My Thoughts on How to Run Multiple Trading Systems (Risk)
3 to 5 strategies
Managing multiple trading systems is not just about diversifying strategies; it’s about allocating capital dynamically to maximize returns while keeping risk under control. The key is adjusting exposure based on performance—scaling up well-performing strategies and reducing exposure to underperformers—all while keeping drawdowns under 40%.
Instead of relying on the Sharpe Ratio, which penalizes all volatility (both upside and downside), I prefer using the Sortino Ratio. The Sortino Ratio focuses only on downside risk, making it more relevant for real-world portfolio management.
This post explains how to:
✅ Allocate capital dynamically among multiple trading strategies.
✅ Use the Sortino Ratio to evaluate strategy performance.
✅ Control drawdowns and keep risk within acceptable limits.
✅ Avoid over-concentration and maintain diversification.
Let’s dive in. 🚀
Why Dynamic Allocation?
Most traders stick with static allocations—distributing capital evenly or using fixed weights for each strategy. While simple, this ignores market changes.
✅ A strategy that worked well last year might struggle now.
✅ A previously weak strategy might start outperforming.
✅ Market conditions shift, so capital should be reallocated dynamically.
A dynamic allocation approach adapts to changing strategy performance and risk conditions by adjusting capital accordingly.
How to Allocate Capital Dynamically
We follow a structured approach for allocating and rebalancing capital across multiple strategies.
1. Compute Trailing Performance Metrics
Each strategy is evaluated using:
Sortino Ratio (instead of Sharpe): Focuses only on downside volatility instead of penalizing both upside and downside moves.
Cumulative returns: Helps track overall performance.
Recent downside deviation: Measures how much the strategy loses rather than total volatility.
These metrics identify which strategies provide the best risk-adjusted returns with minimal downside risk.
2. Assign Weights Based on the Sortino Ratio
Once performance metrics are calculated, capital is allocated proportionally to the Sortino Ratio:
✅ High Sortino Ratio → Higher weight (better risk-adjusted return).
✅ Low Sortino Ratio → Lower weight (reduce exposure).
✅ Negative Sortino Ratio → Minimal allocation (don’t allocate capital to losing strategies).
To avoid excessive shifts:
📌 Smoothing: Averages performance over multiple periods to avoid reacting to short-term noise.
📌 Weight Caps & Floors: No strategy gets more than 40% of capital, and every strategy keeps a minimum allocation.
3. Adjust for Risk (Volatility Targeting & Risk Parity)
After assigning weights based on Sortino, we adjust for overall risk by ensuring portfolio volatility stays within acceptable limits:
📌 Volatility Targeting: If recent market conditions increase volatility, we scale down all positions proportionally.
📌 Risk Parity: Ensures no single strategy dominates the portfolio’s risk. Each strategy contributes equally to overall volatility.
📌 Inverse-Volatility Weighting: If a strategy has high volatility, its allocation is reduced to prevent extreme portfolio fluctuations.
4. Implement Rebalancing
The portfolio is rebalanced weekly or monthly:
If a strategy performs well (high Sortino Ratio), it receives more capital.
If a strategy underperforms (low Sortino Ratio), its exposure is reduced.
If volatility is excessive, all allocations are scaled down to maintain stability.
To reduce trading costs, we only rebalance when changes are meaningful instead of reacting to small fluctuations.
Risk Management: Keeping Drawdowns Under 40%
Drawdowns are the biggest risk for multi-strategy portfolios. A strategy might look great in theory, but if it exposes the portfolio to deep losses, it must be managed carefully.
1. Ex-Ante Risk Controls (Before Allocating Capital)
Simulate worst-case drawdowns before finalizing allocations.
If potential drawdown exceeds 40%, we scale back allocations or adjust risk parameters.
2. Ongoing Monitoring (After Allocating Capital)
If drawdown reaches 30-35%, we trigger an emergency rebalance to reduce exposure.
If drawdown approaches 40%, we de-risk further (reduce leverage or shift to safer strategies).
This adaptive risk control prevents catastrophic losses.
Ensuring Diversification & Avoiding Over-Concentration
📌 Max Weight Cap: No strategy gets more than 30-40% of capital.
📌 Minimum Strategy Count: Always maintain at least 3-5 active strategies.
📌 Correlation Monitoring: Strategies with correlation above 0.8 are treated as a single group.
These steps ensure genuine diversification, reducing the risk of all strategies failing simultaneously.
Backtesting & Performance Evaluation
To validate this approach, we backtest the strategy across different market conditions. Key performance metrics include:
✅ Total return (Did the portfolio outperform a benchmark?)
✅ Annualized volatility (Was risk managed effectively?)
✅ Sortino Ratio (Did we maximize return while controlling downside risk?)
✅ Maximum drawdown (Did we stay under the 40% loss limit?)
We compare the dynamic allocation model to:
1️⃣ A static equal-weight portfolio.
2️⃣ A fixed-weight portfolio (e.g., 50% equities, 30% bonds, 20% gold).
By measuring how well the Sortino-based allocation improves returns and reduces drawdowns, we verify its effectiveness.
Real-World Application & Challenges
🔹 Advantages of Dynamic Allocation:
✅ Reduces exposure to failing strategies before major losses.
✅ Captures upside by increasing exposure to strong performers.
✅ Adapts to market changes without excessive overtrading.
🔹 Challenges to Consider:
⚠️ Trading Costs – Frequent rebalancing increases costs.
⚠️ Data Stability – Past performance may not predict future results.
⚠️ Overfitting Risks – Over-optimizing based on historical data can reduce real-world effectiveness.
To address these, we keep the model simple, robust, and adaptable.
Final Thoughts: Why This Works
Dynamic allocation isn’t about chasing returns—it’s about systematically managing risk.
By adjusting capital allocation based on Sortino Ratio and downside risk:
✅ Enhances risk-adjusted returns (higher Sortino).
✅ Reduces drawdowns while maintaining strong performance.
✅ Maintains diversification while tilting towards strong strategies.
✅ Adapts to changing markets without overreacting.
This strategy combines adaptive allocation with strict risk management, ensuring long-term stability and profitability.
Instead of guessing which strategy will work best, this model allocates capital where it’s most effective, cutting losers before they destroy returns and riding winners without excessive exposure.
At the end of the day, successful trading isn’t just about finding good strategies—it’s about knowing how to allocate capital among them wisely.