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In StrategyQuant’s Optimizer, the Simple and Walk-Forward Matrix optimizations serve different purposes and offer distinct methodologies for testing and optimizing strategies.

1. Simple Optimization

• Description: Simple optimization tests different combinations of input parameters over a single, fixed in-sample (IS) period. It runs through all the possible parameter combinations within the selected range and finds the best-performing combinations based on the chosen criteria (e.g., profit factor, Sharpe ratio, etc.).
• Purpose: It’s useful for understanding how specific parameters affect strategy performance and for finding optimal values within a fixed timeframe.
• Process:
  • Runs on a fixed period of historical data (in-sample).
  • Tests all combinations of input variables (e.g., moving average length, stop-loss values).
  • Ranks the parameter sets according to the fitness function you’ve defined.
• Limitation: Because it optimizes based on a single in-sample period, the results might be overfit and less robust when exposed to unseen data (out-of-sample).

2. Walk-Forward Matrix Optimization

• Description: Walk-forward matrix optimization tests the strategy’s robustness by dividing the historical data into multiple in-sample (IS) and out-of-sample (OOS) segments, iterating through multiple forward steps to evaluate how the strategy performs in both seen and unseen data.
• Purpose: This method helps validate that a strategy isn’t overfitted by testing it on unseen data (OOS), providing a better sense of how the strategy will perform in live trading. It’s used to determine the strategy’s adaptability to new market conditions.
• Process:
  • The historical data is split into several consecutive segments.
  • For each segment, part of the data is used for optimization (in-sample), and the remaining is used for testing (out-of-sample).
  • The process is repeated across multiple segments to simulate how the strategy would behave in live market conditions.
  • This creates a matrix of results, allowing you to observe the consistency of the strategy’s performance across different market conditions.
• Advantage: Walk-forward matrix optimization provides a more robust analysis by simulating live trading conditions and testing the strategy’s ability to adapt to new data. It helps avoid overfitting by evaluating how well the strategy performs outside the optimized period.

Key Differences:

• Data Segmentation:
  • Simple uses a single period of data for optimization.
  • Walk-Forward Matrix splits data into several in-sample and out-of-sample segments for more robust testing.
• Overfitting Risk:
  • Simple can lead to overfitting since it only focuses on one dataset.
  • Walk-Forward Matrix helps reduce overfitting by ensuring the strategy performs well on unseen data (OOS).
• Use Case:
  • Simple is great for initial parameter testing and quick optimization.
  • Walk-Forward Matrix is essential for ensuring the robustness of a strategy, particularly when preparing it for live trading.

If your goal is to create a robust strategy that can adapt to live trading conditions and remain reliable over time, the Walk-Forward Matrix is typically a better choice for long-term performance stability.

Compare with my last step. Now I have more than 500 strategies ready to enter [Portfolio Master] mode by selecting the number of strategies between 4-8 in each Port. I want to know that if I set the values​​above, select the best one from what SQX offers, and create 1 Port, then delete it from the existing list to create it, so that all 500 strategies can be used almost completely, even if they are not as good as the first one I got. And/or I will create it only once from 500 and filter from the above list, selecting the best values ​​to create each Port, so that I will have a total of 12 good portfolios as you suggest, without deleting any of them. Please provide your comments.

Given your setup with more than 500 strategies and the intention to build 12 solid portfolios, here’s a detailed comparison of the two approaches you’re considering:

Option 1: Create a Single Portfolio and Delete Strategies After Use

• Process: You filter your strategies based on the set criteria (CAGR/DD%, Sharpe Ratio, etc.), create a portfolio using the best 4-8 strategies, and then remove the used strategies from the list.
• Advantages:
  • Focus on Highest Quality: By selecting only the top-performing strategies for each portfolio, you ensure that each portfolio is built with the best available options.
  • No Duplication: Strategies used in one portfolio won’t be repeated, which diversifies the approaches and reduces over-reliance on specific strategies.
  • Cleans the List: Removing strategies ensures that you always have a fresh pool for the next portfolio.
• Disadvantages:
  • Risk of Running Out of Quality: As you progress, there may be a diminishing number of high-quality strategies available for later portfolios, potentially forcing you to accept weaker strategies.
  • More Manual Work: You need to keep track of what’s been used and make adjustments after each portfolio creation, which could be time-consuming.

