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Updated 2025-06-04·Editorial policy·Trading system

What is Edge?

Trading edge is a statistical or structural advantage that produces positive expectancy over many trades.

Formula

Edge = positive expectancy over many trades

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 shows up on Indian index, equity, and futures books — update to live quotes in your journal.

Nifty 50 perspective

Trading Edge on Nifty (24,300): backtest includes 9:15 liquidity and expiry-day behaviour; edge on index may vanish outside 10:00–14:30 window.

Reliance Industries perspective

Trading Edge on Reliance (₹1,300): liquidity is deep but event gaps dominate — strategy rules need explicit earnings blackout weeks.

Bank Nifty futures perspective

Trading Edge on Bank Nifty futures (55,000): high beta suits shorter holds; overnight trading edge must state NRML risk and gap plan in writing.

How to validate

  • Minimum sample: 30 closed trades on one strategy tag before trusting Edge.
  • Check for one outlier week inflating Edge — export largest winners and losers.
  • Recompute Edge after including brokerage, STT, and slippage on F&O tags.
  • Compare Edge on the same date range as profit factor and max drawdown.

How to track in TradeLyser

  • Open Strategy Board or analytics → filter by strategy tag and review period.
  • Locate the widget or column reporting Edge (or export trades to compute manually).
  • Store snapshot values in weekly review: Edge, profit factor, drawdown, trade count.
  • If Edge is custom, add a spreadsheet column fed from TradeLyser CSV export.

Best practices

  • Publish Edge per strategy, not only at account level.
  • Use the same calculation window (weekly vs monthly) year-round.
  • Pair Edge with sample size in every review slide or note.
  • Document formula used so mentors interpret the same number.

Common pitfalls

  • Changing rules after fewer than 20 trades because Edge moved slightly.
  • Mixing intraday and positional tags when computing Edge.
  • Ignoring costs so Edge looks better than banked P&L.
  • Letting one outlier trade dominate the Edge reading.

How to use this in TradeLyser

Compare expectancy and profit factor per tag quarterly; pause tags with negative net edge.

Related terms

FAQ

One good month proof of edge?

No — need sample across regimes and costs.

Edge vs luck in short samples?

Use R distribution and rule compliance grades to separate.

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