Portfolio Construction: Building an Edge-Based System
Your edge isn't in ONE great trade—it's in how you allocate capital across HUNDREDS of trades.
Professional traders don't just find good setups. They build portfolios that maximize expected returns while controlling risk. This lesson teaches you how to construct a portfolio like an institutional fund manager.
🎯 What You'll Learn
By the end of this lesson, you'll be able to:
- Calculate Kelly Criterion position size for any trading strategy
- Understand why full Kelly is dangerous (and what fractional Kelly to use)
- Build multi-strategy portfolios with proper correlation adjustments
- Implement dynamic position sizing based on equity curve performance
- Use Signal Pilot tools to validate edge and optimize allocations
⚡ Quick Wins for Tomorrow (Click to expand)
Start with these 3 actions:
- Calculate Kelly % for your best strategy. Need 3 numbers: (1) Win rate (wins ÷ total), (2) Avg winner, (3) Avg loser. Formula: Kelly % = (WR × (AvgW ÷ AvgL) - (1-WR)) ÷ (AvgW ÷ AvgL). Example: 58.3% WR, $360 avg win, $200 avg loss = 35.1% full Kelly. Use 1/4 Kelly = 8.8% per trade. Ed Thorp used Kelly to turn $10K into $800M.
- Implement equity curve position sizing. Calculate 20-day MA of equity. Above MA = increase size 25% (hot streak). Below MA = decrease 50% (cold streak). Prevents revenge trading, maximizes winners. Paul Tudor Jones: "Risk more when winning, less when losing."
- Run Kelly stress test on worst losing streak. Find worst consecutive losses (say 7). Calculate: 2% risk = -14% DD. Full Kelly 20% = -79% DD (account destroyed). Quarter Kelly 5% = -30% DD (recoverable). Full Kelly WILL destroy you. Use quarter Kelly.
💰 How Kelly Criterion Saved a $500K Account
Prop trader: 58% WR, $450 avg win, $300 avg loss. Old (2% fixed): +$140K/year, Sharpe 1.2, 15% DD. Optimization: Kelly = 29.7%, used half Kelly (3% per trade). New (3% Kelly): +$238K/year (+70% more), Sharpe 1.4, 18% DD. Kelly optimizes sizing based on edge: 70% more profit for only 3% more drawdown.
📉 CASE STUDY: Lisa's $91,000 Full Kelly Disaster
Setup: Lisa Chang, options trader with 68% WR credit spreads (avg win $840, avg loss $400, 2.1:1 R:R). Calculated full Kelly = 16.8% per trade. $185K account, Apr-Jun 2024.
The disaster: Weeks 1-2: +$7.5K profit using full Kelly. Week 3: Hit 6-trade losing streak (0.1% probability). Each loss -16.8% compounding = -62% drawdown. Account dropped $192K → $72K in ONE WEEK. Final: $94K (-$91K, -49% total loss in 3 months).
Recovery: Switched to 1/4 Kelly (4.2% per trade). Results: $94K → $147K (+56%) in 6 months, max DD -12% (vs -62%). Same edge, survivable variance.
Lesson: Full Kelly = theoretical optimum, catastrophic variance. Use 1/4 Kelly for 95% of growth with 12% drawdowns instead of 62%. Calculate full Kelly, then USE 25-50% of that number. Growth means nothing if variance destroys you first.
Case Study Quiz: Lisa had a profitable strategy (68% win rate, 2.1:1 R:R) and calculated her optimal Kelly Criterion as 16.8% per trade. She used FULL Kelly and lost $91K (-49%) in 3 months despite having positive edge. What was her fatal mistake?
The Single-Strategy Trap
Most retail traders optimize for ONE perfect setup. They spend months backtesting a breakout strategy, achieve 55% win rate with 2:1 R:R, and think they've "made it."
The problem: Single-strategy traders are one market regime change away from blowing up.
📉 Real Example: The Breakout Trader Who Lost 32% in One Month
Setup: Trader had a proven momentum breakout system. 2022 results: 58% win rate, $580 avg win, $320 avg loss. Made $47K on $150K account (+31% return).
January 2023: Fed pivots hawkish. Market shifts from trending (breakouts work) to choppy range-bound (breakouts fail).
Result: Win rate dropped from 58% to 38% in 4 weeks. Lost -$48K (-32% of account) because he had ZERO mean-reversion strategies to capitalize on the new regime.
