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These are the steps for creating our EA, based on our conversation. Please clarify and analyze which parts take too long. My complete EA creation steps:

A. Building..

1. Creating 20 strategies using Genetic Evolution.
1.1 Breakout Strategy
1.2 Carry Trade Strategy
1.3 Cycle-Based Trend Reentry Strategy
1.4 Day Trading Strategy
1.5 Dynamic Momentum and Price Rejection Strategy
1.6 Grid Trading
1.7 Market Chaos and Divergence Strategy
1.8 Mean Reversion on Trend Weakness
1.9 Multi-Timeframe Divergence Strategy
1.10 News Trading
1.11 Oscillator Reversion and Momentum Burst Strategy
1.12 Position Trading
1.13 Price Action Trading
1.14 Range Trading Strategy
1.15 Retracement Trading
1.16 Scalping Strategy
1.17 Sentiment and Momentum Reversal Strategy
1.18 Swing Trading
1.19 Trend Channel Momentum Strategy
1.20 Trend Trading Strategy

* Using TF H1/H4 – Opened Timeframe – Ranking Profit > 1.4 Ret/DD >4 Min trade per month > 2 – No Cross check / Rubustness test
** Entering always includes Enter at market / Reverse / Stop / Limit pending
*** Filtering each step with 25 entries per market entry type, totaling 100 entries per main category, and a total of 2000 entries.
**** Enabling Exit types: MoveSL2BE / SL2BE add pips / Profit target / Stop loss / Trailing stop / Trailing activation / Exit rules
***** Trading option: Friday Exit 23:00
****** Money management: Risk fixed % of account

A. Building Improved

• Create 20 strategies using Genetic Evolution, which takes time for filtering and refining.
• Filtering 25 strategies for market entry and multiple exit options increases processing time.
• Setting money management complicates calculations.

B. Melting..

2. Testing all 2000 results backtested with all 30 currency pairs, separating timeframes into 10 TFs.
2.1 H1/H4 – M30/H4 – M15/H4 – M5/H4 – M5/H1 – M15/H1 – M30/H1 – M15/M30 – M5/M30 – M5/M15
2.2 Combining the above results for Automatic Retest by changing Precision to 1-minute data tick simulate, but adhering to the original trading settings.
2.2 Adding Monte Carlo trades manipulation – Monte Carlo retest methods and Sequential optimization by changing values in the respective EAs.
2.3 Saving successful files in Folder @Blender
2.4 Automatic retest using only Walk-Forward Matrix.
2.5 Saving successful files in @Melted

B. Melting Improved

• Backtesting 30 currency pairs and various timeframes is time-consuming, especially with trading value changes and Monte Carlo testing.
• Automatic retests with 1-minute tick data and Walk-Forward Matrix require high computational power.

C. Ending..

3. Loading all files in @Blender into the Initial Population to create entirely new EAs, repeating 30 times (30 currency pairs).
3.1 Creating 5 new steps: Build Martingale / ATM / Everyday Exit / Risk % account, and using all Exit types.
3.2 Automatic retest with the original trading settings for 5 timeframes (H1/H4 – m30/h4 – m15/h4 – m5/h4 – m5/h1 – m15/h1 – m30/h1). Using the original settings for Opened timeframe. Using Monte Carlo, both (trades manipulation and retest methods), and Sequential optimization. Adding strategies that passed.
3.3 Automatic retest for all, another round, with 1-minute data tick simulation, with both Monte Carlo (2 versions) and Sequential optimize as before.
3.4 Automatic retest for all, another round, using walk-forward matrix.

C. Ending Improved

• Loading files in @Blender to create 30 new EAs is time-intensive, particularly with additional strategies.
• Multiple automatic retests using Monte Carlo and Sequential Optimization increase processing time.

Conclusion:
Suggestions include reducing strategies and pairs tested, considering partial parameter adjustments, and using more efficient processing tools to save time.

To match your available signals to the 12 strategies, let’s review and count which indicators would be appropriate for each trading strategy from the list of signals you provided.

