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Learning path Silver Repeatable method

Trade frequency

Number of trades over time — impacts costs, stress, sample size, and validation speed.

Who this is for — Anyone confusing activity with edge. Too many trades = costs + decision fatigue; too few = impossible validation.

Trade frequency is the number of plan trades in a period (day/week/month). Defines friction with slippage and fees and time to reach useful sample size.

In plain terms — How often you press the button — sweet spot between data and burnout.

TRADE FREQUENCY (CRUISE SPEED) POCHI DATI SWEET SPOT OVERTRADING 12 / Settimana Troppo lenti: la statistica non si consolida. Troppo veloci: lo spread e le commissioni divorano l'Edge.
Overtrading vs slow sample. Select a point to explore.

Trade-off

High frequency Low frequency
Fast sample size Lower cost %
Costs + slippage ↑ Years to validate
Decision fatigue FOMO «inactivity»

Scalping: small edge per trade — fees may erode it. Swing: few trades — statistical patience required.


Plan rules

  • Expected frequency target (e.g. 2–5 trades/week setup X)
  • Cap with max trades
  • Review: actual vs planned frequency

Typical mistake — Raising frequency in drawdown to «recover» — overtrading.

Example — H1 setup: ~8 trades/month; max 3/day; costs 0.15R/trade → break-even edge ≥ 0.2R/trade.

Summary card

  • Metric: trades / period.
  • Pair: costs + net expectancy.
  • Limit: max trades per session.

Silver path — Metrics module. Index: Silver path.