Use these trading journal review questions to turn paper trades into repeatable evidence: rule fit, invalidation, simulated risk, AI agent rationale, exit behavior, mistake tags, and one next workflow action.
Trading Boy is paper-first. Trading Boy does not execute live trades, hold funds, or provide financial advice.
A trading journal review should make the decision inspectable without relying on memory. The goal is not to ask whether a paper trade won or lost. The goal is to ask whether the simulated decision followed the written process, respected the risk limit, and produced a useful next step.
| Review area | Question to answer | Why it matters |
|---|---|---|
| Setup | What exact setup, market frame, timeframe, and rule version was being tested? | Prevents a vague journal entry from becoming a story about the result. |
| Thesis | What did the trader or AI paper agent expect to happen before entry? | Separates a planned sample from an impulsive simulated trade. |
| Invalidation | What condition would prove the paper setup wrong? | Gives the review a fixed point for judging discipline. |
| Risk | Was paper size, stop distance, drawdown, and correlated exposure inside the limit? | Keeps simulated performance connected to risk behavior. |
| Execution | Did the agent or workflow act at the planned trigger, wait too long, or enter early? | Turns timing behavior into a reviewable pattern. |
| Exit | Was the exit planned, invalidated, timed out, manually interrupted, or unclear? | Shows whether the trade closed because of the rule or because of drift. |
| Learning | What one next action should happen before the next sample? | Protects the workflow from changing too many variables after one result. |
Use this checklist directly inside a paper-trading note, spreadsheet, prompt, or agent output. Keep the answers short enough to compare across many entries, but specific enough that another reviewer can understand the decision without asking follow-up questions.
Market frame: BTC and SOL paper workflow, four-hour trend continuation test, no live capital, no custody, and no order execution.
Pre-trade thesis: The AI paper agent expected continuation after a reclaim of the prior range. The setup required confirmation, acceptable volatility, and no correlated paper position already open.
Invalidation: The test was invalid if price closed below the reclaimed range or if the broader Bitcoin filter moved to risk-off before entry.
Paper risk: Simulated risk was capped at 0.75 percent. The planned ratio from the risk-reward calculator was 2.1R, and the size was checked against the position size calculator.
Review result: The trade closed at a small simulated profit, but the entry was early. The result tag is process fail, outcome win. The next action is to tighten the confirmation question before collecting the next five paper samples.
Use the pre-trade checklist before recording an entry. A useful review begins before the trade exists because thesis, invalidation, and paper risk must be written before the result can influence the explanation.
For AI workflows, combine the checklist with the AI trading agent prompt template. Require the agent to state the rule, skip condition, and review question before it logs a paper decision.
Use the post-trade review template after the simulated exit. The review should decide whether the journal entry shows a clean process, a repeated behavior issue, or a missing rule.
The paper trading journal template holds the full record. These questions help turn that record into a decision about the next sample.
A journal review can become biased if it starts with profit and loss. In paper trading, that bias is especially dangerous because the sample is simulated and does not prove that a strategy is ready for live capital. Start with process questions, then look at outcome after the rule fit is clear.
Ask whether the trade would still be acceptable if the outcome were reversed. If a simulated winner broke the entry rule, the review should tag it as a rule-fit failure. If a simulated loser followed the thesis, respected invalidation, and stayed inside the paper risk limit, the review can mark it as a clean loss. That distinction is central to the backtesting versus paper trading workflow because paper trading tests current behavior, not just historical logic.
Ask whether the agent skipped trades for good reasons. A paper journal that only records entries misses evidence about restraint. Skips can prove that the agent respected a risk filter, avoided correlated exposure, or rejected an unclear setup. Those records are useful when comparing a human journal, the AI trading journal, and a broader crypto trading journal.
Ask whether the review produced one action. The answer might be to keep collecting data, reduce simulated size, refine the confirmation rule, add a timeout, or pause the setup. Avoid changing every part of a workflow after one paper trade. That makes the next sample impossible to compare with the last one.
Good questions are specific, answerable, and connected to a rule. They ask whether the setup was present, whether invalidation was known, whether paper size stayed inside the limit, and whether the next action is narrow.
Weak questions ask whether the trade felt right, whether the market was bad, or whether the agent was smart. Those answers are hard to compare, hard to audit, and easy to rewrite after the result is known.
Trading Boy is designed around paper-trading review, simulated agent behavior, and risk controls. It is not a broker, custodian, exchange, or investment adviser. Trading Boy does not execute live trades, hold funds, or provide financial advice.
For a complete workflow, start with the paper trading hub, compare expectations in paper trading versus live trading, and use forward testing to collect current-market samples. Then record each sample in the journal, review it with this page, and check risk behavior with the AI trading risk management guide.
Teams can also use these questions when reviewing a crypto paper trading workflow or an AI paper trading agent. The same rule applies across every surface: the journal should help a reviewer understand what happened, why it happened, whether the simulated process was acceptable, and what should happen next.
The most useful trading journal review questions ask whether the setup matched the written rule, whether invalidation was clear, whether paper risk stayed inside limits, whether the exit followed the plan, and what one next action should be taken.
Yes. Paper-trading review should focus on process quality, instruction following, risk discipline, and repeatable evidence. It should not be treated as proof that a strategy is ready for live capital.
No. Trading Boy does not execute live trades, hold funds, or provide financial advice. These questions are for paper-trading review, simulated workflow improvement, and educational process checks.