Learn to trade — and how the algorithms work.

Price is supply and demand expressed over time. Trends form when one side persistently dominates; ranges form when they balance. Your job is to find where the odds tilt.

Survivability beats prediction. Risking a fixed small % per trade (1–2%) and capping daily loss is what keeps you in the game long enough for an edge to pay off.

Express every trade in R — multiples of what you risk. A 2R target means you win twice what you'd lose. Even a 45% win rate is profitable at 2R.

London and New York overlap is the deepest, most tradable window. Thin sessions (late Asia, weekends) gap and whipsaw — TradeIQ flags the active session for you.

Momentum oscillator, 0–100. Below 30 = oversold, above 70 = overbought. Best as a confluence filter, not a standalone signal.

When fast EMAs sit above slow ones and price is above them, the trend is up — and vice versa. A clean stack is one of the strongest trend reads.

Average True Range sizes the market's typical move. TradeIQ places stops and targets as ATR multiples so they adapt to conditions.

Tracks momentum shifts via the gap between two EMAs. A rising histogram above zero confirms bullish momentum building.

A deterministic multi-factor model: RSI + EMA stack + MACD + ATR + news + session, blended into a directional score. Actionable BUY/SELL calls require confluence (two-plus aligned factors); weaker setups become WATCH.

A single 0–100 read per instrument, combining Pulse conviction, trend clarity and mean-reversion stretch. Rank the whole market in one column.

How many standard deviations price sits from its 20-bar mean. Beyond ±2σ a move is statistically stretched and prone to snap back.

Live cross-asset correlation. It stops you from stacking the same bet (e.g. BTC and ETH at 0.96) and surfaces natural hedges.

Describe an edge in plain English; Forge parses it into structured rules and emits backtested Python — entirely in-house, no external AI.