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So give me re-arrange 5 pairs like this without duplicating filters for maximum efficiency.

Sure! Here are five pairs of filters arranged for maximum efficiency, ensuring no duplicates across the selections:

Filter Pairs

1. Pair 1:
   • First Filter (IS): Sharpe Ratio
   • Second Filter (OOS): Net Profit
2. Pair 2:
   • First Filter (IS): CAGR/Max DD%
   • Second Filter (OOS): Profit Factor
3. Pair 3:
   • First Filter (IS): Stability
   • Second Filter (OOS): Consecutive Win/Loss
4. Pair 4:
   • First Filter (IS): Ret/DD Ratio
   • Second Filter (OOS): Open DD%
5. Pair 5:
   • First Filter (IS): Max DD%
   • Second Filter (OOS): R-Squared

Summary

• Each pair consists of one metric from the Importance Score (IS) category and one from the Out-of-Sample (OOS) category, ensuring no duplicates. This setup will help you efficiently narrow down your EA selection while covering various critical performance aspects.

Here are the recommended filter settings parameters for each pair to help you refine your EA selection process effectively:

Filter Settings Parameters

1. Pair 1:
   • IS: Sharpe Ratio
     • Setting: Minimum Sharpe Ratio (e.g., > 1.5)
   • OOS: Net Profit
     • Setting: Minimum Net Profit (e.g., > $1,000 or a percentage of capital)
2. Pair 2:
   • IS: CAGR/Max DD%
     • Setting: Minimum CAGR/Max DD% ratio (e.g., > 1.5)
   • OOS: Profit Factor
     • Setting: Minimum Profit Factor (e.g., > 1.5)
3. Pair 3:
   • IS: Stability
     • Setting: Minimum Stability (e.g., > 0.8)
   • OOS: Consecutive Win/Loss
     • Setting: Maximum Consecutive Losses (e.g., < 3)
4. Pair 4:
   • IS: Ret/DD Ratio
     • Setting: Minimum Ret/DD Ratio (e.g., > 1.5)
   • OOS: Open DD%
     • Setting: Maximum Open Drawdown Percentage (e.g., < 15%)
5. Pair 5:
   • IS: Max DD%
     • Setting: Maximum Drawdown (e.g., < 20%)
   • OOS: R-Squared
     • Setting: Minimum R-Squared (e.g., > 0.6)

Summary of Settings

• Each pair is designed with specific thresholds to ensure you select EAs that meet your performance criteria. You can adjust the numerical values based on your risk tolerance and trading goals. These settings will help you focus on strategies that are likely to perform well while managing risk effectively.

After completing Step 3 (the Walk-Forward Matrix with real tick data), the next step for a final review and comparison involves thorough analysis and filtering to confirm the robustness and reliability of the strategies. Here’s what you should do:

1. Aggregate Results from All Steps:

• Compile the performance metrics from Step 1 (Selected TF + Monte Carlo), Step 2 (1-Minute Data Tick), and Step 3 (Real Tick Data with Walk-Forward Matrix).
• Metrics to compare include:
  • Profit Factor
  • Sharpe Ratio
  • CAGR/Max DD%
  • Drawdown (Max and Open)
  • Stability
  • Win/Loss Ratio
  • Net Profit

2. Consistency Check Across Steps:

• Compare Performance Metrics: Ensure that strategies performing well in Steps 1 and 2 still show good results in Step 3.
• Consistency Across Steps: Prioritize strategies that maintain strong performance and meet your criteria in all testing phases. For example, a strategy with a profit factor consistently above your threshold across all steps is likely more robust.
• Stability Analysis: Verify that the stability metric (e.g., > 0.8) is maintained across the steps, which indicates a consistent equity curve and reduced risk of erratic behavior.

3. Look for Outliers:

• Identify strategies that show significant performance drops or volatility in Step 3 compared to Steps 1 and 2. A drop in metrics such as the Sharpe ratio or a spike in drawdown during the Walk-Forward analysis can signal potential weaknesses under live trading conditions.

4. Select the Most Robust Strategies:

• Filter strategies that pass your final criteria (e.g., consistent Sharpe ratio > 2, profit factor > 1.5, drawdown < 20%).
• Prioritize those that show minimal variation in performance metrics across different testing data sets, as this indicates adaptability and robustness.

5. Portfolio Creation:

• Create Portfolios: Use the most robust strategies to create diversified portfolios. Ensure that these portfolios balance different strategy types and timeframes to reduce risk.
• Simulate Portfolio Performance: Run a final simulation or backtest of your chosen portfolios on real tick data to evaluate how they perform together and assess their combined drawdown and profit factor.