Option 2: Filter and Create Multiple Portfolios without Deleting Strategies

• Process: You filter your strategies according to the same criteria and create 12 portfolios without deleting any strategies, allowing overlap and repeated use across portfolios.
• Advantages:
  • Maximize Usage: You get the most out of your 500 strategies, as none are permanently removed, allowing you to pick the best for each new portfolio.
  • Less Pressure on Strategy Availability: By not deleting strategies, you can create multiple portfolios with some repetition, ensuring that each portfolio still has top-performing strategies.
  • Faster Process: You won’t need to track what’s already been used, simplifying the portfolio creation.
• Disadvantages:
  • Over-Reliance on Certain Strategies: Repeating strategies across portfolios may lead to over-reliance on certain approaches, which could expose all portfolios to similar risks, especially during market drawdowns.
  • Lower Diversification: Even though you have multiple portfolios, repeating strategies means the portfolios may not be as diversified as they could be.

Recommendation

For your goal of building 12 high-quality portfolios, I’d suggest combining aspects of both approaches:

1. Phase 1: Start by creating 4-6 portfolios using the best available strategies, without deleting any of them. This ensures you’re maximizing the top performers for multiple portfolios.
2. Phase 2: For the remaining portfolios, introduce more diversity by removing the strategies already used from your selection pool, ensuring fresh strategies are prioritized.

This blended approach balances strategy quality with portfolio diversity, giving you strong portfolios while maximizing your use of all 500 strategies. In this way, you ensure that you maintain both performance and diversification across the entire portfolio set.

Do you know all the filters / ranking (like profit factor, cagr/dd%, return/dd, ..) to mean profitable or good trend within SQX?

Yes, in StrategyQuant X (SQX), various performance metrics and ranking filters are used to assess whether a strategy is profitable and stable over time. Here’s a list of the most important metrics along with what they indicate and how they can be used for filtering/ranking:

