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Updated 2025-06-01·Reviewed by TradeLyser Editorial Team·Editorial policy·Trading system

What is Edge Audit?

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.

Indian market context (NSE)

Reference levels: Nifty 50 at 24,300, Reliance Industries at ₹1,300, Bank Nifty futures at 55,000 (lot size 30). Examples below show how Edge Audit shows up on Indian index, equity, and futures books — update to live quotes in your journal.

Nifty 50 perspective

Edge Audit in Indian context at Nifty 24,300: apply SEBI/regulatory framing where relevant and tag index trades separately in weekly review.

Reliance Industries perspective

Edge Audit using Reliance at ₹1,300 as a liquid large-cap example — adjust numbers to your live quote and contract note.

Bank Nifty futures perspective

Edge Audit with Bank Nifty futures at 55,000 — respect lot size 30 and quarterly vs monthly contract rules on NSE.

How to validate

  • Validate Edge Audit 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 Edge Audit 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 Edge Audit the same way to mentors and peers — shared vocabulary.
  • Re-read this page after major rule changes to Edge Audit usage.
  • Prefer one improvement per month over ten simultaneous tweaks.
  • Link learn articles when Edge Audit needs deeper study.

Common pitfalls

  • Using Edge Audit buzzwords without measurable journal tags.
  • Copying another trader’s Edge Audit rule without sample size context.
  • Skipping weekly review because the term feels “basic”.
  • Letting social media redefine Edge Audit mid-quarter.

Reference guide

ContextValueReading
Audit frequencyMonthly audit with 30+ trades per setupNever auditing — trading a dead strategy without knowing it

Related terms

Expectancy
Metrics

Expectancy answers whether your edge pays each time you repeat the setup. Positive expectancy means the system earns over many trades; negative expectancy means it bleeds even with a high win rate.

Monthly Review
General

Monthly review is a periodic deep audit — typically 60–90 minutes — that examines aggregated journal metrics: expectancy, profit factor, drawdown, rule-break rate, and setup-level performance across a calendar month or ~20 trading sessions.

Profit Factor
Metrics

Profit factor summarises whether total winning rupees outweigh total losing rupees over a window. Below 1.0 means net losing; above 1.0 means net winning before you judge consistency.

Sample Size Rule
General

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.

Strategy Scorecard
General

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.

Tag Taxonomy
General

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.

FAQ

How many trades do I need before an edge audit is meaningful?

You need at least 30 closed trades per setup for the statistics to be directionally reliable, and 100+ for statistically robust conclusions. An edge audit on 10 trades is anecdotal. TradeLyser shows a confidence indicator alongside expectancy to signal when sample size is too small.

What should I do if my edge audit shows no edge?

First, check whether the degradation is recent (last 30 trades) or long-term (all trades). If recent, it may be a drawdown phase — continue paper trading or reduced size. If long-term, the setup logic may be flawed or market conditions have changed. Document findings and reduce or pause size until a re-test period shows improvement.

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