AI Trading Journal Workflow

Paper-first boundary

Trading Boy does not execute live trades, hold funds, or provide financial advice. This page is for simulated paper-trading review, prompt design, journal structure, and human review. It is not a signal feed, broker instruction, or promise of live trading results.

When to use this page

Use it when AI output, paper trades, and human notes need to become one reviewable journal process.

The search intent behind AI trading journal workflow for paper trades is usually practical: the user wants a reusable asset, an example, and a checklist. This page treats those variants as one owner page rather than splitting guide, example, checklist, and template into thin sibling pages.

Use the asset only after the paper-trading workflow, prompt version, permission boundary, and journal output format are clear. If the user cannot identify the setup, invalidation, risk field, or review question, the next action should be a skip, caveat, or human review rather than a confident simulated entry.

Journal workflow sequence

Review field	Pass condition	Paper-mode boundary
Before entry	Capture setup, thesis, invalidation, data freshness, and paper risk.	No complete pre-entry row means no clean sample.
During decision	Log the agent output in the required format.	The journal preserves the original reasoning.
After exit	Tag rule fit, behavior, and paper outcome separately.	Outcome does not rewrite the original thesis.
Weekly review	Group rows by rule, behavior, risk, and prompt version.	One review chooses one next action.
Version note	Record changed prompts, templates, and rules.	Comparisons stay fair across samples.

Reusable prompt or worksheet text

Role: You are helping organize a simulated paper-trading review. You may summarize context, apply written rules, identify missing fields, and prepare journal evidence. You may not route live trades, request secrets, or provide financial advice.

Required output: Decision type, setup name, rule version, thesis, invalidation, paper risk, data caveat, behavior tag, and one human review question.

Skip rule: If setup, invalidation, paper risk, or data quality is missing, produce a skip or excluded row. Do not invent the missing field to make the record look complete.

Review handoff: Send the output to the paper journal, evaluation checklist, or human review checklist. Choose one next paper-mode action: collect more samples, tighten one field, pause, or revert a prompt change.

Example paper workflow

Scenario: A trader runs the workflow for ten simulated decisions. Three are entries, four are skips, two are missed setups, and one is excluded for stale data. The weekly review learns more from the mix than from paper PnL alone.

Good output: The journal shows what happened before, during, and after each paper decision.

Weak output: The journal keeps only entry price and exit price with no thesis or behavior review.

Decision: The reviewer keeps the evidence in paper mode, checks the output with the AI paper trading agent evaluation checklist, and records any prompt change in AI trading agent prompt versioning.

Use it with these controls

Prompt version: every sample should name the version that produced the output.
Output format: the agent should use consistent fields for entries, exits, skips, and missed setups.
Risk gate: size, exposure, drawdown, stop distance, and pause rules should be checked before judging the idea.
Human review: a person should approve prompt, risk, or workflow changes before the next sample.
Data privacy: private exchange credentials, account identifiers, and secret values should stay out of prompts and screenshots.

How it supports ranking

This owner page consolidates the guide, example, template, checklist, and for-paper-trading variants into one durable page. That gives searchers a complete answer without flooding the sitemap with near duplicates.

It also links into the surrounding Trading Boy system: paper-trading hub, AI paper agent, prompt template, output format, risk controls, permission boundaries, and paper-trading limitations.

Related AI paper-agent pages

Use these links to move between setup, output, risk, journal, and review pages without leaving the paper-first cluster.

AI Trading Journal Workflow FAQ

What is an AI trading journal workflow?

It is a sequence for turning AI paper-agent output into structured journal rows and review actions.

Should skipped trades be included?

Yes. Skips show whether the agent respects incomplete setups, data caveats, and risk boundaries.

Can this workflow execute live trades?

No. It is a paper-trading workflow and does not execute live trades.