Learn to trade like institutions. Master order blocks, fair value gaps, liquidity sweeps, and market structure with AI-powered Smart Money analysis.
Smart Money Concepts (SMC) is a trading methodology that analyzes how institutional traders (banks, hedge funds) move markets. Instead of following retail indicators, SMC traders identify: (1) Market Structure — trend direction through higher highs/lows, (2) Order Blocks — zones where institutions placed large orders, (3) Fair Value Gaps — imbalances where price moved too fast, (4) Liquidity Sweeps — stops being hunted before the real move. SignalPro AI identifies all of these patterns automatically.
An order block is the last candle before a strong impulsive move. It represents where institutional orders accumulated. To trade them: (1) Identify a strong impulsive move that breaks structure, (2) Mark the last opposing candle before the move (the order block), (3) Wait for price to retrace into the order block zone, (4) Enter with a stop below/above the order block, (5) Target the next liquidity pool. SignalPro AI detects order blocks across all timeframes.
A Fair Value Gap is a 3-candle pattern where the middle candle creates an imbalance (gap between wicks of first and third candles). These gaps act as magnets for price: (1) Bullish FVG: price tends to retrace down to fill the gap before continuing up, (2) Bearish FVG: price tends to retrace up to fill the gap before continuing down. FVGs combined with order blocks create high-probability trade setups. SignalPro identifies and signals these confluence zones.
Smart money needs liquidity (retail stop losses) to fill large orders. Liquidity sweeps happen when price spikes through obvious support/resistance to trigger stops, then reverses sharply. Pattern: (1) Identify obvious highs/lows where stops accumulate, (2) Wait for a fast spike through that level (the sweep), (3) Enter on the reversal candle, (4) Stop below/above the sweep low/high, (5) Target internal liquidity. SignalPro AI detects these institutional sweeps in real-time.
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