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Risk & Position SizingFREE

Stress-test your position-sizing rules before the market does

You have sizing 'rules' you mostly follow. Find out where they break — in a conversation, not in a drawdown.

The prompt — copy and run it

Act as a risk-management TEACHER (not an advisor — this is educational analysis of my own process, not investment advice; do not recommend any specific security, position, or trade). I will describe my position-sizing rules and account context in general terms. Your job:

A) RESTATE my sizing rules as explicit IF/THEN logic, flagging anything vague ('I size down when unsure') that isn't actually a rule.

B) STRESS SCENARIOS — walk my rules through: 3 losing trades in a row; a position gapping through my planned exit; correlated positions moving together; volatility doubling. For each, show what my rules would have me do and where they're silent.

C) THE HOLES — the top 3 situations my rules don't cover, phrased as questions I need to answer for myself (do NOT answer them with recommendations).

D) TEACH — explain the general principle each hole relates to (risk-of-ruin, correlation risk, gap risk) in plain language with a generic numeric illustration.

My sizing rules & context: [DESCRIBE — e.g. 'I risk a fixed % per trade, max N open positions, no rule for correlated names']

Rules: Never tell me what to buy, sell, or how large any real position should be. If I ask for a pick or a target, refuse and return to process. This is education about MY rules, not advice.

How to use this prompt

  1. Copy the full prompt above with the Copy button.
  2. Add your context. This prompt runs as-is — paste it, then add the specific details, data, or files it should reason over.
  3. Paste into ChatGPT, Claude, or Gemini and run. Read the reality guardrail below before you act on the output.

Why this prompt works

Sizing failures are process failures, and process is exactly what an LLM can interrogate safely — no market data needed, no advice given. Forcing vague habits into IF/THEN logic exposes the gaps while they're still hypothetical.

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Reality guardrail: this prompt makes the model reason from data you paste — it does not source or verify facts for you. Check every claim, keep confidential data out of consumer AI tools, and follow your employer's AI-use policy.

Frequently asked

When should I use this prompt?

You have sizing 'rules' you mostly follow. Find out where they break — in a conversation, not in a drawdown.

Why does this prompt work?

Sizing failures are process failures, and process is exactly what an LLM can interrogate safely — no market data needed, no advice given. Forcing vague habits into IF/THEN logic exposes the gaps while they're still hypothetical.

What mistake does this prompt help you avoid?

The 'how much should I buy' slide into advice — the prompt refuses sizing recommendations for real positions and teaches the principle instead.

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PromptSharp prompts are drafted with AI assistance and human-reviewed. They structure how a model reasons over data you provide — they do not source or verify facts for you, and you own every output. Nothing here is financial, legal, tax, or investment advice. Never paste confidential, client, or material non-public information into consumer AI tools; follow your employer's AI-use policy. © 2026 PromptSharp.