COMPARATIVE PRODUCTIVITY ANALYSIS OF MARTINGALE AND LINEAR AVERAGING STRATEGIES IN LOCO LONDON GOLD ROLLING CONTRACTS (XUL10) WITHIN INDONESIA’S ALTERNATIVE TRADING SYSTEM

The high volatility of the derivative market—particularly in the Loco London Gold Rolling Contract (XUL10) traded within Indonesia’s Alternative Trading System (ATS)—necessitates the use of adaptive and measurable position-management strategies. This study evaluates two contrasting averaging-down approaches: Martingale, based on exponential lot increments, and Linear Averaging, based on linear lot increments. The objective is to compare their effectiveness, measured through liquidity and recovery speed, and their efficiency, measured through initial capital endurance. A quantitative comparative method is applied through historical backtesting of XAU/USD price data from 2024 to mid-2025 using target iterations of 30, 40, and 50 points. Performance is assessed using multidimensional indicators such as Profit Factor (PF), Return on Margin (ROM), Efficiency Ratio (ER), and capital endurance analysis through margin-call (MC) risk mapping relative to key support levels (S1 and S2). The findings show that systematic strategies produce far more consistent productivity than speculative real-market practices and reveal a clear trade-off between effectiveness and efficiency. Martingale demonstrates higher effectiveness and superior liquidity speed due to its exponential leverage, achieving the highest net profit in scenarios such as the 40-point target in 2025. In contrast, Linear Averaging provides higher efficiency and stronger capital endurance, emerging as the safest and most consistent approach—particularly at the 30-point target—by keeping MC levels within the safe Support-2 zone, although with slower recovery. Overall, Martingale offers aggressive profit potential but carries significant margin-call risk that demands strict margin management, while Linear Averaging offers superior capital safety and long-term sustainability, making it the preferable model for traders with lower risk tolerance.