Lesson: One strategy = one point of failure. Institutions run 5-15 uncorrelated strategies to survive regime changes.
The Three Pillars of Portfolio Construction
Professional portfolio construction rests on three pillars:
| Pillar | Retail Approach | Institutional Approach |
|---|---|---|
| 1. Diversification | One "perfect" strategy | 5-10 strategies across regimes (trend, mean-reversion, volatility, correlation) |
| 2. Position Sizing | Fixed 1-2% per trade (ignores edge) | Kelly Criterion adjusted for edge strength (5-15% for proven edges) |
| 3. Correlation Management | Ignored (all strategies correlated) | Reduce allocation to correlated strategies (avoid doubling down on same bet) |
Edge-Based Allocation vs Equal Weighting
Equal weighting: Allocate same % to each strategy (e.g., 3 strategies = 33% each)
Edge-based allocation (Kelly): Allocate MORE to strategies with stronger edge, LESS to weaker edges
Example: Why Equal Weighting Leaves Money on the Table
3 strategies: A (65% WR, Kelly 26.7%), B (52% WR, Kelly 14.4%), C (48% WR, Kelly 8.5%). Equal weight: 33% each = over-allocate to weak C, under-allocate to strong A. Result: +18.2% return, 22% DD. Kelly weight: 26.7%/14.4%/8.5% = optimal allocation by edge. Result: +26.8% return (+47% more!), 19% DD. Allocate based on edge, not equality.
Building for Regime Resilience
Markets cycle through four primary regimes. Your portfolio should have strategies for each:
| Regime | Characteristics | Strategy Types That Work |
|---|---|---|
| Trending Bull | Higher highs, low volatility, QE environment | Momentum breakouts, pullback buying, BTFD strategies |
| Trending Bear | Lower lows, rising volatility, QT environment | Breakdown shorts, rally fades, put spreads |
| Range-Bound | Choppy, oscillating between support/resistance | Mean reversion, support/resistance trades, theta decay (options selling) |
| High Volatility | VIX > 25, whipsaw moves, uncertainty | Volatility selling (after spikes), wide stop strategies, reduced size |
💡 Pro Tip: The "2-2-1" Portfolio Structure
Institutions often use a "2-2-1" diversification model:
- 2 Trend strategies (long bias and short bias) — capitalize on directional moves
- 2 Mean-reversion strategies (support bounces and resistance fades) — profit from ranges
- 1 Volatility strategy (VIX spike trading or premium selling) — hedge against chaos
This ensures you have exposure to multiple regimes simultaneously. When trends die, mean-reversion activates. When volatility explodes, volatility strategy hedges the others.
What Is Kelly Criterion?
The Kelly Criterion is a mathematical formula that answers one question: "Given my edge (win rate and reward/risk ratio), what percentage of my account should I risk per trade to maximize long-term compound growth?"
Developed by John Kelly Jr. at Bell Labs in 1956, it's been used by:
- Ed Thorp: Beat blackjack casinos, then turned $10K into $800M hedge fund (Princeton Newport Partners)
- Warren Buffett & Charlie Munger: Use Kelly to size Berkshire Hathaway positions
- Renaissance Technologies: Jim Simons' $130B quant fund uses Kelly-based position sizing
The Kelly Formula (Simplified)
Kelly % = (Win Rate × Avg Win - Loss Rate × Avg Loss) / Avg Win
Or, in mathematical notation:
f* = (p × b - q) / b
Where:
- f* = Optimal fraction of capital to risk (Kelly %)
- p = Win rate (probability of winning)
- q = Loss rate (1 - p)
- b = Win/Loss ratio (Avg Win / Avg Loss)
Step-by-Step Kelly Calculation
Example: 60% win rate, $500 avg win, $300 avg loss. Variables: p = 0.60, q = 0.40, b = $500/$300 = 1.67. Formula: f* = (0.60 × 1.67 - 0.40) / 1.67 = 0.60 / 1.67 = 0.359 = 35.9% full Kelly. Use Quarter Kelly: 35.9% / 4 = 9% per trade.
✅ What This Means in Practice
With a $100,000 account and this 60% win rate system:
- Full Kelly (35.9%): Risk $35,900 per trade — suicidal (one bad week destroys account)
- Quarter Kelly (9%): Risk $9,000 per trade — optimal balance of growth and survival
- Typical 1-2% sizing: Risk $1,000-$2,000 per trade — safe but leaves massive edge on the table
Key insight: If you have a PROVEN 60% win rate with 1.67:1 R:R, risking only 1-2% is under-utilizing your edge. Kelly says you can safely risk 8-9% and achieve far higher compound growth.
