Feedback Request: Backtest and Montecarlo results across multiple instruments

Hello everyone. I have been developing and testing a system built by studying gold, and I would like to share the backtest equity curves and bootstrap Montecarlo analyses based on two hundred simulations per asset class. All tests started with an initial capital of 100,000.00. I tested the algorithm live on gold for two and a half months, achieving a 3 percent drawdown with a 10 percent gain. Since this is my first algorithm, I would love to hear the opinion of anyone who has long-term experience regarding algorithms and live execution. Starting with the asset performance breakdown, the backtest results derived from the provided equity curve images show distinct trajectories across different markets. For XAGUSD, the Montecarlo simulation shows an average PnL of plus 111.48 percent with a standard deviation of 75.92 percent, a median of plus 120.71 percent, and a win rate of 39.7 percent. The average maximum drawdown sits at 27.88 percent with a worst-case scenario of 68.49 percent, yielding a loss probability of 9.0 percent. For XAUUSD, as clearly illustrated by its steady upward equity curve ending at an initial capital of 100,000.00 turning into a final capital of 211,493.84 with a PnL of plus 111.49 percent, the Montecarlo indicates an average PnL of plus 87.98 percent and a win rate of 37.7 percent. The average maximum drawdown is tightly controlled at 9.00 percent, and the loss probability is exceptionally low at 1.0 percent. For NAS100, represented by a strongly bullish equity curve moving from 100,000.00 to a final capital of 182,058.44 with an 82.06 percent PnL, the Montecarlo reveals an average PnL of plus 57.53 percent with a win rate of 36.6 percent. The average maximum drawdown is 9.54 percent, and the loss probability is 4.5 percent. For SP500, shown in the equity chart growing from 100,000.00 to a final capital of 1,255,725.50 reflecting a 25.57 percent PnL, the Montecarlo yields an average PnL of plus 49.64 percent alongside a win rate of 34.8 percent. The average maximum drawdown is 8.21 percent, and the loss probability stands at 8.5 percent. For GER40, the equity curve highlights significant growth, moving from an initial capital of 100,000.00 to a final capital of 365,400.96 with a total PnL of plus 265.40 percent in a clean upward trend. For USDJPY, displayed through an equity curve rising to a final capital of 128,863.74 with a PnL of plus 28.86 percent, the Montecarlo records an average PnL of plus 9.10 percent and a lower win rate of 28.3 percent. The average maximum drawdown is 9.35 percent, while the probability of loss increases to 35.0 percent. For GBPUSD, whose choppy and sideways equity curve closes at a modest final capital of 101,093.85 with a PnL of plus 1.09 percent, the Montecarlo shows an average PnL of minus 0.14 percent and a weak win rate of 23.4 percent. The average maximum drawdown is 11.80 percent, and the probability of a losing outcome reaches 53.0 percent. For USDCAD, characterized by an equity chart showing a sharp jump followed by a prolonged decline ending at a final capital of 103,845.06 with a 3.85 percent PnL, the Montecarlo delivers an average PnL of minus 1.61 percent and a win rate of only 19.1 percent. The average maximum drawdown is 13.04 percent, and the loss probability hits 58.5 percent. Looking at these overarching patterns, the system clearly thrives on trending assets like precious metals and major stock indices, while struggling significantly on currency pairs where win rates drop below 25 percent and the odds of losing money exceed 50 percent. I would love to hear thoughts from the community on whether this stark performance divergence points toward structural edge differences across asset classes or potential overfitting on directional markets, and whether currency pairs should simply be dropped from this version. Any constructive feedback is greatly appreciated.