What is Scaling In?

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

Nifty 50 perspective

Scaling In 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

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

Bank Nifty futures perspective

Scaling In on Bank Nifty futures (55,000): high beta suits shorter holds; overnight scaling in must state NRML risk and gap plan in writing.

How to validate

• Validate Scaling In only after costs — gross win rate can hide negative expectancy.
• Use walk-forward windows (e.g. last 60 / prior 60 trades) for stability.
• Retire or refactor the tag if Scaling In expectancy turns negative with 50+ trades.
• Ensure no overlapping tags duplicate the same trades.

How to track in TradeLyser

• Define Scaling In in Strategy Board with entry/exit/skip criteria.
• Enforce single-tag discipline — no secondary discretionary entries.
• Review expectancy, win rate, and avg R monthly on the tag only.
• Archive tag version when rules change; do not blend old and new trades.

Best practices

• One playbook page per Scaling In strategy with non-negotiable rules.
• Paper trade rule changes for two weeks before live size.
• Track costs explicitly on high-frequency Scaling In variants.
• Compare versioned tags after each rule amendment.

Common pitfalls

• Adding discretionary trades under the Scaling In tag.
• Scaling up after one lucky week of Scaling In results.
• Ignoring brokerage drag on high-frequency variants.
• Retiring a tag without exporting final statistics.

How to use this in TradeLyser

Define max adds and spacing in plan; log each leg with shared setup ID.