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Yes, it is possible to find or build a strategy that meets these criteria, but it will depend on several factors, including the quality of your data, the optimization process, and the strategy type.

Here’s a breakdown of what each criterion implies and how achievable it is:

1. CAGR/Max DD% > 1:

• Achievability: This is a reasonable and important target, as it ensures your strategy produces more growth than risk. You can achieve this through proper risk management, consistent profits, and by minimizing drawdowns.
• Tuning Tips: Focus on risk control, such as using tight stop losses and proper position sizing (e.g., your 0.01 lot per $100 account balance rule).

2. Sharpe Ratio > 2:

• Achievability: A Sharpe Ratio above 2 is challenging but realistic, especially with a well-optimized strategy. It implies high risk-adjusted returns with low volatility.
• Tuning Tips: To achieve this, focus on strategies that reduce large fluctuations in returns. Use techniques like trailing stops, break-even exits, and conservative risk management. Avoid strategies with excessive drawdowns or those that rely on highly volatile instruments without proper hedging.

3. Profit Factor > 1.5:

• Achievability: This is a common target for profitable trading strategies. A profit factor above 1.5 indicates that your gross profits are at least 1.5 times larger than your gross losses.
• Tuning Tips: Optimize entry/exit rules, avoid overtrading, and focus on strategies that aim for higher reward-to-risk ratios, such as your target of RRR > 1:3.

4. Stability > 0.8:

• Achievability: Stability near 0.8 is a realistic goal for most well-performing strategies. It shows a relatively smooth and reliable equity curve, which is necessary for long-term performance.
• Tuning Tips: Stability can be enhanced by reducing the frequency of large drawdowns, fine-tuning exit rules, and optimizing over a range of market conditions (using IS and OOS testing).

5. Open DD% < 15%:

• Achievability: This is achievable but can be difficult if you’re targeting high returns. Controlling open drawdown is crucial to keep the account safe from volatile market swings.
• Tuning Tips: You can keep open drawdown in check by adjusting trade size, using dynamic stop-loss management (e.g., ATR-based stops), or employing partial exits as trades move into profit.

Finding Such a Strategy:

1. Backtesting and Optimization: You’ll likely need extensive backtesting with 20 years of M1 data (as you’re already using) to find strategies that meet all these criteria. Sequential optimization across timeframes (H1, H4, etc.) can help refine strategies for long-term stability.
2. Strategy Combination: You may need to combine trend following, breakout, and swing trading methods, as these tend to perform well in various market conditions.
3. Fine-Tuning Parameters: Parameters like risk management rules, trailing stops, and exit timing (closing trades before Friday or after 5 days) will play a key role in managing drawdowns and ensuring the other metrics hold up.

It will take work, but it is possible to find a strategy that fits within these boundaries. Be prepared for iterative testing and refinement in StrategyQuant X to optimize across these performance metrics.

Great! Now that we’re moving forward with the Trend + Breakout + Swing Trading combination, here’s the plan to proceed:

Steps for Optimization and Backtesting:

1. Initial Setup:
   • Main Timeframe: H1 (for active signals).
   • Sub Timeframe: H4 (for confirmation).
   • Open Duplicate Orders allowed, with signals from Trend Trading (ADX, Ichimoku, MACD), Breakout (Bollinger Bands, ATR, Momentum), and Swing Trading (RSI, Fractals, MACD).
   • Implement trailing stop and break-even with ATR or Parabolic SAR.
   • Ensure RRR > 1:3 and close all trades by Friday.
2. Optimization:
   • Risk and Lot Size Management: 0.01 lots per $100 balance, with risk percentage on the account.
   • Sequential optimization for additional timeframes like M30/H4, M15/H4, M5/H4 to explore robustness across different market conditions.
   • Focus on finding the optimal parameters for indicators like ATR and Ichimoku to maximize profitability across both trending and volatile markets.
3. Backtesting:
   • Using your M1 data over 20 years, run the backtest for IS (In-Sample) and OOS (Out-of-Sample) periods.
   • Analyze performance metrics: Profit Factor, RRR, Stability, Drawdown, and Win/Loss ratio.
4. Validation:
   • Post-backtest, validate on OOS data to ensure consistency and reliability in live market conditions.

