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/strategy-pivot-designer

@09a9359

Detect backtest iteration stagnation and generate structurally different strategy pivot proposals when parameter tuning reaches a local optimum.

Use this Skill: https://skilld.dev/gh/tradermonty/claude-trading-skills/strategy-pivot-designer

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referencesstrategy_archetypes.md

≈1.5k tokens on demand. Your agent reads this file only when SKILL.md points to it.

Strategy Archetypes Catalog

Eight canonical strategy archetypes cover the primary systematic trading approaches. Each archetype defines default modules, typical failure modes, and compatible pivot targets.


1. Trend Following Breakout (trend_following_breakout)

Description: Buy when price breaks above a consolidation range with volume confirmation. Ride the trend with trailing stops.

Default Modules:

  • hypothesis_type: breakout
  • mechanism_tag: behavior
  • entry_family: pivot_breakout
  • horizon: medium (10-60 days)
  • risk_style: wide (trailing stop 8-12%)

Typical Failure Modes:

  • Whipsaws in range-bound markets
  • Late entries after extended moves
  • Gap-downs through stop levels

Compatible Pivots From: mean_reversion_pullback, volatility_contraction, sector_rotation_momentum


2. Mean Reversion Pullback (mean_reversion_pullback)

Description: Buy oversold pullbacks within an established uptrend. Profit from reversion to mean.

Default Modules:

  • hypothesis_type: mean_reversion
  • mechanism_tag: statistical
  • entry_family: research_only
  • horizon: short (3-14 days)
  • risk_style: tight (stop 3-5%)

Typical Failure Modes:

  • Catching falling knives in trend changes
  • Insufficient recovery within time stop
  • Sector-wide selloffs overwhelming individual stock mean reversion

Compatible Pivots From: trend_following_breakout, volatility_contraction, earnings_drift_pead


3. Earnings Drift PEAD (earnings_drift_pead)

Description: Exploit post-earnings announcement drift by entering after significant earnings surprises.

Default Modules:

  • hypothesis_type: earnings_drift
  • mechanism_tag: information
  • entry_family: gap_up_continuation
  • horizon: medium (5-30 days)
  • risk_style: normal (stop 5-8%)

Typical Failure Modes:

  • One-day gap fills that reverse the drift
  • Market-wide selloffs overwhelming individual stock drift
  • Late entry after drift has already occurred

Compatible Pivots From: event_driven_fade, trend_following_breakout, mean_reversion_pullback


4. Volatility Contraction (volatility_contraction)

Description: Enter when volatility contracts to historical lows (VCP pattern), anticipating expansion in the trend direction.

Default Modules:

  • hypothesis_type: breakout
  • mechanism_tag: structural
  • entry_family: pivot_breakout
  • horizon: medium (10-40 days)
  • risk_style: tight (stop 3-6%)

Typical Failure Modes:

  • False breakouts from contraction zones
  • Extended contraction periods draining capital via time stops
  • Volatility expanding in the wrong direction

Compatible Pivots From: trend_following_breakout, mean_reversion_pullback, statistical_pairs


5. Regime Conditional Carry (regime_conditional_carry)

Description: Hold positions only during favorable macro regimes, using regime detection to filter entries.

Default Modules:

  • hypothesis_type: regime
  • mechanism_tag: macro
  • entry_family: research_only
  • horizon: long (30-120 days)
  • risk_style: normal (stop 5-8%)

Typical Failure Modes:

  • Regime detection lag causing late entries/exits
  • Whipsaws during regime transitions
  • Underperformance during trending markets due to conservative entry timing

Compatible Pivots From: sector_rotation_momentum, event_driven_fade, statistical_pairs


6. Sector Rotation Momentum (sector_rotation_momentum)

Description: Rotate into sectors showing relative strength momentum, exit when momentum fades.

Default Modules:

  • hypothesis_type: momentum
  • mechanism_tag: behavior
  • entry_family: research_only
  • horizon: medium (20-60 days)
  • risk_style: normal (stop 5-8%)

Typical Failure Modes:

  • Momentum reversals during sector rotation shifts
  • Crowded trades in popular sectors
  • Correlation spikes during market stress nullifying diversification

Compatible Pivots From: trend_following_breakout, regime_conditional_carry, earnings_drift_pead


7. Event Driven Fade (event_driven_fade)

Description: Fade overreactions to scheduled or unscheduled events, betting on mean reversion after the initial move.

Default Modules:

  • hypothesis_type: mean_reversion
  • mechanism_tag: information
  • entry_family: research_only
  • horizon: short (1-10 days)
  • risk_style: tight (stop 2-5%)

Typical Failure Modes:

  • Events that represent genuine regime changes (not overreactions)
  • Cascading events that compound the initial move
  • Liquidity gaps during extreme events

Compatible Pivots From: earnings_drift_pead, mean_reversion_pullback, volatility_contraction


8. Statistical Pairs (statistical_pairs)

Description: Trade cointegrated pairs, going long the undervalued and short the overvalued member when spread deviates from equilibrium.

Default Modules:

  • hypothesis_type: mean_reversion
  • mechanism_tag: statistical
  • entry_family: research_only
  • horizon: medium (10-30 days)
  • risk_style: normal (stop via z-score threshold)

Typical Failure Modes:

  • Cointegration breakdown due to fundamental changes
  • Extended spread divergence exceeding risk limits
  • Execution risk on short leg (borrow costs, locate difficulty)

Compatible Pivots From: mean_reversion_pullback, volatility_contraction, regime_conditional_carry


Archetype Compatibility Matrix

Source Archetype Compatible Pivot Targets
trend_following_breakout mean_reversion_pullback, volatility_contraction, sector_rotation_momentum
mean_reversion_pullback trend_following_breakout, volatility_contraction, earnings_drift_pead
earnings_drift_pead event_driven_fade, trend_following_breakout, mean_reversion_pullback
volatility_contraction trend_following_breakout, mean_reversion_pullback, statistical_pairs
regime_conditional_carry sector_rotation_momentum, event_driven_fade, statistical_pairs
sector_rotation_momentum trend_following_breakout, regime_conditional_carry, earnings_drift_pead
event_driven_fade earnings_drift_pead, mean_reversion_pullback, volatility_contraction
statistical_pairs mean_reversion_pullback, volatility_contraction, regime_conditional_carry

Source: SKILL.md on GitHub

1 warning3d5 checks · Risk SAFE
  • Gen Agent Trust Hub3d

    The strategy-pivot-designer skill is a local utility for quantitative trading researchers. It provides logic to identify when a strategy's backtest performance has plateaued and automatically generates alternative strategy architectures (pivots) to explore. The skill operates exclusively on local JSON and YAML data, utilizes secure parsing methods, and follows identifier sanitization best practices. No malicious patterns or security risks were identified.

  • Socket3d

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  • Snyk3d

    Risk: LOW · No issues

  • Runlayer7mo

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  • ZeroLeaks5mo

    Score: 93/100 · 2 sections analyzed

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Last checked against GitHub 15 hours ago.

Activeupdated 7 months ago

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