6. Forward Testing and Live Demo:

• Forward Test: Run your selected strategies or portfolios in a live demo account for a few weeks to a few months. This will help validate the strategies’ performance in real-time conditions without risking capital.
• Monitor Performance: Continuously track key metrics and look for consistency with backtested and Walk-Forward results.

7. Compare and Review the Results:

• Final Review Report: Create a comparison report summarizing the performance of each strategy across all testing steps and during the forward test. Highlight key metrics, any significant deviations, and overall performance trends.
• Decision Making: Choose to proceed with strategies or portfolios that maintain robust performance throughout all phases, as they are likely to be the most reliable for live trading.

This comprehensive review ensures that the strategies you move forward with are robust, adaptable, and optimized for real trading environments.

Suggested Approach for Phase 1 Portfolio Creation with IS and OOS Filtering

In phase 1, the goal is to create several robust portfolios by filtering and ranking strategies to achieve high performance and stability, with a specific focus on their behavior in both in-sample (IS) and out-of-sample (OOS) testing.

1. IS and OOS Filtering:
   • IS: Ensure strategies perform consistently during the in-sample period by prioritizing parameters like CAGR/Max Drawdown (DD%), Sharpe Ratio, and Stability. These metrics demonstrate the strategy’s profitability and risk management in the training phase.
   • OOS: Use filters that emphasize robustness and adaptability to unseen data. High values for metrics like Sharpe Ratio, Stability, and low OOS drawdowns indicate resilience. Also, analyze parameters such as Open DD% and consecutive losses to evaluate risk in live scenarios.
2. Prioritize Key Performance Metrics for Filtering and Ranking:
   • CAGR/Max DD%: A high ratio here is essential for long-term profitability.
   • Sharpe Ratio: Select for a Sharpe Ratio > 2 in both IS and OOS to ensure that returns consistently outweigh risk.
   • Profit Factor: A Profit Factor > 1.5 across IS and OOS indicates that profitable trades outweigh losses.
   • Stability: Aim for Stability > 0.8, ensuring strategies are less likely to be overfitted.
   • Open DD% and Max DD%: Filter for Open DD% < 15% to limit real-time exposure to high drawdowns, with Max DD% providing an additional safeguard.
   • Net Profit and R-Squared (R²): These are supportive metrics, with higher values indicating stronger trends in profit generation.
3. Portfolio Structuring:
   • From the filtered strategies, construct 4–6 portfolios, each containing 4–8 strategies that exhibit the highest OOS Sharpe Ratios, Stability, and low drawdowns. Ensure each portfolio balances a mix of high-return and stable strategies.
   • Once these portfolios are built, remove selected strategies from the list for the next round of portfolio creation, or, alternatively, create all portfolios from the initial list to maximize the use of all high-performing strategies without deletion.

This approach ensures each portfolio is diversified in both strategy type and performance metrics, optimizing for long-term stability across various market conditions.

For filtering strategies in In-Sample (IS) and Out-of-Sample (OOS) phases, here’s how you should approach it to ensure long-term stability:

Filtering by IS and OOS:

Both IS and OOS performance are critical, as they provide insight into how the strategy performs in known market conditions (IS) and unseen market conditions (OOS). The goal is to ensure the strategy generalizes well beyond the backtested data.

Key Steps to Approach IS and OOS Filtering:

1. Separate IS/OOS Data

Make sure your dataset has been divided into In-Sample (IS) and Out-of-Sample (OOS) parts. IS is used for training or optimization, while OOS is used to test the strategy’s robustness.

2. Prioritize OOS for Long-Term Viability

• OOS performance is more important than IS because it demonstrates how the strategy handles real, unseen market conditions. Always filter strategies that have both IS and OOS results, but give more weight to OOS metrics to ensure robustness.

Ranking and Filtering for IS and OOS:

To set up your filters and ranking criteria for both IS and OOS, here’s how to prioritize:

1. Sharp Raio (OOS > IS)1. Sharpe Ratio (OOS > IS)

• IS: Should be > 1.5. A high IS Sharpe Ratio indicates good performance in training data.
• OOS: This should be your priority and should ideally be > 2. It shows strong performance with minimal volatility in unseen data.
• Why: If OOS Sharpe is much lower than IS, the strategy may be overfit. The OOS Sharpe Ratio >2 confirms the strategy can handle real-world volatility.

2. CAGR/Max DD% (OOS > IS)

• IS: Should be > 1, but OOS should be higher than IS.
• OOS: Should be prioritized here as it shows the return achieved per unit of drawdown in unseen market conditions. Aim for > 1.
• Why: Ensuring the OOS CAGR/Max DD% is strong proves that the strategy will continue to generate healthy returns with manageable risk.