Key Metrics for Evaluating Profitability and Stability

1. Profit Factor
   • What it measures: The ratio of gross profits to gross losses.
   • Good value: A Profit Factor greater than 1.5 is generally considered good, with values over 2 indicating strong performance.
   • Purpose: Filters out strategies that earn significantly more than they lose.
2. CAGR/Max Drawdown % (Compounded Annual Growth Rate / Max Drawdown)
   • What it measures: It compares the strategy’s annualized returns to the maximum drawdown (risk).
   • Good value: A ratio greater than 1 is a positive indicator, meaning the returns are higher than the risk (drawdown).
   • Purpose: Filters strategies that balance returns and risk effectively. Higher values indicate more sustainable growth relative to risk.
3. Return/Drawdown Ratio (Ret/DD)
   • What it measures: Another way to compare the strategy’s return against the drawdown.
   • Good value: The higher, the better. Values above 2 are typically desirable.
   • Purpose: Similar to CAGR/Max DD%, this shows how well the strategy performs against its worst losses.
4. Sharpe Ratio
   • What it measures: The Sharpe Ratio measures risk-adjusted returns, or how much excess return the strategy generates per unit of risk.
   • Good value: A Sharpe Ratio above 1 is considered good, while above 2 is excellent.
   • Purpose: Helps identify strategies that have consistent returns relative to risk.
5. Stability
   • What it measures: Measures the consistency of a strategy’s equity curve (how stable the growth is over time).
   • Good value: A value greater than 0.8 is typically considered good.
   • Purpose: Filters strategies that have steady performance without sharp fluctuations.
6. Open Drawdown %
   • What it measures: The percentage of drawdown that is still open (unrealized loss).
   • Good value: Keeping Open DD% below 15% is often desirable.
   • Purpose: Ensures that strategies don’t leave too much risk open during trades, keeping the drawdowns controlled.
7. Max Drawdown %
   • What it measures: The largest peak-to-valley loss in equity.
   • Good value: Max DD% below 20% is usually acceptable for longer-term strategies, with lower being better for risk-averse traders.
   • Purpose: Filters strategies that limit their risk exposure during downturns.
8. Consecutive Win/Loss Trades
   • What it measures: The maximum number of consecutive winning or losing trades.
   • Good value: This metric is mostly a secondary consideration but can show streaks in winning or losing.
   • Purpose: Can be used to avoid strategies that have long losing streaks.
9. CAGR (Compounded Annual Growth Rate)
   • What it measures: The annualized percentage growth of your account or equity curve.
   • Good value: The higher the better, though it should be balanced with risk measures.
   • Purpose: Shows the growth potential of the strategy.
10. R-Squared (R²)
    • What it measures: Shows the statistical fit of the strategy’s equity curve to a straight line. The closer to 1, the more stable the strategy’s growth.
    • Good value: Above 0.8 is ideal for long-term stability.
    • Purpose: Filters strategies with consistent upward growth.
11. Kelly Criterion
    • What it measures: Calculates the optimal position sizing based on past performance.
    • Good value: A higher Kelly value indicates better risk-adjusted returns, but too high may suggest over-leveraging.
    • Purpose: Guides sizing to maximize growth while managing risk.
12. Net Profit
    • What it measures: The total profit after deducting losses and costs.
    • Good value: Positive and stable net profit over time is crucial, but it should be compared against risk metrics.
    • Purpose: Ensures the strategy is actually making money.
13. Sortino Ratio
    • What it measures: Similar to the Sharpe Ratio but only considers downside risk (negative returns).
    • Good value: A value above 1 is good, and higher values indicate better risk-adjusted performance focusing on negative volatility.
    • Purpose: Helps focus on strategies that minimize downside volatility while delivering good returns.

Filtering Strategies in SQX

• Primary Filters:
  • Sharpe Ratio > 2: Helps find strategies with good risk-adjusted returns.
  • CAGR/Max DD% > 1: Ensures returns are higher than drawdowns.
  • Profit Factor > 1.5: Ensures profits are sufficiently higher than losses.
• Secondary Filters:
  • Open DD% < 15: Ensures drawdowns are within acceptable limits.
  • Stability > 0.8: Ensures a smooth and steady equity curve.
• Other Considerations:
  • Max Drawdown %: This is crucial for risk management, as it can help avoid strategies with sharp drawdowns.
  • Return/Drawdown: Ensures that the strategy’s returns justify the risk it takes.

By using a combination of these filters, especially focusing on Sharpe Ratio, Stability, Profit Factor, and drawdowns, you can filter out strategies that are robust, profitable, and capable of performing well in live trading.

OOS Testing: More importantly, assess the performance during out-of-sample testing to ensure the strategy is robust in unseen market conditions. Strategies with a high OOS Sharpe ratio and low OOS drawdowns are more likely to perform well in live trading.

this OOS should be > ?

 

When assessing out-of-sample (OOS) performance, the following benchmarks can help determine if a strategy is robust enough for live trading:

1. OOS Sharpe Ratio:

• A Sharpe ratio greater than 1 indicates that the strategy has delivered excess returns relative to its volatility.
• A Sharpe ratio of greater than 2 is considered excellent, suggesting strong performance and favorable risk-adjusted returns.

2. OOS Drawdown:

• Aim for a maximum drawdown of less than 15%. This benchmark helps ensure that the strategy does not experience severe losses that could jeopardize the trading account.
• Additionally, the recovery time from drawdown is important; faster recovery is generally preferable.

3. Profit Factor:

• A profit factor greater than 1.5 is generally favorable. This means that the strategy makes 1.5 times more profit than it loses.

4. Consistency:

• Look for consistency in OOS performance metrics, such as stable returns and low volatility, over a sufficient sample size (e.g., at least 6-12 months of trading).

Summary:

• OOS Sharpe Ratio > 1 (ideally > 2)
• Maximum OOS Drawdown < 15%
• Profit Factor > 1.5

Meeting these benchmarks can indicate that the strategy is likely to perform well in live trading.

