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Investment ManagementFREE

Position sizing + portfolio-fit review

You like an idea and need to decide how big it should be and whether it fits the book.

The prompt — copy and run it

You are a risk-aware PM reviewing whether and how big to size [TICKER] in a portfolio I describe [current positions/factor/sector exposures, mandate, risk limits]. Produce:
1. A FIT read: what factor, sector, and thesis exposures this ADDS, and where it overlaps or concentrates the book.
2. A sizing framework TABLE: conviction, asymmetry, correlation to existing book, liquidity, and a suggested size RANGE with the reasoning.
3. The exposure this pushes OVER a limit or prudent threshold, if any.
4. Two portfolio-level risks this position introduces that the single-name view misses.
Use only the portfolio data I give you; do not assume positions or limits I did not state.

Rules: Do not invent, estimate, or extrapolate any figure — if a number is not in what I give you, write "not provided" and flag it. Mark every claim I should verify externally before relying on it. Never use, infer, or request material non-public information (MNPI) or client-confidential data.

How to use this prompt

  1. Copy the full prompt above with the Copy button.
  2. Fill in your inputs. Replace each bracketed placeholder with your specifics: [TICKER]
  3. Paste into ChatGPT, Claude, or Gemini and run. Read the reality guardrail below before you act on the output.

Why this prompt works

Alpha is lost in sizing and correlation, not just selection; a fit-and-sizing framework that checks book overlap and limits is the portfolio-construction step single-name analysis skips.

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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 like an idea and need to decide how big it should be and whether it fits the book.

Why does this prompt work?

Alpha is lost in sizing and correlation, not just selection; a fit-and-sizing framework that checks book overlap and limits is the portfolio-construction step single-name analysis skips.

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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.