3. Profit Factor (OOS close to IS)

• IS: Look for > 1.5 to ensure profitability in known data.
• OOS: Should ideally be close to IS performance. Aim for > 1.5, and if OOS is significantly lower, be cautious.
• Why: Large gaps between IS and OOS profit factor indicate potential overfitting.

4. Return/Drawdown Ratio (Ret/DD) (OOS > IS)

• IS: Should be > 2.
• OOS: Should be comparable or better than IS, ideally > 2. If OOS Ret/DD drops too much compared to IS, the strategy may not generalize well.
• Why: This helps you assess the balance of returns versus risk in unseen conditions. Favor strategies where OOS Ret/DD is consistent with IS.

5. Stability (OOS close to IS)

• IS: Should be > 0.8 to indicate a stable equity curve in the training data.
• OOS: Should be close to IS. Significant drops here mean the strategy is less reliable in real conditions.
• Why: High stability in OOS ensures the strategy performs smoothly without wild fluctuations in live trading.

6. Open Drawdown % (OOS < IS)

• IS: Set the threshold < 15% to limit exposure in known conditions.
• OOS: This should be the same or lower than IS to ensure the strategy doesn’t take on too much risk when live. Prioritize < 10-12% for OOS.
• Why: You want to reduce risk in live markets, so OOS drawdown should ideally be lower than IS.

7. Max Drawdown % (OOS < IS)

• IS: Set a threshold < 20-25%.
• OOS: Should be the same or lower than IS to avoid risk spikes in live trading. < 20% is preferable.
• Why: Keeping OOS max drawdown low is critical to ensuring the strategy doesn’t suffer big losses in real-world conditions.

8. Net Profit (OOS close to IS)

• IS: Look for solid net profit but not at the expense of risk.
• OOS: Should be close to IS. If OOS profit is significantly lower than IS, this could be a sign of overfitting.
• Why: The goal is to ensure consistent profitability across both IS and OOS phases.

9. R-Squared (R²) (OOS close to IS)

• IS: Look for R² to indicate a strong trend, but don’t prioritize it too heavily.
• OOS: Should be close to IS values. Large differences could signal instability in the equity curve.
• Why: R² helps in assessing whether the strategy maintains its trend in unseen data.

10. Consecutive Win/Loss Trades (OOS > IS)

• IS: Avoid strategies with large streaks of losses.
• OOS: Should be comparable to IS, and you want to avoid any strategies where the number of consecutive losses is much higher in OOS.
• Why: A strategy that maintains its win/loss consistency across IS and OOS will be more robust.

Suggested Filter Prioritization for IS/OOS:

1. Sharpe Ratio (OOS > IS)
2. CAGR/Max DD% (OOS > IS)
3. Return/Drawdown Ratio (Ret/DD) (OOS > IS)
4. Profit Factor (OOS close to IS)
5. Stability (OOS close to IS)
6. Open Drawdown % (OOS < IS)
7. Max Drawdown % (OOS < IS)
8. Net Profit (OOS close to IS)
9. Consecutive Win/Loss Trades (OOS > IS)
10. R-Squared (R²) (OOS close to IS)

Summary

When filtering and ranking strategies, OOS performance should take precedence over IS, as it reflects the strategy’s performance in live, unseen market conditions. Always ensure that OOS metrics are close to or better than IS to confirm the robustness of your strategy, particularly Sharpe Ratio, CAGR/Max DD%, and Ret/DD.

In phase 1, which says to create 4-6 portfolios, in this part, what should I filter and rank them by? 1. Profit Factor 2. CAGR/Max DD% 3. Sharpe Ratio 4. Return/Drawdown Ratio (Ret/DD) 5. Stability 6. Open Drawdown % 7. Max Drawdown % 8. Consecutive Win/Loss Trades 9. Net Profit 10. R-Squared (R²)

To build the 4-6 portfolios in Phase 1, focusing on filtering and ranking the strategies effectively, I would suggest using a weighted approach to emphasize the metrics that align with both profitability and risk management for long-term stability. Here’s how to prioritize and filter the metrics:

1. CAGR/Max DD% (Priority: High)

• Why: This is one of the most crucial metrics because it shows how well the strategy performs in terms of growth while managing risk. Higher values mean you get better returns for each unit of risk.
• How to Filter: Select strategies with a CAGR/Max DD% > 1 as a minimum requirement, and prioritize strategies that have values significantly greater than 1 (e.g., >1.5 or >2) for better risk-adjusted returns.