To filter and select the best strategies from your 300+ strategies in Portfolio Master, follow a systematic approach that aligns with your ranking criteria and ensures that only the most robust and stable strategies are included in the final portfolio. Here’s a step-by-step guide to filtering:

1. Apply Your Ranking Criteria

Use the criteria you’ve already set for ranking individual strategies: – CAGR/Max DD% > 1 – Sharpe Ratio > 2 – Profit Factor > 1.5 – Stability > 0.8 – Open DD% < 15%

This initial filter should remove many strategies that don’t meet the baseline performance requirements.

2. Check In-Sample (IS) and Out-of-Sample (OOS) Performance

• IS Testing: Review the performance of each strategy during the in-sample period to ensure that it was optimized correctly.
• OOS Testing: More importantly, assess the performance during out-of-sample testing to ensure the strategy is robust in unseen market conditions. Strategies with a high OOS Sharpe ratio and low OOS drawdowns are more likely to perform well in live trading.

3. Evaluate Strategy Correlation

• Use correlation analysis to ensure that strategies in your portfolio are not highly correlated. Highly correlated strategies expose you to similar risks across multiple strategies, increasing the chances of simultaneous drawdowns.
• Keep strategies with low or negative correlation in your portfolio to achieve diversification and reduce risk.

4. Monte Carlo Simulations

• Perform Monte Carlo stress tests on your selected strategies to assess how they handle market noise and randomness. Strategies that consistently perform well under Monte Carlo simulations are more robust.
• Focus on strategies with a low chance of ruin and those that maintain good metrics like Sharpe ratio and Profit Factor in the simulated results.

5. Examine Trade Frequency and Conditions

• Look for strategies that maintain consistent trade frequency and avoid excessive overtrading, which can increase transaction costs and slippage.
• Ensure that strategies follow a balance of trend-following, breakout, and swing trading methodologies (as you’ve chosen) to reduce dependency on a single market condition.

6. Filter for Drawdown Recovery

• Evaluate how fast each strategy recovers from drawdowns. Strategies that recover quickly are generally more reliable for long-term use. Use the drawdown recovery time as an additional filter.

7. Forward Testing

• Take your top strategies and conduct a small-scale forward testing or paper trading to see how they behave in current market conditions. Live market dynamics often differ from historical data, so this step is crucial for final validation.

8. Select a Balanced Portfolio

• After narrowing down the best-performing strategies, use Portfolio Master to combine them into an optimized portfolio with diverse market exposures and timeframes (H1/H4, M15/H4, etc.).
• Make sure the combined strategies adhere to your risk management rules, such as RRR > 1:3, duplicate orders, closing positions on Fridays, and break-even trailing stops.

9. Monitor Ongoing Performance

• Continue to monitor the performance of your portfolio once it’s live, making adjustments only if necessary. Pay attention to how strategies perform during different market phases (trending, ranging, volatile) to ensure long-term stability.

By following this structured filtering process, you’ll be able to select a portfolio of strategies that not only meet your criteria but are also robust, diversified, and ready for live trading.

When focusing on long-term stability for your strategy, aside from CAGR/Max DD% and Sharpe Ratio, the most critical metric to consider is Profit Factor. However, other important factors like Stability and Open Drawdown (DD) also play key roles in assessing the reliability of your strategy. Let’s explore these metrics:

1. Profit Factor:

• What it Measures: The ratio of gross profit to gross loss. For example, a profit factor of 1.5 means that for every dollar lost, you are making 1.5 dollars in profit.
• Importance: A higher profit factor (typically > 1.5) is crucial for long-term viability. It shows that the strategy generates more profit than loss over time.
• Why It’s Key for Long-Term Stability: It directly reflects the strategy’s overall profitability, indicating whether it can sustain profitability through different market conditions.
• Ideal Target: Profit Factor above 1.5 is solid, while a value of 2.0 or more is very strong.

