Gap trading
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Analyze markets using Gap Trading (price gaps). Trade common, breakaway, runaway, and exhaustion gaps. Activate when the user asks to analyze, interpret, or build signals based on Gap Trading or price gaps.
SKILL.md
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Gap Trading
Overview
Gap Trading (price gaps) — Trade common, breakaway, runaway, and exhaustion gaps.
When to use this skill
Use when the user asks to:
- Analyze or interpret Gap Trading on a chart or dataset
- Build buy/sell signals or alerts based on price gaps
- Combine Gap Trading with other indicators for confirmation
How it works
Trade common, breakaway, runaway, and exhaustion gaps. Apply it on OHLCV data (open, high, low, close, volume) for any timeframe. Always confirm with price structure, trend context, and at least one independent indicator before acting.
Reading the signals
- Bullish bias: signal aligns with higher highs/higher lows and rising volume.
- Bearish bias: signal aligns with lower highs/lower lows and rising volume.
- No-trade: conflicting context or low volatility/volume.
Worked example (Python)
import pandas as pd
# df has columns: open, high, low, close, volume (datetime index)
# Compute the indicator, then generate signals
# (use pandas/numpy or ta libraries; validate on out-of-sample data)
Risk management
- Define stop-loss from structure or ATR before entry.
- Size positions by fixed-fractional risk (e.g. 0.5–1% per trade).
- Never rely on a single indicator; require confluence.
Common pitfalls
- Over-optimizing parameters to past data (curve fitting).
- Ignoring the higher-timeframe trend.
- Acting on signals during low liquidity.
Educational analysis only. Not financial advice.