Step 1: Assign numbers for 100 trades
40 trades → pay spread/commission only, assume C = 0.05R → loss 0.05R each
30 trades → lose 1R each
15 trades → gain 0.2R each
15 trades → gain big wins, average 6R each
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Step 2: Calculate total
1️⃣ Cost-only trades:
40 × -0.05 = -2.0R
2️⃣ Losing trades:
30 × -1 = -30R
3️⃣ Small wins:
15 × 0.2 = 3R
4️⃣ Big wins:
15 × 6 = 90R
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Step 3: Sum all outcomes
"Net R"=-2-30+3+90=61R
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Step 4: Per trade expectancy
"Expectancy per trade"=61/100=0.61R
✅ Matches our earlier analytical calculation.
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Step 5: Interpretation
Total profit over 100 trades: +61R
Average per trade: +0.61R
Drawdown risk: 30 losing trades can hit 30R, but 15 big winners (average 6R each) cover this easily.
Key insight: A small fraction of big wins drives profitability; the system is highly asymmetric but mathematically strong.
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Step 6: Updated plan – 100+ trades/month across multiple currencies
Assumptions
Account = $10,000
1R = 1% of account = $100 per trade
Expectancy per trade = 0.61R = $61
Number of trades per month = 100 (can scale for 100+ later)
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Step 7: Monthly profit estimate
"Profit/month"=100×61=$6,100
"Percentage gain"=(6,100)/(10,000)×100=61%
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Step 8: Scaling for more trades
120 trades/month → $61 × 120 = $7,320 → 73.2%
150 trades/month → $61 × 150 = $9,150 → 91.5%
Note: Profit scales linearly if expectancy remains the same, but volatility also increases.
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Step 9: Risk & volatility
More trades → more frequent small losses (30% losing + 40% cost trades), but big wins dominate.
Higher trade count → reduces luck variance; average $/R is more reliable.
Multiple currencies → slightly increases risk due to correlation; adjust position sizing per pair.
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Step 10: Key insight
Trades/month Expected profit ($) % gain
100 6,100 61%
120 7,320 73%
150 9,150 91.5%
✅ Mathematically, trading 100+ trades/month with your system on a $10K account can produce $6K–$9K monthly, assuming distribution holds and R-risk is 1% per trade.