Trading Strategies and Potential Indicator Matches:

1. Price Action Trading
   Indicators: Candle Pattern, Fractal, Highest Lowest, Moving Average, Bollinger Bands, Fibonacci (custom code possible)
2. Range Trading Strategy
   Indicators: Bollinger Bands, ATR, RSI, Stochastic, Disparity Index, Keltner Channel
3. Trend Trading Strategy
   Indicators: Momentum, Moving Average, Ichimoku, Super Trend, Parabolic SAR, Kaufman Efficiency Ratio, MACD, Vortex, Hull Moving Average, CSSA Market Regime, ADX (if included later)
4. Position Trading
   Indicators: RSI, Momentum, MACD, Moving Average, Kaufman Efficiency Ratio, VWAP, Ichimoku
5. Day Trading Strategy
   Indicators: Stochastic, RSI, ATR, VWAP, Bollinger Bands, Momentum, Williams %R, Connors RSI, KAMA
6. Scalping Strategy
   Indicators: ATR, Stochastic, RSI, VWAP, Momentum, Parabolic SAR, Fractal, Disparity Index, Gann Hi Lo
7. Swing Trading
   Indicators: RSI, MACD, Stochastic, Kaufman Efficiency Ratio, Super Trend, Williams %R, Bollinger Bands, Keltner Channel
8. Carry Trade Strategy
   Indicators: ATR, RSI, Moving Average, Hull Moving Average, VWAP, Gann Hi Lo
9. Breakout Strategy
   Indicators: Bollinger Bands, ATR, RSI, Momentum, ADX, Super Trend, TTM Squeeze, MACD, Williams %R
10. News Trading
    Indicators: ATR, RSI, Momentum, Disparity Index, Super Trend, VWAP
11. Retracement Trading
    Indicators: RSI, Fibonacci Retracement (custom), MACD, Stochastic, Kaufman Efficiency Ratio, Williams %R
12. Grid Trading
    Indicators: ATR, RSI, Moving Average, VWAP, Bollinger Bands, Super Trend

Indicators used from your list:

1. ATR
2. Bollinger Bands
3. Candle Pattern
4. Connors RSI
5. CSSA Market Regime
6. Disparity Index
7. Fractal
8. Gann Hi Lo
9. Hull Moving Average
10. Ichimoku
11. KAMA
12. Kaufman Efficiency Ratio
13. Keltner Channel
14. MACD
15. Momentum
16. Moving Average
17. Parabolic SAR
18. RSI
19. Stochastic
20. Super Trend
21. TTM Squeeze
22. VWAP
23. Williams %R
24. Vortex

Count:

• Total unique indicators used: 24

These are indicators that match the various strategies you are working with, excluding the ones you mentioned you don’t want (like ADX, MACD, RSI, and ATR). Some of these indicators can work across multiple strategies, making them versatile tools for your trading system.

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.

To start with a combination that covers different market conditions while aligning with your desired strategy, I recommend focusing on a hybrid of Trend Trading, Breakout Strategy, and Swing Trading. These three strategies complement each other well and offer a balanced approach to both trending and volatile markets.

Combination Strategy: Trend + Breakout + Swing

Key Features:

1. Trend Trading: Capitalizes on long-lasting trends using indicators like ADX, MACD, and Ichimoku to identify strong trends. This ensures you catch larger moves.
2. Breakout Strategy: Helps in volatile conditions where price breaks out of consolidation. Use Bollinger Bands, ATR, and Momentum to identify breakouts and apply trailing stops to secure gains.
3. Swing Trading: Captures intermediate price swings between market highs and lows. MACD, RSI, and Fractals work well to time entry and exit points, ensuring you profit from reversals or corrections.

Signals for the Combination:

• Trend Trading: Use ADX (>25) to confirm a strong trend. Combine with Ichimoku for entry points in the direction of the trend. Apply MACD for further momentum confirmation.
• Breakout Strategy: Add Bollinger Bands for spotting volatility and breakout zones, while ATR helps manage trailing stops after the breakout. Momentum confirms the strength of the breakout.
• Swing Trading: Use Fractals and RSI to identify swing highs and lows. Swing trades can be opened in the direction of the trend or at key reversal points. Apply a trailing stop or break-even to secure profits on swings that move in your favor.