A Sharpe ratio greater than 1 is a positive indicator for a trading strategy, but when it’s over 2, it signifies even better performance. Here’s a breakdown:

• Sharpe Ratio > 1: Indicates that the strategy is generating more returns than the risk it’s taking. A ratio above 1 means the excess returns (returns above the risk-free rate) are higher than the volatility of the strategy’s returns.
• Sharpe Ratio > 2: This is considered excellent performance. A Sharpe ratio over 2 means the strategy is delivering significantly higher returns relative to the amount of risk (volatility) it’s exposed to. It suggests the strategy is not only profitable but also doing so with low volatility and risk. This kind of performance is desirable for long-term strategies, as it indicates a strong balance between risk and reward.

What a Sharpe Ratio Over 2 Means:

1. Efficient Risk Management: The strategy takes relatively low risk compared to the high returns it generates.
2. Low Volatility: The equity curve should be relatively smooth, with fewer large drawdowns.
3. Consistency: It’s a sign of strong risk-adjusted returns—the strategy is not reliant on a few lucky trades but generates returns consistently over time.

In summary, a Sharpe ratio over 2 indicates an outstanding risk-reward balance, and such a strategy is highly desirable, especially if the ratio remains consistent across both In-Sample (IS) and Out-of-Sample (OOS) testing. However, always double-check for overfitting or data snooping—make sure that this performance translates well in OOS and live trading conditions.

i just building and got some prototype but i asking u: Profit factor, Ret/DD ratio, Stability, Fitness, Open DD%, Win/Loss ratio and CAGR/Max DD%. Rank these values ​​from most important to least important that I should consider, including the analysis of both IS and OOS at each stage.

When evaluating a trading strategy, especially in StrategyQuant X (SQX), the metrics you mentioned are all important but serve different purposes. Ranking them depends on your specific goals (e.g., minimizing risk, maximizing returns, or focusing on long-term sustainability). Here’s a ranking from most important to least important, considering both In-Sample (IS) and Out-of-Sample (OOS) stages:

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

• Why It’s Important: This is a key metric for long-term growth and sustainability of the strategy. It balances how much the strategy grows versus how much it risks. A high CAGR with a low Max Drawdown ensures that the strategy is generating returns without taking excessive risk.
• IS/OOS Consideration: A good ratio in both IS and OOS suggests that the strategy is scalable and robust across different market environments.
  • IS: Focus on optimizing this metric to ensure strong growth.
  • OOS: Ensure consistency; a large drop in OOS could indicate overfitting.

2. Profit Factor

• Why It’s Important: Profit Factor (gross profit divided by gross loss) is essential for understanding the overall profitability of the strategy. A Profit Factor greater than 1 indicates a profitable system, with values above 1.5 or 2 being ideal.
• IS/OOS Consideration: Profit Factor must remain solid in OOS testing. If it drops significantly OOS, the strategy may be curve-fitted.
  • IS: Aim for a strong value, but don’t prioritize it at the expense of risk management.
  • OOS: Focus on stability and a consistent profit factor.

3. Ret/DD Ratio (Return-to-Drawdown Ratio)

• Why It’s Important: This metric balances returns against drawdowns. A high Ret/DD ratio indicates that the strategy generates good returns relative to the risk (drawdown) it takes.
• IS/OOS Consideration: It’s important in both IS and OOS stages because it ensures that your strategy’s performance isn’t reliant on taking high risks. Look for consistency across both.
  • IS: Focus on maximizing returns while keeping drawdowns minimal.
  • OOS: The ratio should not degrade significantly, ensuring stability.

