ANALISIS KINERJA EXPERT ADVISOR DENGAN OPTIMASI PARAMETER INDIKATOR RSI DAN SMOOTHED MOVING AVERAGE UNTUK TRADING US100 (STUDI KASUS MENGGUNAKAN AKUN STANDAR BROKER FXTM)

Paskah Monika Putri Gultom, Nim. 7213550002 ANALYSIS OF EXPERT ADVISOR PERFORMANCE WITH PARAMETER OPTIMIZATION OF THE RSI AND SMOOTHED MOVING AVERAGE INDICATORS FOR TRADING US100 (A CASE STUDY USING A STANDARD ACCOUNT ON THE FXTM BROKER)
This research aims to design, develop, and evaluate an Expert Advisor (EA) that integrates the Relative Strength Index (RSI) and the Smoothed Moving Average (SMMA) to support automated trading on the US100 index using a standard account from the FXTM broker. The study addresses the high volatility of US100, which often leads to inaccurate trading signals when default indicator settings are used. A parameter optimization procedure was performed through grid search in the MetaTrader 5 Strategy Tester using five years of historical data (July 2020–July 2025). The optimization focused on RSI periods, RSI threshold levels, and SMMA lengths. Performance evaluation was conducted through backtesting and followed by real-time testing to validate stability and robustness.The results show that optimized parameters significantly improve signal accuracy, profitability ratios, and risk management compared with default settings. The EA demonstrated enhanced trend-following capability, reduced false signals during volatile phases, and more consistent performance in both trending and ranging markets. However, performance remains sensitive to sudden volatility spikes, indicating the need for periodic re-optimization to maintain EA reliability in real market conditions.