Application of Your Rules:

1. Open Orders with Duplicates Allowed: During strong trend or breakout conditions, duplicate trades can be placed. For instance, multiple orders can be triggered as long as ADX shows a strong trend or Bollinger Bands expand during a breakout.
2. Profit Targets: Exit trades when profit reaches 1-5% of total capital or the position exceeds 5 days. Use RSI or Fractals to close swing trades, while MACD and ATR help manage trend and breakout exits.
3. Break-Even and Trailing Stop: Apply a Parabolic SAR or ATR-based trailing stop after price moves in your favor. For trend trades, break-even should trigger when the price has moved favorably by a set percentage (e.g., 1-2%).
4. RRR > 1:3: Ensure all trades have a minimum risk-reward ratio of 1:3 by setting stop-losses based on ATR and take-profits aligned with trend direction.
5. Close by Friday: Use an exit rule to ensure all positions are liquidated before Friday’s close, even if the profit target has not been met.
6. Consecutive Wins/Losses > 2: Monitor consecutive wins or losses to adjust position sizing or avoid overtrading during losing streaks.

Expected Benefits:

• Trend Trading captures long-term movements in strong markets.
• Breakout Strategy profits from high volatility and sharp market moves.
• Swing Trading adds flexibility by allowing trades in both trending and counter-trending situations.

This combination can help you build a well-rounded system, adaptable to various market conditions while maximizing your profit potential.

My desired strategy, can you adaption with those 12 strategies above and use my signals, make it greater possible: 1. Open orders duplicate allowed 2. Close orders with a profit for 1-5% from the total capital or close by using signals that hold positions for no more than 5 days 3. Use Break-Even profits and use trailing according to appropriate signals to catch up with profits as quickly as possible 4. I need RRR more than 1:3 5. Close all orders before the market closes every Friday 6. Consec win/loss trades > 2

To adapt your desired strategy with the 12 trading methods and signals you provided, we can combine specific features from each strategy to create an enhanced, hybrid approach. Let’s structure it step by step:

Key Elements of Your Desired Strategy:

1. Open Duplicate Orders: This allows more flexibility in taking multiple trades if the conditions allow.
2. Profit Target: Closing orders with 1-5% profit from the total capital.
3. Time-Limited Holds: No position should last more than 5 days.
4. Break-Even and Trailing Stop: Secure profits with a break-even and then trail the stop to maximize gains.
5. High RRR (1:3): Ensuring risk is minimized and profits are large enough to justify trades.
6. Close by Friday: All positions are liquidated before the market closes on Friday.
7. Consecutive Wins/Losses: Focus on having more than 2 consecutive wins or limiting losses.

Strategy Adaptation Across the 12 Trading Methods:

1. Price Action Trading:

• Signals: Use Candle Patterns and Fractals to capture high-quality reversal or breakout trades.
• Adaption: These signals can be used to open multiple positions during a strong price action movement, with a stop-loss placed at key price levels. The trailing stop and break-even would be applied as soon as the price moves favorably.

2. Range Trading Strategy:

• Signals: Apply Bollinger Bands, RSI, and Stochastic for entering positions at the range extremes.
• Adaption: Open trades when the price reaches either overbought or oversold levels. Use trailing stops aggressively to capture small but consistent gains within the range. If the trade doesn’t meet profit criteria within 5 days, exit by signal.

3. Trend Trading Strategy:

• Signals: Combine ADX, Ichimoku, and Super Trend to ride strong market trends.
• Adaption: Open duplicate positions in a strong trend confirmed by ADX (>25) and Ichimoku cloud direction. Apply the trailing stop to catch the bulk of the move while closing trades that meet the 1-5% profit or exceed 5 days of holding.

4. Position Trading:

• Signals: Use Ichimoku and Hull Moving Average for longer-term trend confirmation, but limit holding time to 5 days.
• Adaption: Position trading signals are generally longer-term, but in your strategy, we can shorten this by closing trades within 5 days if the target profit is not reached.

5. Day Trading Strategy:

• Signals: Utilize VWAP, Momentum, and RSI to capture intraday moves.
• Adaption: Open multiple positions based on intraday momentum and close them by the end of the trading day or use your break-even and trailing stop to capture small profits. Ensure no trades remain open on Fridays.

6. Scalping Strategy:

• Signals: Leverage Parabolic SAR, Stochastic, and VWAP for fast entries/exits.
• Adaption: Scalping will require tighter trailing stops and quicker moves to break-even. You can open duplicate orders on small moves and close them as soon as you hit the profit target or within 5 days.