2. Sharpe Ratio (Priority: High)

• Why: The Sharpe Ratio indicates risk-adjusted returns. A Sharpe Ratio > 2 is generally considered excellent, as it means the strategy is delivering high returns for the level of volatility/risk involved.
• How to Filter: Filter out strategies with Sharpe ratios below 2. Rank remaining strategies by Sharpe Ratio as a second key factor.

3. Profit Factor (Priority: Medium-High)

• Why: The Profit Factor compares gross profits to gross losses. A Profit Factor > 1.5 indicates that for every dollar risked, the strategy earns at least 1.5 dollars.
• How to Filter: Filter strategies with a Profit Factor above 1.5 and rank them to ensure a healthy balance of profits vs losses.

4. Return/Drawdown Ratio (Ret/DD) (Priority: Medium-High)

• Why: This metric reflects how much return you are getting for each unit of drawdown. A higher value indicates better performance relative to risk.
• How to Filter: Ret/DD values should be high (>2), and strategies with strong Ret/DD ratios should be given more weight in the ranking process.

5. Stability (Priority: Medium)

• Why: This measures the consistency of the equity curve. Stability above 0.8 ensures smoother performance with fewer wild swings.
• How to Filter: Filter for strategies with Stability > 0.8 and rank by Stability to ensure you are selecting smooth performers.

6. Open Drawdown % (Priority: Medium)

• Why: Open Drawdown % indicates how much capital is at risk while a trade is active. Keeping this low ensures that you don’t have a lot of capital exposed to ongoing risk.
• How to Filter: Select strategies with Open DD < 15% to avoid excessive risk during open trades.

7. Max Drawdown % (Priority: Medium)

• Why: Max Drawdown % shows the largest peak-to-trough drop in equity. Lower drawdowns indicate less capital loss during downturns.
• How to Filter: Set a maximum acceptable drawdown threshold (e.g., Max DD < 20-25%), and give higher preference to strategies with lower Max Drawdowns.

8. Net Profit (Priority: Medium-Low)

• Why: Net Profit is important for absolute returns but should not overshadow risk-adjusted performance metrics.
• How to Filter: While this metric should not dominate, it’s important to ensure the strategies are delivering consistent profits. Rank by profit only after other risk-adjusted metrics.

9. R-Squared (R²) (Priority: Low)

• Why: R² measures the strength of the trend in the equity curve. While useful, this can be less relevant for short-term portfolios.
• How to Filter: R² should be considered, but not weighted too heavily in early portfolio building stages.

10. Consecutive Win/Loss Trades (Priority: Low)

• Why: This is more of a psychological metric that shows how many wins or losses can occur consecutively. While useful, this is not a key metric for filtering.
• How to Filter: Use this as a final check to ensure your selected strategies don’t have extreme streaks of losses or wins, which could indicate volatility.

Suggested Approach for Phase 1 Portfolio Creation:

1. Primary Filters: Start by filtering with CAGR/Max DD% > 1, Sharpe Ratio > 2, Profit Factor > 1.5, Stability > 0.8, and Open Drawdown < 15%.
2. Ranking: Once you’ve applied these filters, rank the remaining strategies using CAGR/Max DD%, Sharpe Ratio, and Ret/DD as your top three criteria.
3. Secondary Filters: As a secondary consideration, check Max Drawdown %, Net Profit, and Stability to ensure balanced strategies.
4. Final Checks: Lastly, apply Consecutive Win/Loss Trades and R² to fine-tune for consistency and smoother equity curves.

This structured approach will allow you to maximize the robustness and profitability of your strategies while controlling risk and volatility.

Added ability to filter by IS and OOS in each topic to see which IS/OOS should be used.

When adding the ability to filter by In-Sample (IS) and Out-of-Sample (OOS) performance in each metric or topic, it becomes critical to differentiate between the two phases of strategy testing. The IS data is used to develop and optimize the strategy, while the OOS data tests the strategy on unseen, untouched market conditions to assess its robustness.

Here’s how to approach filtering each metric for IS and OOS:

IS (In-Sample) vs OOS (Out-of-Sample) Explanation

• In-Sample (IS): The period used for building and optimizing the strategy. High IS performance may indicate overfitting if OOS performance is poor.
• Out-of-Sample (OOS): The unseen data used to test the robustness of a strategy. Good OOS performance indicates that the strategy generalizes well to unseen market conditions.