Why Full Kelly Is Dangerous (The Variance Problem)
Full Kelly optimizes for maximum geometric growth but ignores psychological survival.
The math problem: Even with a 60% win rate, you WILL hit losing streaks. Probability of 5 consecutive losses:
0.40^5 = 0.01024 = 1.024%
Translation: With 100 trades per year, you'll hit a 5-trade losing streak roughly once per year.
| Kelly Fraction | Risk Per Trade | Loss After 5-Trade Streak | Recovery Needed |
|---|---|---|---|
| Full Kelly (35.9%) | $35,900 | -81.7% (account at $18,300) | +546% to break even (impossible) |
| Half Kelly (18%) | $18,000 | -59.8% (account at $40,200) | +149% to break even (very hard) |
| Quarter Kelly (9%) | $9,000 | -37.2% (account at $62,800) | +59% to break even (achievable) |
| Fixed 2% | $2,000 | -9.6% (account at $90,400) | +11% to break even (easy, but slow growth) |
Conclusion: Quarter Kelly gives you 75% of optimal growth with manageable drawdowns. Full Kelly gives you maximum growth with account-destroying drawdowns.
Why Ed Thorp Used Fractional Kelly
Ed Thorp (mathematician who beat blackjack, 20% annual return for 30 years): "Full Kelly maximizes growth but causes very large drawdowns. Half Kelly or less gave nearly the same growth with much smaller swings. Psychological benefit of smaller drawdowns far outweighed tiny loss in compound growth." Rule: Use 25-50% of Kelly for real trading.
Multi-Strategy Portfolio Allocation
Real portfolios don't have just one strategy. You might run momentum breakouts, mean-reversion trades, and options income simultaneously.
The question: How do you allocate capital across multiple strategies with different edges?
Step 1: Calculate Kelly % for Each Strategy Independently
Example portfolio with 3 strategies:
| Strategy | Win Rate | Avg Win | Avg Loss | Win/Loss Ratio | Full Kelly % | Quarter Kelly % |
|---|---|---|---|---|---|---|
| A: Breakouts | 45% | $600 | $200 | 3.0 | 26.7% | 6.7% |
| B: Mean Rev | 65% | $300 | $250 | 1.2 | 35.8% | 8.95% |
| C: Volatility | 55% | $450 | $350 | 1.29 | 20.2% | 5.05% |
Total allocation (if strategies were independent): 6.7% + 8.95% + 5.05% = 20.7%
Step 2: Adjust for Correlation
The problem: If your strategies are correlated (win/lose together), you're effectively making the same bet multiple times.
Correlation coefficient ranges from -1 to +1:
- +1.0: Perfect correlation (always move together) — same strategy, don't double allocation
- +0.6 to +0.8: High correlation (often move together) — reduce allocation by 30-50%
- +0.2 to +0.4: Low correlation (somewhat independent) — reduce allocation by 10-20%
- 0.0: No correlation (truly independent) — no adjustment needed
- -0.5 to -1.0: Negative correlation (move opposite) — can increase total allocation (hedged)
How to Calculate Strategy Correlation (Excel/Python)
Excel: Export daily P&L to columns (Date, Strategy A, Strategy B). Use =CORREL(B:B, C:C) for correlation coefficient.
Python: df[['Strategy_A', 'Strategy_B']].corr() gives correlation matrix.
Interpretation: 0.15 = nearly independent ✅. 0.60 = high overlap ⚠️ (reduce allocation). 0.05 = independent ✅.
Step 3: Apply Correlation Adjustment
Continuing our 3-strategy example, assume these correlations:
- Strategy A & B: 0.15 (low correlation)
- Strategy B & C: 0.60 (high correlation) ⚠️
- Strategy A & C: 0.05 (independent)
Adjustment rule: Reduce allocation to correlated pairs by 30% (for 0.60 correlation)
| Strategy | Quarter Kelly % | Correlation Issue | Adjusted Allocation |
|---|---|---|---|
| A: Breakouts | 6.7% | None (independent) | 6.7% (no change) |
| B: Mean Rev | 8.95% | 0.60 with C | 8.95% × 0.70 = 6.27% |
| C: Volatility | 5.05% | 0.60 with B | 5.05% × 0.70 = 3.54% |
New total allocation: 6.7% + 6.27% + 3.54% = 16.51%
Result: Reduced from 20.7% to 16.51% to account for B-C correlation. This prevents over-concentration when those two strategies lose together.
