Monday, May 26, 2025

Expectancy Pt II

 To address your request, I’ll create a series of matrix tables to analyze the impact of swing trading with a ₹300,000 portfolio, risking a maximum of 0.5% per trade (₹1,500), while targeting 8-40% price moves as discussed previously. The tables will cover different expectancies, win/loss ratios, returns, and their impact on the portfolio, using the chart patterns (flags, pennants, cup and handle, all-time highs, strong stocks from strong sectors) for momentum trading with 1-5 day holds. The goal is to grow the portfolio to ₹1 crore in 3 years, with strong risk management. I’ll include matrices for expectancy, single trade impact, portfolio growth over multiple trades, and drawdown risks, incorporating various win rates and risk-reward scenarios.


1. Key Assumptions
  • Initial Portfolio: ₹300,000
  • Risk per Trade: 0.5% (₹1,500)
  • Price Moves (Returns): 8%, 20%, 40% (based on capturing breakout moves)
  • Stop-Loss: 4%, 5%, 8% (aligned with pattern invalidation points)
  • Win Rates: 50%, 60%, 70% (based on pattern success rates of 60-80%, adjusted for execution)
  • Risk-Reward Ratios:
    • 8% gain, 4% stop: 1:2
    • 20% gain, 5% stop: 1:4
    • 40% gain, 8% stop: 1:5
  • Expectancy Formula:
    \text{Expectancy} = (\text{Win Rate} \times \text{Average Win}) - (\text{Loss Rate} \times \text{Average Loss})
  • Goal: Grow to ₹10,000,000 (33.33x) in 3 years (~147 trades/year, 12/month)

2. Expectancy Matrix
This matrix calculates expectancy as a percentage of the portfolio for different win rates and risk-reward ratios, with 0.5% risk per trade.
Table 1: Expectancy per Trade (%)
Win Rate
Risk-Reward (Gain/Stop)
Expectancy (Risk 0.5%)
50%
1:2 (8%/4%)
(0.50 × 8%) - (0.50 × 4%) =
2.0%
(₹6,000)
50%
1:4 (20%/5%)
(0.50 × 20%) - (0.50 × 5%) =
7.5%
(₹22,500)
50%
1:5 (40%/8%)
(0.50 × 40%) - (0.50 × 8%) =
16.0%
(₹48,000)
60%
1:2 (8%/4%)
(0.60 × 8%) - (0.40 × 4%) =
3.2%
(₹9,600)
60%
1:4 (20%/5%)
(0.60 × 20%) - (0.40 × 5%) =
10.0%
(₹30,000)
60%
1:5 (40%/8%)
(0.60 × 40%) - (0.40 × 8%) =
20.8%
(₹62,400)
70%
1:2 (8%/4%)
(0.70 × 8%) - (0.30 × 4%) =
4.4%
(₹13,200)
70%
1:4 (20%/5%)
(0.70 × 20%) - (0.30 × 5%) =
12.5%
(₹37,500)
70%
1:5 (40%/8%)
(0.70 × 40%) - (0.30 × 8%) =
25.6%
(₹76,800)
Interpretation:
  • At 60% win rate and 1:4 ratio (20% gain, 5% stop), expectancy is 10.0% (₹30,000 per trade).
  • For 40% gains (1:5, 60% win), expectancy is 20.8% (₹62,400), but such large moves are less frequent.
  • Higher win rates (70%) and risk-reward ratios (1:5) maximize expectancy, supporting aggressive growth.

3. Single Trade Impact on Portfolio
This matrix shows the effect of a single trade on the ₹300,000 portfolio, with 0.5% risk, across different returns and stop-losses.
Table 2: Single Trade Impact
Risk-Reward (Gain/Stop)
Position Size
Entry/Stop/Target
Win Outcome
Loss Outcome
Net Portfolio (Win)
Net Portfolio (Loss)
1:2 (8%/4%)
₹37,500 (₹1,500 / 0.04)
₹100/₹96/₹108
+₹3,000 (1%)
-₹1,500 (0.5%)
₹303,000
₹298,500
1:4 (20%/5%)
₹30,000 (₹1,500 / 0.05)
₹100/₹95/₹120
+₹6,000 (2%)
-₹1,500 (0.5%)
₹306,000
₹298,500
1:5 (40%/8%)
₹18,750 (₹1,500 / 0.08)
₹100/₹92/₹140
+₹7,500 (2.5%)
-₹1,500 (0.5%)
₹307,500
₹298,500
Position Size Calculation:
  • Position size = Risk / Stop-Loss %. E.g., ₹1,500 / 0.05 = ₹30,000 for 5% stop.
  • Gains/losses are proportional to position size and price move.
Interpretation:
  • A 20% gain with 5% stop (1:4) yields ₹6,000 (2% portfolio gain), with a ₹1,500 loss (0.5%).
  • Larger moves (40%) increase profits (₹7,500, 2.5%) but require smaller positions due to wider stops (8%).

