Using Trading System Consolidated Models in Stock Exchange Price Forecasting

Abstract

For successful trading on stock exchanges, it is important to use trading tools that will ensure success in trading operations and provide competitive advantages. The purpose of the article is to develop an algorithm for the creation of a trading system and selecting a research object whose shares may subsequently become the object of real trade. The basis of the developed trading system is the consolidated mathematical model based on several models (multipliers, neural network and discounted cash flows). Two forecasting models were created. The first consolidated model estimates share prices with lower deviation from the actual prices than the prices predicted by other mathematical models. For the second consolidated model, TakeProfit at the forecasted level was set. It allows closing the position as soon as a targeted price is reached. The results of the work identified directions for improving trading algorithms by use of the elements of fundamental analysis, namely, by forecasting the impact of macroeconomic factors and an evaluation of market indices.