⚠️ The "Diversification Illusion" Trap
Many traders think they're diversified because they trade "stocks, crypto, and forex" — but all three are risk-on assets that crash together during Fed hawkishness.
Example: December 2021 - January 2022
- Fed signals tapering (QT begins)
- SPY drops -12%, BTC drops -50%, EUR/USD drops -7%
- Trader with "diversified" long portfolio lost 20%+ across ALL positions same month
True diversification = strategies that profit in DIFFERENT market conditions:
- Long breakouts (profit in QE bull markets)
- Short fades (profit in QT bear markets)
- Mean reversion (profit in choppy ranges)
- Volatility selling (profit when VIX spikes then collapses)
Step 4: Set Portfolio Heat Limits
Portfolio heat = Total risk across all open positions simultaneously
Institutional standard: Never exceed 10-15% total portfolio heat
Example:
- Strategy A: 6.7% allocation, currently have 1 trade open → 6.7% heat
- Strategy B: 6.27% allocation, currently have 2 trades open → 12.54% heat
- Strategy C: 3.54% allocation, currently have 1 trade open → 3.54% heat
Total portfolio heat: 6.7% + 12.54% + 3.54% = 22.78% ⚠️ TOO HIGH!
Action required: Don't take new trades until portfolio heat drops below 15%. Close or scale out of positions to reduce exposure.
💡 Pro Tip: The "Portfolio Heat Dashboard"
Create a simple spreadsheet that calculates real-time portfolio heat:
| Strategy | Kelly % | Open Positions | Current Heat |
|---|---|---|---|
| Breakouts | 6.7% | 1 | 6.7% |
| Mean Rev | 6.27% | 0 | 0% |
| Volatility | 3.54% | 1 | 3.54% |
| Total Portfolio Heat | 10.24% ✅ | ||
Rule: Before entering any new trade, check this dashboard. If adding the trade would push heat above 15%, wait for an existing position to close first.
Part 4: Dynamic Position Sizing
Fixed-Fraction vs Dynamic Kelly
Fixed-Fraction: Always risk same % (e.g., 1% per trade)
Dynamic Kelly: Adjust size based on recent performance
Equity Curve Trading
Concept: Increase size when winning, decrease when losing
Method:
- Calculate 20-day moving average of equity curve
- If equity > MA: Increase position size by 25% (edge working)
- If equity < MA: Decrease position size by 50% (edge broken or regime shift)
Benefit: Automatically scales risk to match performance (compound winners, limit losers)
Example: Equity Curve Position Adjustment
Baseline: $100K account, 1% risk = $1,000/trade. Hot streak (equity > MA): $108K account, 1.25% risk = $1,350/trade. Cold streak (equity < MA): $97K account, 0.5% risk = $485/trade. Risk more when winning, less when losing.
Part 5: Using Signal Pilot for Portfolio Construction
Janus Atlas: Multi-Strategy Overlay
Feature: Visualize all active strategies on same chart (identify correlation)
Use case: If all your setups trigger on same day → high correlation → reduce total size
Pentarch Pilot Line: Edge Validation
Feature: Compare your entries vs institutional flow
Signal: If Pilot Line confirms your setup (institutional flow aligned) → increase size to Kelly %
Warning: If Pilot Line contradicts setup (institutions selling, you buying) → reduce size to 0.5× Kelly
Harmonic Oscillator: Regime Detection for Sizing
Feature: Identify trending vs mean-reverting regimes
Application: Increase potential breakout strategy allocation in trending regime, increase mean-reversion allocation in ranging regime
💡 Pro Tip: The "Correlation Audit" Every Quarter
Most traders blow up from hidden correlation. March 2023 SVB collapse: Trader had 4 "uncorrelated" strategies (banks, tech, credit spreads, vol selling). Historical correlation 0.2-0.3. Crisis correlation spiked to 0.95 → all lost money same day, -22% in one session. Audit: If Fed raises 0.5%, which strategies lose? If VIX spikes to 40, how many stops hit? If >60% fail same scenario, over-concentrated.
