20 Min in the Hong Kong Stock Market // Physica A. - 2000. - Vol. 287. - Pp. 405-411.][Vaquero L. M. et al. A Break in the Clouds: Toward a Cloud Definition // ACM SIGCOMM Computer Communication Review. - 2009. - Vol. 39, No 1.][Non-Stationary and Stationary Prediction of Financial Time Series using Dynamic Ridge Polynomial Neural Network / R. Ghazali, A. J. Hussain, N. M. Nawi, B. Mohamad // Neurocomputing. - 2009. - Vol. 72. - Pp. 2359-2367.][Y.uml.u S., G.urgen F. S., Okay N. A Comparison of Global, Recurrent and Smoothed-Piecewise Neural Models for Istanbul Stock Exchange (ISE) Prediction // Pattern Recognition Letters. - 2005. - Vol. 26, No 13. - Pp. 2093-2103.][Chiarella C., El-Hassan N., Kucera A. Evaluation of American Option Prices in a Path Integral Framework using Fourier-Hermite Series Expansions // Journal of Economic Dynamics & Control. - 1999. - Vol. 23. - Pp. 1387-1424.][Гудман Ф. Г., Вахман Т. Динамика рассеяния газа поверхностью. - М.: Мир, 1980.][Bogdanov A., Gevorkyan A. Quantum Chaos in the Framework of Complex Probability Processes. Thermodynamics of Nonrelativistic Vacuum. - Los Alamos National Laboratory e-print archive No. quantph/ 9810079.][Nechaev Y. I. Principle of Competition at Neural Network Technologies Realization in On-Board Real-Time Intelligence Systems // Proceedings of First International Congress on Mechanical and Electrical Engineering and Technology "MEET-2002" and Fourth International Conference on Marine Industry "MARIND-2002". - Vol. 3. - 2002. - Pp. 51-57.]