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
Backtesting applies strategy rules to past data to estimate performance — subject to bias.
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.
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.
Win rate is the share of your closed trades that closed in profit after costs. It tells you how often you are right — not how much you make when you are wrong.
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.
Start journaling with
TradeLyser
Connect your broker, tag strategies, and review performance with AI-assisted insights.