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Jesse Livermore Trading Mind System icon

Jesse Livermore Trading Mind System

Professional Updated 2026.08.29

Paste the following prompt into your AI chat to install this skill:

Please install @user_231765ee/livermore1 according to https://skillhub.cn/install/skillhub.md.

About this skill

Problem

  • Trading discussion often lacks a consistent framework: prediction, chasing, averaging down, and emotional stops get mixed together.
  • Specific assets may receive opinion-first answers without checks on trend direction, key points, and time context.
  • Livermore’s principles are hard to apply directly for review, Q&A, and decision checks.

How It Works

  • Question classification: separates factual, framework-only, and mixed questions, then decides whether research is needed first.
  • Livermore-style research: organizes facts by least-resistance path, key-point breakout, and time background.
  • Model-driven answer: uses leader stocks, psychological reversal, and position discipline, while checking rules such as no averaging down.
  • Expression constraints: favors direct, conclusion-first wording and avoids absolute claims.

Limits

  • Best for markets with visible trends, such as equities or commodities, not all asset classes.
  • The framework is based on early-20th-century price patterns and needs manual review in modern markets.
  • It is not an automated trading signal, and it does not replace risk control, compliance judgment, or personal financial capacity.

Use Cases

  • Review a losing trade and check for averaging down, slow stops, or oversized bets.
  • Analyze an equity trend by least-resistance path, prior highs, and breakout confirmation.
  • Add position limits, profit extraction, and no-prediction rules to a trading plan.
  • Screen current sectors using the leader framework to avoid laggard positions.

Best For

  • Private fund researchers who need to decompose losing trades into rule violations
  • Analysts responsible for reviewing paper-trading plans
  • Finance students learning Livermore’s framework for case-based Q&A
  • AI engineers adding market-research steps to trading assistants