APPLYING ARTIFICIAL INTELLIGENCE TO ENHANCE THE QUALITY OF AUTOMATED FOREX TRADING SYSTEMS

Trend-following trading is a popular strategy in automated forex trading. This approach achieves high profitability and success rates in trending markets. However, this strategy performs poorly in non-trending markets, such as choppy, range-bound, or sideways markets. In this study, we focus on leveraging artificial intelligence - specifically, LSTM networks—to filter out suboptimal trades by predicting market trends. The experimental results were quite surprising: applying artificial intelligence to the automated trading system enabled us to eliminate more than 70% of the ineffective trades generated by the existing trend-following system. Keywords: Expert Advisor System; RNN; LSTM; Time Series; Forex Strategy