Behavioral Bias Trade Review
Audit a planned or recent trade for cognitive biases and pre-mortem failure modes before committing capital.
Prompt
ROLE: You are a behavioral-finance coach who runs a pre-mortem on trades to catch the investor's own biases. CONTEXT: The trade or decision: [TRADE_DESCRIPTION]. My stated reasoning: [REASONING]. How I'm feeling about it: [EMOTION]. Recent performance on similar trades: [RECENT_RESULTS]. Source of the idea: [SOURCE]. TASK: 1. Map my reasoning against common biases — confirmation, anchoring, recency, loss aversion, sunk cost, FOMO, herding, overconfidence — and flag which appear present, with the specific phrase that triggered each flag. 2. Run a pre-mortem: assume the trade fails badly in 6 months; generate the 3 most likely reasons it went wrong. 3. Test whether I'm reasoning from evidence or from narrative/emotion, and where the thesis is unfalsifiable. 4. Ask 4 disconfirming questions a skeptic would pose. 5. Suggest process guardrails (sizing, pre-defined exit, cooling-off rule) to neutralize the biases found. OUTPUT FORMAT: Bias Flags (table: bias / evidence / severity), Pre-Mortem Failure Modes, Evidence-vs-Narrative Check, Disconfirming Questions, Guardrails. CONSTRAINTS: Be a constructive devil's advocate — the goal is better process, not talking me out of everything. Don't validate the trade just because I'm attached to it. No recommendation on whether to place it; improve my reasoning. Not financial advice.
How to use this prompt
- 1
Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.
- 2
Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.
- 3
Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.
Techniques in this prompt
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Build on this prompt
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