Supply Demand Snop automates MT5 supply and demand strategy for consistent trade entries

This Review of Supply Demand Snop in 2025 presents a focused performance analysis and practical review of how the EA behaves live and in backtests. Supply Demand Snop is built around simple candle calculations that identify supply and demand zones, then executes trades on MT5 with options for single-shot entries or a conditional martingale sequence. The algorithm reads consecutive candle structures and uses volume-aware timing and trailing stop logic to tighten exits and protect gains. What makes Supply Demand Snop unique is its emphasis on simplicity: the author, Sudibyo Raharjo, designed the EA to require minimal parameter tuning while providing ready-to-use presets and a clear balance recommendation of $1,000. The code prioritizes predictable behavior over complex pattern matching, which helps traders understand why a trade was opened and how the trailing stop will respond as price moves. Supply Demand Snop handles trending swings and short consolidation breaks best, and it is less effective in highly erratic, news-driven spikes unless martingale protections are active. Risk management is implemented through configurable stop values, optional martingale sizing, and an automated trailing stop that attempts to lock profit incrementally. Expected trading results emphasize moderate trade frequency on XAUUSD, steady long-term growth with disciplined settings, and the need for ongoing monitoring when martingale is enabled.

Typical trading results from Supply Demand Snop show a win rate expectation between 50 and 65 percent depending on timeframe and settings. Backtests and demo forward tests reported by users indicate average trade frequency as low to medium, roughly 5 to 20 trades per month on XAUUSD when using M15 to H1 timeframes. Drawdown management is driven by the trailing stop and optional martingale; conservative single-shot mode tends to keep peak drawdowns under 15 percent in many test samples while martingale configurations can push drawdowns toward 25–35 percent in stressed scenarios. Account requirements start at a recommended $1,000 minimum to match preset lot-sizing. Traders should expect smoother equity curves with single-shot operation and higher but faster-executing returns with martingale enabled. Real trading results and trading results metrics should be verified on a demo or small live account before full deployment.

Supply Demand Snop presents a moderate to aggressive risk profile depending on mode selection. In single-shot mode the risk is moderate and comparable to many systematic EAs, while activating martingale increases risk toward aggressive territory due to compounding position sizing. Stop loss strategy relies on candle-structure based levels and the trailing stop to preserve gains, not fixed guaranteed stops. Position sizing should be conservative: aim for 0.5 to 2 percent risk per trade on the recommended $1,000 minimum account, and scale up only after successful demo validation. Vulnerabilities include news-driven volatility and thin liquidity during market open hours, which can widen spreads and trigger price slippage. For cautious adoption use single-shot mode and maintain clear monitoring when martingale is engaged. Supply Demand Snop documentation recommends the minimum $1,000 starting capital to align with preset risk parameters.

Install Supply Demand Snop by copying the EA file into the MT5 Experts folder and restarting MetaTrader 5. Attach the EA to your chosen XAUUSD chart and load the included preset to match the developer recommendations. Configure the key parameters: select single-shot or martingale mode, set the trailing stop distance, and confirm lot sizing relative to your account balance. Choose a broker with low spreads and reliable execution for XAUUSD, preferably one offering raw spreads or low-cost swaps. Test extensively in the MT5 strategy tester and on a demo account across M15 to H1 timeframes before trading live. Start with the recommended $1,000 minimum and small lots for live testing.