7. Swing Trading:

• Signals: MACD, RSI, and Fractals to identify swing highs/lows.
• Adaption: Swing trading offers opportunities to capture larger moves. Duplicate orders can be opened as long as the swing signal is valid, with the trailing stop applied to catch larger profits. Exit after 5 days or on the Friday close.

8. Carry Trade Strategy:

• Signals: KAMA and Directional Index for long-term bias, but constrained to short-term holding.
• Adaption: In traditional carry trade, positions are held long-term, but with your strategy, use the trailing stop to secure short-term profits within 5 days.

9. Breakout Strategy:

• Signals: Bollinger Bands, ATR, and Momentum for volatility-based breakouts.
• Adaption: Use breakout signals to open duplicate trades. Once the breakout occurs, the trailing stop will help capture further gains while securing profits. Close the trade if the price meets the 1-5% target or exits by Friday.

10. News Trading:

• Signals: ATR, Momentum, and VWAP to capture volatility spikes.
• Adaption: News trading tends to be unpredictable, so quick entries with trailing stops and a break-even move are essential. Use this approach to exit trades quickly if the market moves in your favor.

11. Retracement Trading:

• Signals: Fibonacci Retracements, RSI, and Fractals for entry signals.
• Adaption: Enter on retracement to a key Fibonacci level with multiple orders. Apply trailing stop once the price resumes the primary trend. Close the trade either at the target profit or after 5 days.

12. Grid Trading:

• Signals: Generally grid strategies are less signal-based, but ATR or Bollinger Bands can help define volatile zones.
• Adaption: In a grid strategy, you can apply the trailing stop on profitable orders while still allowing duplicate trades. Close all positions before the end of the week or after 5 days to prevent overexposure.

Enhancing the Strategy:

1. Duplicate Orders: This flexibility allows for scaling into trades during favorable conditions, especially in trending markets or during strong breakouts. Combining this with ADX for trend strength or ATR for volatility can provide an edge.
2. Close Orders Based on Capital Gain or Signal: The 1-5% capital gain target works well with signals like Ichimoku, Candle Patterns, or Bollinger Bands to time exits when trades become profitable.
3. Break-Even and Trailing Stop: Use Parabolic SAR or ATR for managing the trailing stop, ensuring that once the price has moved in your favor, the trailing stop locks in profits while allowing room for larger gains.
4. RRR of 1:3: Targeting a risk-reward ratio of 1:3 is ideal for strategies like Breakout or Swing Trading. Use Fractals, RSI, and MACD to spot high-probability trades and manage risk with well-placed stop losses.
5. Weekly Close: Ensure that all trades are automatically closed by Friday using a time-based exit rule, combined with signals to prevent holding positions over the weekend.
6. Consecutive Wins/Losses: This could be monitored in SQX by applying risk filters, ensuring the strategy does not become too risky if losses accumulate, or adding more trades if you’re on a winning streak.

By merging these trading strategies with your specifications, you’ll create a highly adaptable system that should perform well across different market conditions.

simulate for this 12 straegies method by using my signals provided: 1. Price action trading 2. Range trading strategy 3.Trend trading strategy 4. Position trading 5. Day trading strategy 6. Scalping strategy 7. Swing trading 8. Carry trade strategy 9. Breakout strategy 10. News trading 11. Retracement trading 12. Grid trading

To simulate these 12 trading strategies using the available signals in SQX, we’ll first match each strategy type with appropriate indicators from your list. This will create a structured approach for SQX to build and optimize each strategy based on specific methodologies.

1. Price Action Trading:

• Signals: Candle Patterns, Fractals, ATR
• Approach: Price action traders rely on interpreting market structure, chart patterns, and key price levels. Candle patterns combined with ATR for volatility can help pinpoint entries and exits.
• Use in H1/H4: H1 for active candle formations; H4 for larger price patterns.

2. Range Trading Strategy:

• Signals: Bollinger Bands, Keltner Channel, RSI, Stochastic
• Approach: Range trading involves identifying overbought and oversold conditions within a sideways market. Bollinger Bands and Keltner Channel are excellent for defining the range, while RSI or Stochastic can time the entry.
• Use in H1/H4: H1 for entering at range extremes; H4 to confirm the range is stable.

