Abstract
The article describes the process of creating a flexible trading strategy for algorithmic tradingin a specialized development environment MQL5 IDE in the MetaTrader 5 multi-asset platform.The advantages and expediency of using the MetaTrader 5, MetaTrader 4 platforms andtheir respective trading applications Trade Assistant, Forex Trade Manager, Trade Time Manager,CAP Gold Albatross EA and Fast Copy are shown. A comparative analysis of the existing implementationsof trading advisors based on various indicators, as well as those created using intelligenttechnologies, has been carried out. In the previously implemented trading advisors, for predictingthe prices of the volatility of financial assets, flexible learning algorithms, compensatoryfuzzy logic models, and technical analysis tools are mainly used, which entails high time costs, inconditions of high financial market volatility. To solve this problem, the authors propose an integratedapproach based on the use of technical analysis tools built into the MetaTrader 5 multimediaplatform and the trading strategy automation algorithm, which makes it possible to obtain aforecast of a given accuracy for the selected instrument in real time. The paper substantiates theneed to introduce elements of automatic trading when analyzing the quotes of financial instrumentsand managing a trading account in order to avoid mechanical, analytical, organizationaland psychological mistakes made by traders. The study shows step by step the process of creating,debugging, testing, optimizing and executing the implemented trading advisor. An algorithm forautomating a trading strategy has been developed and its block diagram has been presented.The initial data for the trading strategy automation algorithm are determined, and the mathematicalapparatus for calculating indicators of limit orders of the TakeProfit and StopLoss types isdescribed. Since exchange trading is associated with many risks, we analyzed the impact of differentvalues of lots of TakeProfit and StopLoss limit orders on possible profit and drawdown limit(loss). As a result, the EA worked correctly in real time without human intervention for eightweeks using two trading strategies. The results of testing the developed software allow us to drawthe following conclusions: when the EA shows a high degree of recommendation, the actual financialassets show high efficiency.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
