Why Most Multi-Strategy Portfolios Are Improperly Weighted

How I Calculate Risk per Strategy to Achieve Equal Portfolio Weighting

When running multiple expert advisors or trading strategies in the same portfolio, equal risk per trade does not mean equal exposure. In fact, using a fixed risk per trade across different strategies almost always leads to imbalanced performance, where some strategies dominate the portfolio while others dilute returns.

The goal of my risk model is simple:

Every strategy should contribute roughly the same expected annual return to the portfolio.

To achieve this, risk must be adjusted based on:

• Trading frequency

• Average holding time

• Market volatility

• Realistic long-term profitability

  
  

Why Fixed Risk per Trade Does Not Work

Let’s look at common mistakes:

1. Different trade frequency

• Strategy A trades 3 times per week

• Strategy B trades 10 times per week

If both use the same risk per trade, Strategy B will naturally have much higher exposure, even if it performs worse.

2. Different holding times

• Strategy A holds trades for 1 hour

• Strategy B holds trades for 10 hours

Even with the same number of trades per week, the strategy with longer holding time has:

• Higher market exposure

• Larger profit and loss swings

• Higher impact during trending or volatile periods

Because of this, you cannot equalize risk by:

• Using the same percentage risk

• Dividing risk by trades per week

• Ignoring holding time and volatility

  
  

Step 1: Risk Must Be Based on Volatility (ATR)

I base all risk on volatility, not stop-loss size or fixed percentages.

Specifically:

• Risk is calculated using 1 ATR (Average True Range)

• Usually a daily ATR, as it represents the market’s average daily movement

This approach:

• Automatically adapts to different instruments (Forex, Gold, Indices, Crypto)

• Adjusts for changing market conditions over time

• Avoids problems where price levels change but volatility increases

A 1% move today is not the same as a 1% move 20 years ago — volatility-based risk solves this.

Step 2: Define the Portfolio Target

Example portfolio:

• 10 strategies

• Target portfolio return: 50% per year

This means:

• Each strategy should contribute ~5% per year

• No compounding assumed (fixed-risk model for clarity)

  
  

Step 3: Backtest Each Strategy at 1% ATR Risk

For each strategy:

• Run a long-term backtest (e.g. 10 years)

• Use 1% risk per ATR

• Record:

  • Total profit (%)

  • Profit Factor

Profit Factor is crucial because:

• PF = 1.0 → breakeven

• PF > 1.0 → profitable

• Unrealistically high PFs in backtests must be discounted

  
  

Step 4: Use a Realistic Profit Factor Baseline

Backtests often exaggerate performance.
I assume a realistic long-term profit factor of 1.2.

This is:

• Conservative

• Achievable over multiple years

• Suitable for live trading expectations

  
  

Step 5: Scale Risk Based on Profit Factor Degradation

Example 1: Strong Backtest, Needs Higher Risk

• 10-year backtest profit: 100%

• Profit Factor: 2.0

• Annual profit at 1% risk: 10%

But:

• PF 2.0 is 5× higher than realistic PF 1.2

• Expected real-world profit:
  10% ÷ 5 = 2% per year

Target is 5% per year, so:

• Risk must be increased by 2.5×

• Final risk: 2.5% per ATR

  
  

Example 2: Weak Backtest, Needs Lower Risk

• 10-year backtest profit: 50%

• Profit Factor: 1.1

• Annual profit at 1% risk: 5%

If PF improved from 1.1 → 1.2:

• Profit would roughly double

• Expected profit becomes 10% per year

Target is only 5%, so:

• Risk must be reduced by 50%

• Final risk: 0.5% per ATR

  
  

Final Result

After adjusting risk this way:

• Every strategy is normalized to the same expected annual contribution

• High-frequency strategies no longer overpower low-frequency ones

• Long-holding strategies are properly weighted

• Portfolio behavior becomes smoother and more predictable

If all strategies end up with the same real-world profit factor, they will also produce the same annual return.

This is the foundation of a properly balanced multi-strategy portfolio.