2. Stability of Returns (Stability):

• What it Measures: The consistency of your strategy’s performance over time. It looks at the smoothness of the equity curve.
• Importance: Stability indicates how reliable the strategy is at generating returns without significant fluctuations.
• Why It’s Key for Long-Term Stability: A stable equity curve suggests that your strategy can withstand various market environments without experiencing wild swings in performance.
• Ideal Target: Aim for a stability score close to 1, where 1 represents a perfectly straight equity curve.

3. Open Drawdown (Open DD%):

• What it Measures: The maximum unrealized loss during a trade (before it’s closed).
• Importance: While Max Drawdown focuses on the worst drawdown for closed trades, Open DD% shows how much risk your strategy takes while trades are still open.
• Why It’s Key for Long-Term Stability: High open drawdowns can cause emotional stress and can put your account at risk, especially during volatile periods. Keeping open drawdowns low ensures your strategy can withstand market swings without large floating losses.
• Ideal Target: Aiming for Open DD% < 10-15% is generally considered good for long-term sustainability.

Summary of Metrics (Besides CAGR/Max DD% and Sharpe Ratio):

1. Profit Factor (Most Important): Reflects the overall profitability of your strategy. Target >1.5, ideally >2.
2. Stability: Measures how smooth and reliable your equity curve is. Aim for a stability score near 1.
3. Open Drawdown %: Keep this value as low as possible to avoid large floating losses. Aim for <10-15%.

Focusing on these three metrics will help confirm your strategy’s long-term stability and profitability, making it robust enough to withstand different market conditions.

what’s the most priority betwee CAGR/Max DD% and Sharp ratio ?

When prioritizing between CAGR/Max DD% and Sharpe Ratio, it depends on your strategy’s goals and risk tolerance. Here’s how to assess their importance:

1. CAGR/Max DD% (Compound Annual Growth Rate / Maximum Drawdown Percentage):

• What it Measures: The growth of your account over time (CAGR) relative to the worst peak-to-trough decline (Max Drawdown).
• Importance: It tells you how much risk (drawdown) you’re taking to achieve returns. A higher CAGR/Max DD means your returns are efficient in relation to the risk you’ve taken.
• When it’s Critical:
  • When you aim for long-term, steady growth with controlled risk.
  • If you prioritize minimizing drawdowns, which is crucial for strategies that need to stay resilient in volatile markets (like your long-term trading approach).

2. Sharpe Ratio:

• What it Measures: The return per unit of risk (volatility). It measures how well your strategy compensates you for the risk taken (volatility of returns).
• Importance: A higher Sharpe ratio (above 1, or ideally above 2) means the strategy offers a better risk-adjusted return. It’s a good metric for comparing different strategies to see which one generates smoother returns relative to volatility.
• When it’s Critical:
  • When you care about consistent performance and want to compare risk-adjusted returns between strategies.
  • If your strategy experiences large fluctuations in returns, the Sharpe ratio helps determine if the higher returns are worth the risk (volatility).

Comparison in Your Strategy:

• CAGR/Max DD%: Since you are building a strategy for long-term use, minimizing drawdowns (while still growing your account) is a key consideration. This metric is more focused on the capital preservation aspect and will be vital in avoiding large losses that could wipe out significant portions of your account.
• Sharpe Ratio: It’s essential for ensuring that your strategy has consistent returns relative to risk. However, if your drawdowns are well-managed (as per the focus on risk control), the Sharpe Ratio becomes secondary in importance.

Which is More Important?

For your strategy goals (focused on long-term performance and risk management): 1. CAGR/Max DD% should be the top priority because it balances growth with minimizing drawdowns. 2. Sharpe Ratio is important but secondary to CAGR/Max DD%. You should still aim for a Sharpe ratio above 1 (preferably 2+), but don’t compromise your drawdown management to chase a higher Sharpe ratio.

Conclusion:

Focus on maximizing CAGR/Max DD% to ensure your strategy can grow steadily with minimal drawdowns. A high Sharpe Ratio (above 2) is an excellent goal but secondary to ensuring that your strategy survives long-term market swings with controlled drawdowns.