Metric Prioritization and IS/OOS Expectations

1. Profit Factor
   • IS Target: Should be > 1.5.
   • OOS Target: A good profit factor in OOS should remain above 1.3 or higher to show that the strategy is profitable without overfitting.
   • Purpose: This shows how well the strategy is balancing profits against losses both in-sample and out-of-sample.
2. CAGR/Max DD%
   • IS Target: > 1 (This indicates returns are higher than the risk during optimization).
   • OOS Target: Should ideally remain above 0.8 in OOS. If the value dips significantly, it might indicate over-optimization in the IS phase.
   • Purpose: It helps compare growth to risk over the strategy’s life cycle. Stability in this metric across IS and OOS is important for long-term performance.
3. Sharpe Ratio
   • IS Target: > 2 (This shows good risk-adjusted performance in-sample).
   • OOS Target: Should remain above 1.5 in OOS. Sharpe ratios dropping significantly in OOS may indicate risk or volatility problems in unseen data.
   • Purpose: This measures the strategy’s ability to handle risk consistently, and OOS results are crucial to validate its stability in live trading.
4. Return/Drawdown Ratio (Ret/DD)
   • IS Target: > 2 (Shows solid returns in comparison to risk).
   • OOS Target: Ideally, you want this to stay above 1.5 to confirm stability.
   • Purpose: A high Ret/DD ratio in IS shows good returns relative to risk, but if the OOS version drops sharply, it indicates the strategy may not handle risk well in real market conditions.
5. Stability
   • IS Target: > 0.8 (A smooth, consistent equity curve).
   • OOS Target: Stability should remain > 0.7 in OOS. A significant drop indicates the strategy’s performance may become inconsistent in live conditions.
   • Purpose: High stability across IS and OOS ensures a smooth equity curve, avoiding sharp performance drops in real trading.
6. Open Drawdown %
   • IS Target: < 15% (Keeps risk exposure in check during optimization).
   • OOS Target: Should remain below 20% in OOS testing. If OOS drawdowns significantly exceed the IS values, the strategy may struggle in volatile or unseen markets.
   • Purpose: Managing open drawdowns is critical for risk control, and seeing how this behaves OOS ensures you’re not taking on excessive risk in real trading.
7. Max Drawdown %
   • IS Target: < 20% (Manages maximum peak-to-valley losses).
   • OOS Target: Should not exceed 25% in OOS. Drawdown stability between IS and OOS indicates the strategy is capable of handling stress.
   • Purpose: This metric helps manage risk, ensuring that no single market condition causes extreme losses.
8. Consecutive Win/Loss Trades
   • IS Target: > 2 (Aims for win streaks without significant drawdowns).
   • OOS Target: Should be similar to IS results, or show a smooth transition. Long losing streaks in OOS can be a warning sign.
   • Purpose: This shows how often you can expect consecutive wins or losses. Stability between IS and OOS is a good indicator of robustness.
9. Net Profit
   • IS Target: Positive net profit in IS with steady growth.
   • OOS Target: Should maintain a positive net profit. If OOS performance is significantly lower, this indicates overfitting.
   • Purpose: Maintaining positive net profit in both IS and OOS is crucial for real trading profitability.
10. R-Squared (R²)
    • IS Target: > 0.8 (A high R² shows smooth, predictable growth).
    • OOS Target: Should remain above 0.7 to avoid overfitting. A significant drop in OOS means the strategy is inconsistent.
    • Purpose: This metric helps you find strategies that perform smoothly without high volatility in their returns.
11. Sortino Ratio
    • IS Target: > 1.5 (Indicates good risk-adjusted returns considering only downside volatility).
    • OOS Target: Above 1.2 in OOS. A sudden drop in Sortino indicates the strategy is exposing itself to more downside risk than it did during optimization.
    • Purpose: This is a good alternative to Sharpe Ratio, focusing on negative risk rather than total risk. Stability in OOS is critical for downside protection.

How to Use These Filters in SQX:

1. First pass with IS filters:
   • During the initial build/optimization phase, filter strategies based on high values for key metrics in the IS data. Use Profit Factor > 1.5, CAGR/Max DD% > 1, Sharpe Ratio > 2, Ret/DD > 2, and Stability > 0.8.
2. Second pass with OOS filters:
   • After IS optimization, evaluate the strategies in the OOS phase. Set slightly lower but still acceptable values: Profit Factor > 1.3, Sharpe Ratio > 1.5, CAGR/Max DD% > 0.8, Ret/DD > 1.5, and Stability > 0.7.
3. Compare IS and OOS performance:
   • Discrepancies between IS and OOS are normal, but they should not be drastic. If a strategy performs well in IS but poorly in OOS, it’s likely overfitted. Favor strategies with consistent metrics across both phases.

By maintaining these IS/OOS targets in SQX, you can ensure your strategies are robust and able to handle live trading without deteriorating due to overfitting.

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.