DEPENDENCY INJECTION USING FOR THE DEVELOP OF INFORMATION TECHNOLOGY FOR INVESTIGATION OF PARAMETRIC VAR METHODS - Zinchenko, Artem Yu. (Systems and Technologies, 2022)
Summary. This paper considers the use of technology of loosely coupled software modules of an automated information system based on injection of dependencies to assess and forecast market risks. Based on the implemented automated system for basic parametric VaR methods, calculations were performed and modeling was performed, in particular for the exponentially smoothed model, variation-covariance (multicomponent portfolio method), volatility model and heuristic model. Based on the theory of interval estimation, it is proposed to use a heuristic model, the idea of ​​which is that the coefficients of the forecast model are also predicted. So, the model does not work on coefficients adapted to previous statistics, but it works on coefficients that are projected to calculate the forecast for the next step. In addition, the article analyzes in detail the use of the principle of Dependency inversion in the implementation of such service-oriented architectural solutions. Finally, the results of comparing models for assessing and forecasting market risks are presented. The best models are selected.