🎯 Practice Exercise: Build Your Kelly Portfolio
Scenario: Your Three Trading Strategies
You have $100,000 capital and three proven strategies. Calculate optimal Kelly allocation for each:
| Strategy | Win Rate | Avg Win | Avg Loss | Trades/Month |
|---|---|---|---|---|
| Strategy A: Momentum Breakouts | 45% | $600 | $200 | 8 |
| Strategy B: Mean Reversion | 65% | $300 | $250 | 12 |
| Strategy C: Options Income | 70% | $200 | $400 | 15 |
Additional Info:
- Correlation between Strategy A & B: 0.15 (nearly independent)
- Correlation between Strategy B & C: 0.6 (moderately correlated)
- Correlation between Strategy A & C: 0.05 (independent)
Your Tasks:
Task 1: Calculate full Kelly % for each strategy
Formula: Kelly % = (Win Rate × (Avg Win / Avg Loss) - (1 - Win Rate)) / (Avg Win / Avg Loss)
Task 2: Which fractional Kelly should you use? (Full, Half, or Quarter?)
Task 3: Adjust allocations for correlation. Which strategies need reduced sizing?
Task 4: Calculate dollar amount to risk per trade for each strategy
📋 Solution (Try First!)
Click to Reveal Solution
Task 1: Full Kelly: A = 26.7% (45% WR, 3.0 b), B = 35.8% (65% WR, 1.2 b), C = 10.0% (70% WR, 0.5 b).
Task 2: Use quarter Kelly (10-15% DDs vs 40-70% at full). Result: A = 6.7%, B = 9.0%, C = 2.5%.
Task 3: B & C have 0.6 correlation. Reduce both by 25%: A = 6.7%, B = 6.75%, C = 1.9%. Total = 15.35%.
Task 4: $100K account: A = $6,700/trade, B = $6,750/trade, C = $1,900/trade. Expected 18-24% CAGR, 12-16% max DD.
📝 Knowledge Check
Test your understanding of Kelly Criterion and portfolio construction:
Your trading system shows: 60% win rate, $400 average win, $200 average loss. What's the correct Kelly % and what should you actually risk per trade?
You have 3 trading strategies with these full Kelly %: Strategy A = 20%, Strategy B = 25%, Strategy C = 30%. Average correlation between them is 0.80. What's your total portfolio allocation?
Your account equity curve has dropped below its 20-day moving average for the first time in 3 months. Your standard position size is 2% per trade. What should you do?
Portfolio Construction Workflow:
- Backtest each strategy: Calculate win rate, win/loss ratio
- Calculate Kelly % for each strategy (use quarter or half Kelly)
- Identify correlation between strategies (do they win/lose together?)
- Reduce allocation to highly correlated strategies (correlation >0.6)
- Cap total portfolio allocation at 100% (or your risk tolerance)
- Implement equity curve tracking (20-day MA)
- Adjust sizing based on equity vs MA (increase when above, decrease when below)
Pre-Trade Kelly Check:
- Identify which strategy this setup belongs to
- Check remaining allocation for that strategy (have you hit Kelly limit?)
- Check portfolio heat: Total risk across all positions < 10%?
- Use Signal Pilot Pentarch Pilot Line to confirm edge (institutional flow aligned?)
- If edge confirmed, use full (quarter/half) Kelly. If not, use 0.5× Kelly or skip
Key Takeaways
- Kelly Criterion mathematically optimizes sizing based on edge (win rate × win/loss ratio)
- Never use full Kelly (too volatile) — use 0.25-0.5× Kelly
- Correlation matters: Reduce allocation to correlated strategies (they're the same bet)
- Dynamic sizing: Increase when equity > MA, decrease when < MA
- Portfolio heat cap: Total risk across all positions should never exceed 10%
- Overconfidence kills: 60% WR + 2:1 R:R = 20% full Kelly. 7-loss streak (~1.6% probability) loses 22% at full Kelly vs 4-5% at quarter Kelly. Always fractional Kelly.
Kelly criterion provides the math, fractional Kelly provides survival. Build portfolios that grow steadily without ruin risk.
Related Lessons
Advanced Risk Management
Foundation for Kelly-based portfolio construction.
Read Lesson →Quantitative Strategy Design
Advanced quantitative methods for portfolio optimization.
Read Lesson →⏭️ Coming Up Next
Lesson #48: Institutional Order Flow — Enter the Advanced track and learn how institutions execute large orders without moving markets.
Downloads
Educational only. Trading involves substantial risk of loss. Past performance does not guarantee future results.
💬 Discussion (0 comments)
Loading comments...