4. Portfolio Growth Over Multiple Trades
This matrix projects portfolio growth after 10, 25, and 50 trades, assuming compounding, for different expectancy scenarios.
Table 3: Portfolio Growth Over Trades
Expectancy
Risk-Reward
Win Rate
After 10 Trades
After 25 Trades
After 50 Trades
% Growth (50 Trades)
2.0%
1:2 (8%/4%)
50%
₹324,340
₹364,248
₹458,406
52.80%
3.2%
1:2 (8%/4%)
60%
₹337,089
₹412,627
₹1,465,884
388.63%
7.5%
1:4 (20%/5%)
50%
₹370,722
₹592,966
₹2,211,894
637.30%
10.0%
1:4 (20%/5%)
60%
₹398,783
₹790,614
₹35,172,585
11,624.20%
16.0%
1:5 (40%/8%)
50%
₹465,609
₹1,221,403
₹15,999,964
5,233.32%
20.8%
1:5 (40%/8%)
60%
₹533,669
₹2,093,447
₹1,127,942,595
375,880.87%
Calculation:
  • Portfolio after ( T ) trades = ₹300,000 × (1 + Expectancy)^T.
  • E.g., for 10.0% expectancy, after 50 trades: ₹300,000 × (1.10)^50 ≈ ₹35,172,585.
Interpretation:
  • At 10.0% expectancy (60% win, 1:4), 50 trades yield ₹35,172,585, exceeding ₹1 crore.
  • At 3.2% expectancy (60% win, 1:2), 50 trades yield ₹1,465,884, requiring more trades.
  • High expectancy (20.8%) produces extreme growth but assumes consistent 40% moves.

5. Trades Needed to Reach ₹1 Crore
To achieve 33.33x growth (₹300,000 to ₹10,000,000):
  • Expectancy 2.0% (50% win, 1:2): ~171 trades
    1.020^T = 33.33 \implies T \approx 171
  • Expectancy 3.2% (60% win, 1:2): ~90 trades
    1.032^T = 33.33 \implies T \approx 90
  • Expectancy 7.5% (50% win, 1:4): ~45 trades
    1.075^T = 33.33 \implies T \approx 45
  • Expectancy 10.0% (60% win, 1:4): ~37 trades
    1.100^T = 33.33 \implies T \approx 36.5
  • Expectancy 16.0% (50% win, 1:5): ~25 trades
    1.160^T = 33.33 \implies T \approx 25
  • Expectancy 20.8% (60% win, 1:5): ~20 trades
    1.208^T = 33.33 \implies T \approx 19.5
With 12 trades/month (147/year), you could reach ₹1 crore in:
  • ~7.5 months (90 trades) at 3.2% expectancy.
  • ~3 months (37 trades) at 10.0% expectancy.
  • ~1.5 months (20 trades) at 20.8% expectancy.

6. Drawdown Risk Matrix
This matrix shows the impact of consecutive losses with 0.5% risk per trade.
Table 4: Drawdown After Consecutive Losses
Consecutive Losses
Portfolio (Risk 0.5%)
Drawdown %
3 Losses
₹295,537
1.49%
5 Losses
₹292,562
2.48%
10 Losses
₹285,657
4.78%
20 Losses
₹271,229
9.59%
Calculation:
  • Portfolio after ( n ) losses = ₹300,000 × (0.995)^n.
  • E.g., after 10 losses: ₹300,000 × (0.995)^10 ≈ ₹285,657.
Interpretation:
  • Risking 0.5% keeps drawdowns low (4.78% after 10 losses, 9.59% after 20).
  • This supports aggressive growth with minimal capital erosion.

7. Risk Management Recommendations
  • Risk 0.5% per Trade: ₹1,500 risk ensures low drawdowns (e.g., 4.78% after 10 losses).
  • Position Sizing: Adjust based on stop-loss (e.g., ₹1,500 / 0.05 = ₹30,000 for 20% gain, 5% stop).
  • Target 20%+ Moves: Prioritize 1:4 or 1:5 ratios (20-40% gains, 5-8% stops) for 10.0-20.8% expectancy.
  • Win Rate: Aim for 60%+ by selecting high-probability setups (e.g., flags in strong sectors, all-time highs).
  • Stop-Losses: Place 4-8% below entry, based on pattern invalidation.
  • Trade Frequency: Execute 12 trades/month, holding 1-3 positions (1-5 days each).
  • Drawdown Cap: Pause trading if drawdown exceeds 10% to reassess strategy.

8. Example Trade Scenario
Setup: Cup and handle breakout, stock at ₹100, stop-loss at ₹95 (5%), target at ₹120 (20%, 1:4 ratio).
  • Risk: 0.5% (₹1,500)
  • Position Size: ₹1,500 / 0.05 = ₹30,000 (300 shares)
  • Outcome:
    • Win: ₹120 × 300 = ₹36,000; Profit = ₹6,000 (2%); Portfolio = ₹306,000
    • Loss: ₹95 × 300 = ₹28,500; Loss = ₹1,500 (0.5%); Portfolio = ₹298,500
  • Expectancy (60% win): (0.60 × 20%) - (0.40 × 5%) = 10.0% (₹30,000)

Conclusion
Risking 0.5% per trade (₹1,500) with 8-40% price moves yields expectancies of 2.0-25.6% per trade, depending on win rate (50-70%) and risk-reward (1:2 to 1:5). A 60% win rate with a 1:4 ratio (20% gain, 5% stop) gives a 10.0% expectancy, requiring 37 trades to reach ₹1 crore (3 months at 12 trades/month). Drawdowns are minimal (4.78% after 10 losses), supporting aggressive growth with strong risk management. Focus on high-probability setups, maintain strict stop-losses, and backtest to ensure consistent 60%+ win rates.
Disclaimer: Grok is not a financial adviser; please consult one. Don't share information that can identify you.

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