4. Open Drawdown % (Open DD%)

• Why It’s Important: Open DD% tracks the maximum floating loss during a trade that hasn’t closed yet. This is crucial for understanding the worst-case scenarios and how your strategy behaves in adverse conditions. High Open DD% could signal that the strategy lets trades run into significant losses before closing them.
• IS/OOS Consideration: In OOS, you want to see a manageable Open DD%. A high Open DD% in OOS could indicate riskier trades.
  • IS: Optimize to keep Open DD% within acceptable risk limits.
  • OOS: Check if the Open DD% stays controlled in unseen data.

5. Stability

• Why It’s Important: Stability measures how consistent the equity curve is over time. A stable equity curve is essential for long-term profitability and avoiding emotional stress from sharp equity fluctuations.
• IS/OOS Consideration: Stability should be maintained across both IS and OOS phases to ensure that the strategy isn’t over-optimized to one specific market condition.
  • IS: High stability is desirable, but watch out for overfitting.
  • OOS: Check if stability remains intact without large drops in equity.

6. Win/Loss Ratio

• Why It’s Important: While the Win/Loss ratio is helpful, it doesn’t paint a full picture. A strategy with a lower win rate can still be profitable if the winning trades are larger than the losing ones. It’s more useful when combined with other metrics like Profit Factor or Return-to-Drawdown.
• IS/OOS Consideration: While optimizing, focus less on having a high Win/Loss ratio and more on profitability. The Win/Loss ratio may vary but shouldn’t drastically change between IS and OOS phases.
  • IS: It’s fine if the Win/Loss ratio isn’t extremely high as long as the strategy is profitable.
  • OOS: Ensure the ratio doesn’t drop significantly.

7. Fitness

• Why It’s Important: Fitness is an overall measure used by SQX to rank strategies based on multiple performance metrics. It’s a good indicator in the early stages of strategy generation but can be less reliable than specific metrics like CAGR/Max DD% or Profit Factor for deep analysis.
• IS/OOS Consideration: While a high fitness score is useful for identifying strong candidates in genetic evolution, don’t rely on it too heavily in OOS testing. Focus more on the other key metrics.
  • IS: A high fitness score helps in the strategy-building process.
  • OOS: Use other metrics to verify performance rather than fitness alone.

Stage-Specific Considerations:

In-Sample (IS) Analysis:

• In the IS phase, you are primarily focusing on optimizing your strategy.
  • Prioritize CAGR/Max DD%, Profit Factor, and Ret/DD Ratio. These three metrics ensure that you have a strategy that is growing profitably with manageable risk.
  • Pay attention to Stability and Open DD% next, as they will indicate how smooth your strategy’s equity curve is and whether you can tolerate the drawdowns during open trades.
  • Win/Loss Ratio is less critical here, as it can be misleading if isolated from other factors. A lower Win/Loss ratio can be fine as long as the profits outweigh losses.
  • Fitness is helpful early on but don’t let it overshadow more significant performance metrics.

Out-of-Sample (OOS) Analysis:

• In the OOS phase, your focus shifts to robustness and ensuring the strategy is not overfitted to past data.
  • Look for consistency in CAGR/Max DD%, Profit Factor, and Ret/DD Ratio between IS and OOS. If these metrics significantly degrade, it’s a sign of overfitting.
  • Stability becomes more crucial here. A strategy that maintains stability in OOS is likely to perform well in live markets.
  • Open DD% should be well-managed, and ideally, it should not increase dramatically in OOS testing.
  • The Win/Loss Ratio can fluctuate, but it should not collapse in OOS. Ensure that profitable trades remain larger than losing ones.

Final Ranking Summary:

1. CAGR/Max DD% (Balances growth vs. risk, essential for long-term viability)
2. Profit Factor (Key profitability measure)
3. Ret/DD Ratio (Measures return relative to risk)
4. Open DD% (Manages risk on open trades)
5. Stability (Ensures a smooth equity curve)
6. Win/Loss Ratio (Helpful but secondary to profitability metrics)
7. Fitness (Useful early but less important for final validation)

This ranking should help guide your focus when optimizing and validating strategies in SQX. Let me know if you want to dive deeper into any specific aspect of the metrics!