3. Trend Trading Strategy:

• Signals: ADX, MACD, Super Trend, Ichimoku
• Approach: Focus on capturing sustained market trends. ADX confirms trend strength, MACD signals momentum, while Ichimoku and Super Trend confirm trend direction.
• Use in H1/H4: H1 for trend signals; H4 for broader trend confirmation.

4. Position Trading:

• Signals: Ichimoku, Hull Moving Average, RSI, ADX
• Approach: Position traders take long-term trades based on macro trends. Ichimoku and Hull MA work well for spotting long-term trends, while ADX confirms trend strength.
• Use in H1/H4: H4 for trend identification; H1 for fine-tuning entries.

5. Day Trading Strategy:

• Signals: Moving Average, VWAP, RSI, Momentum
• Approach: Day traders use quick signals to profit from intraday price movements. Moving averages, VWAP (volume-weighted average price), and momentum indicators work well for this.
• Use in H1/H4: H1 for day trading entries; H4 for ensuring alignment with larger trends.

6. Scalping Strategy:

• Signals: Parabolic SAR, ATR, Stochastic, VWAP
• Approach: Scalping requires fast signals. Parabolic SAR and ATR work for precise entry/exit timing, while Stochastic identifies quick overbought/oversold conditions.
• Use in H1/H4: H1 for quick price action trades; H4 could be used to ensure macro trend direction is not against the trade.

7. Swing Trading:

• Signals: MACD, RSI, Hull Moving Average, Fractals
• Approach: Swing traders seek to profit from intermediate price swings. MACD and Hull MA identify swings, while RSI and Fractals time entry/exit points.
• Use in H1/H4: H1 for swing setups; H4 for trend alignment.

8. Carry Trade Strategy:

• Signals: KAMA (Kaufman Adaptive Moving Average), Directional Index, VWAP, ATR
• Approach: Although carry trading is more interest-rate based, technical signals like KAMA can help identify good entry points into longer-term trades, while ATR helps manage risk.
• Use in H1/H4: H4 for trend setup; H1 for trade entry and management.

9. Breakout Strategy:

• Signals: Bollinger Bands, ATR, Momentum, ADX
• Approach: Breakout strategies focus on trading volatility expansions. Bollinger Bands and ATR identify breakouts, while Momentum confirms the breakout direction.
• Use in H1/H4: H1 for breakouts; H4 for larger breakout confirmation.

10. News Trading:

• Signals: ATR, Momentum, Volume-based signals (e.g., VWAP, AVG Volume)
• Approach: News trading involves reacting quickly to market events. ATR captures volatility surges, while VWAP and momentum indicators show how the market reacts.
• Use in H1/H4: H1 for fast reaction to news events; H4 for identifying broader market sentiment.

11. Retracement Trading:

• Signals: Fibonacci retracement levels (can be coded), Stochastic, RSI, Fractals
• Approach: Retracement trading involves entering trades when price retraces within a larger trend. Stochastic and RSI work to identify the retracement, while Fractals show reversal points.
• Use in H1/H4: H1 for identifying retracement; H4 for trend direction and retracement targets.

12. Grid Trading:

• Signals: None (grid strategy), ATR, Bollinger Bands (optional for range)
• Approach: Grid trading involves placing multiple orders at set intervals without needing precise signals. However, ATR or Bollinger Bands can add volatility context to the grid.
• Use in H1/H4: Primarily H1 for grid execution; H4 for macro trend bias (optional).

Simulation Expectations:

• Price Action, Range, and Trend Strategies: These should perform well when tested with H1 signals and H4 confirmation due to their reliance on technical signals and clear exit rules.
• Day Trading and Scalping: These may require faster timeframes or tighter risk management, but with ATR and quick momentum indicators, they can be effective.
• Swing Trading and Position Trading: These will work well on higher timeframes (H1/H4), as they capitalize on medium- to long-term price movements.
• Breakout, News, and Retracement Trading: The success of these strategies will depend on volatility and momentum confirmation.
• Grid Trading: This is more mechanical and will require less signal-based input but can benefit from ATR or volatility-based indicators to avoid extreme market conditions.

By implementing these strategies and adjusting them with sequential optimization, you can test and refine how each approach behaves on various timeframes.