The system of predictive analysis of Bank investments using technologies of supercomputer simulation

Abstract

The article discusses an approach to building a system for generating a bank investment prediction with the technology of parallel computing. We develop a predictive model of the price of securities for the banking business on the stock market. For predictive analysis of investments, the choice of a mathematical model was justified using the Monte Carlo method. Computer simulation was carried out to form a forecast of securities prices based on historical data on securities of Goldman Sachs. Estimates of the execution time of the forecasting algorithm by the parallel programming method are obtained. The conclusion is made about the applicability of the proposed model when using the method of algorithmic trading in the stock market. The technical requirements for the development of a predictive analytics system for the Bank's investment portfolio are formulated.