Swing Trading

objective

Manage multi-day swing strategies with regime-aware sizing and disciplined risk exits.

workflow

1. •define setup taxonomy and multi-day holding horizon rules.
2. •select entries using trend, reversal, and catalyst filters.
3. •size positions by volatility and portfolio concentration constraints.
4. •monitor overnight gap risk and event exposure throughout holding period.
5. •exit through target, stop, or thesis invalidation framework.

required diagnostics

• •setup win rate and expectancy by market regime.
• •overnight gap contribution to pnl and risk.
• •holding-period distribution and signal decay.
• •stop-loss and target-hit efficiency statistics.
• •portfolio-level concentration drift during swings.

risk controls

• •enforce per-trade and portfolio stop thresholds.
• •enforce event-calendar risk adjustments before major catalysts.
• •enforce concentration caps across correlated names.

outputs

• •run python scripts/swing_trading_diagnostics.py input.csv --output diagnostics.json and keep the json artifact.
• •write an implementation memo using references/swing-trading-playbook.md with assumptions, tests, limits, and rollout plan.

resources

• •use scripts/swing_trading_diagnostics.py for deterministic diagnostics.
• •use references/swing-trading-playbook.md for the domain checklist and delivery structure.