What is Tag Taxonomy?
Tag taxonomy is the controlled vocabulary of labels used in a trading journal — naming conventions for setups, market regimes, mistakes, and session types. It prevents duplicate tags (ORB vs opening-range-breakout) from splitting one edge into false small samples.
What tag taxonomy includes
Layers: setup tags (entry logic), instrument tags (nifty-fut, bnfut, stock-fo), session tags (expiry-day, event-rbi), behavior tags (revenge, checklist-fail). Each layer answers different analytics questions.
Indian market context
Split index vs stock F&O; tag expiry-week separately; tag fno-ban trades; tag MIS vs NRML if product mix affects stats. NSE calendar events get standard event-* tags for cross-month filtering.
Maintain a merge map when renaming tags — old slug → new slug — and batch-update historical trades once per quarter. Parallel synonyms (orb, opening-range, orb-nifty) split sample size and fake weak edges in Strategy Board.
Cap active setup tags at what you actually trade: three to five playbooks is enough for most retail books. New tags earn a place only after a pilot sample with written rules — not after one good trade. Archive retired tags in the master doc instead of deleting history.
Worked example taxonomy excerpt
| Tag | Layer |
|---|---|
| orb-nifty-15m | Setup |
| index-bnfut | Instrument |
| expiry-day | Session |
| rule-break-size | Behavior |
Common mistakes
- New tag per trade instead of reusing playbook list.
- Over-granular tags with 3 trades each.
- No merge process — analytics noise grows.
- Behavior tags never reviewed in monthly audit.
- Using mood adjectives in setup tags instead of playbook slugs from the master taxonomy list.
How to validate
- Validate Tag Taxonomy with a written rule and at least 20 tagged examples.
- Ask whether the reading changed because of process or one outlier trade.
- Compare two independent time windows before adjusting position size.
- Document validation date in weekly review notes.
How to track in TradeLyser
- Mention Tag Taxonomy in trade comments when it influenced the decision.
- Mirror the term in weekly review questions for consistency.
- Filter trades mentioning the concept during monthly analytics.
- Cross-link to related glossary terms in mentor notes.
Best practices
- Teach Tag Taxonomy the same way to mentors and peers — shared vocabulary.
- Re-read this page after major rule changes to Tag Taxonomy usage.
- Prefer one improvement per month over ten simultaneous tweaks.
- Link learn articles when Tag Taxonomy needs deeper study.
Common pitfalls
- Using Tag Taxonomy buzzwords without measurable journal tags.
- Copying another trader’s Tag Taxonomy rule without sample size context.
- Skipping weekly review because the term feels “basic”.
- Letting social media redefine Tag Taxonomy mid-quarter.
How to use this in TradeLyser
Maintain master tag list in TradeLyser docs; when creating a tag, search synonyms first. Quarterly merge report in monthly review.
Reference guide
| Context | Value | Reading |
|---|---|---|
| Naming | Kebab-case stable slugs: orb-nifty-15m | Ten synonyms for same breakout setup |
| Governance | Merge map when adding new tag | Anyone on team adds tags without review |
Related terms
An edge audit is a structured review — typically monthly or quarterly — in which a trader examines the expectancy, win rate, and profit factor for each setup tag and strategy in their journal to confirm that a statistical edge is present, stable, or improving. It also identifies setups that have degraded and should be paused.
A journal template defines the standard fields captured for each trade and session — instrument, setup tag, entry/exit, stop, size, P&L, emotion grade, rule compliance, and notes. Templates enforce consistency so analytics remain comparable over months.
The sample size rule in trading is the principle that no meaningful conclusion should be drawn from the performance of a setup until it has at least 30 closed trades (for directional confidence) or 100 trades (for statistical robustness). Evaluating win rate or expectancy on fewer trades conflates luck with edge.
A setup tag is a user-defined label attached to each trade in a journal to identify the specific entry pattern or strategy used — for example, "VWAP Rejection", "Flag Breakout", or "OI Reversal". Consistent tagging allows traders to isolate the win rate, expectancy, and R-multiple for each distinct setup.
A strategy scorecard is a one-page summary of the core performance metrics for a specific trading strategy — including win rate, expectancy, profit factor, max drawdown, average R-multiple, and sample count. It enables side-by-side comparison of multiple strategies and quick identification of which deserve more capital allocation.
A trading journal is a systematic record of every trade a trader takes, documenting instrument, setup, entry and exit prices, position size, P&L, emotions, and rule adherence. It is the primary tool for identifying patterns, diagnosing mistakes, and proving whether an edge exists after costs on NSE and F&O books.
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FAQ
How many setup tags should I allow?
Start with 3–5 active setups; expand only when a new setup has 20+ pilot trades and distinct rules.
Tag taxonomy vs setup tag field?
Setup tag is one field; taxonomy is the governing list and rules for all tag types in the journal.
Rename old tags?
Merge in TradeLyser by mapping old → new and re-tagging historical trades once — avoid parallel synonyms going forward.
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