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By merging these trading strategies with your specifications, you’ll create a highly adaptable system that should perform well across different market conditions. Would you like to test this setup with a focus on any particular method or combination first? ———— make 1 of random uniqe and exotic trading style

Here’s an exotic and unique trading strategy that merges multiple aspects of traditional techniques but with an unconventional twist:

“Harmonic Grid Momentum Breakout”

Concept: This strategy combines the principles of grid trading, harmonic patterns, and momentum breakouts. The goal is to capture both trending and ranging market conditions while managing risk dynamically. It thrives on detecting strong directional moves and harmonic reversals, using grid placement to capture both breakouts and retracements.

Key Components:

1. Grid Trading Layer:
   • A grid of orders is placed at regular intervals above and below the current price, with a predetermined spacing (e.g., 10 pips).
   • The grid can be expanded dynamically based on market volatility using ATR.
   • If price moves into a trending market, breakouts are captured, while in ranging conditions, price oscillations fill and close the grid orders profitably.
2. Harmonic Pattern Recognition:
   • The strategy identifies harmonic patterns (e.g., Gartley, Bat, Butterfly) using Fibonacci retracements and extensions.
   • When a pattern completes, it signals a reversal or continuation of the trend.
   • Entry orders are placed based on the harmonic reversal points, with grids enhancing profit capture from both retracement and continuation.
3. Momentum Confirmation (RSI + MACD):
   • RSI is used to confirm momentum. If RSI > 70, look for shorting opportunities; if RSI < 30, look for buying opportunities.
   • MACD crossover signals trend strength and confirms breakout conditions. If the MACD lines cross and the grid captures the breakout, positions are allowed to ride the momentum.
4. Dynamic Risk Management:
   • Trailing Stop: Adjusts dynamically based on ATR, ensuring profits are locked in while allowing the trade to run.
   • Break-even Stop: Once price moves halfway to the profit target, the stop loss moves to break even, ensuring no loss on that trade.
5. Weekly Market Reset:
   • All open trades are closed by the end of the trading week, ensuring no positions are held over the weekend to avoid gaps.
   • The grid resets at the beginning of the new week with fresh levels based on the week’s opening volatility.

Trading Conditions:

• Timeframes: H1 for main signal entries, H4 for confirming harmonic patterns and momentum direction.
• Market: Gold (XAU/USD).
• Lot Sizing: 0.01 lot per $100 of the account balance, with risk managed by risk percentage of total capital (as per your initial design).
• Risk/Reward Ratio: Aimed at 1:3 or higher.

How It Works:

1. Setup Phase: The grid is initialized with buy and sell orders at regular intervals.
2. Harmonic Detection: As the market moves, harmonic patterns are identified, and additional grid orders are aligned to these patterns, looking for precise reversals.
3. Momentum Confirmation: If the market shows momentum through RSI and MACD crossovers, additional positions are opened based on the breakout strength.
4. Profit Capture: As price fluctuates within the grid, orders are closed for profits. If momentum is strong, the trailing stop secures profits as the price trends.

Exotic Edge:

• Multi-Layer Strategy: This strategy captures both ranging and trending conditions. The harmonic patterns add precision, while the grid ensures profits from oscillations, and momentum ensures strong breakouts are capitalized on.
• Versatile Profit Capture: Whether the market moves wildly or remains calm, this strategy can adapt, always seeking opportunities across multiple layers.

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.

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.

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.

do it your best with my need to build on main TF H1, sub chart H4. H1 for active signal H4 for confirmation. basse on 0.01 : 100$ and Risk % on account.

To build your strategy in StrategyQuant X with the main TF (H1) for active signals and H4 for confirmation, along with risk management based on 0.01 lots per $100 balance and a percentage-based risk, here’s an optimal setup.

1. Timeframe Setup:

• Main Timeframe (H1): This will be the active trading timeframe where signals are generated and trades are executed.
• Sub-chart Timeframe (H4): This higher timeframe will be used to confirm the direction of the trend before executing trades on the H1 chart.

2. Signal and Confirmation Logic:

• H1 (Active Timeframe):
  • Use indicators like Moving Average (MA), RSI, or MACD for generating buy/sell signals.
  • For example:
    • Buy Signal: Price crosses above the 50-period Moving Average (MA).
    • Sell Signal: Price crosses below the 50-period Moving Average (MA).
• H4 (Confirmation Timeframe):
  • This timeframe will confirm the trend direction before executing trades.
  • Confirmation example:
    • Only buy if the 200-period MA on H4 is pointing upwards.
    • Only sell if the 200-period MA on H4 is pointing downwards.

3. Position Sizing:

• For position sizing, your specification is to trade 0.01 lots per $100 of balance. To implement this:
  • Set the lot size based on account balance: Use a custom rule in StrategyQuant that dynamically calculates lot size.
  • For every $100 in balance, set lot size = 0.01.
  • Risk Percentage: Use the account balance and risk percentage to calculate the stop loss based on the total risk per trade.
    • Example: If risk per trade is 1%, on a $100 account, this equals $1 risk. The stop loss distance should be calculated based on the value of 0.01 lots.

4. Exit Strategies:

Combine different exit strategies to close trades frequently while maintaining profitability:

• Trailing Stop:
  • Set a trailing stop that follows the price as it moves in favor of your trade. This will ensure that you secure profits when the price reverses slightly.
  • Trailing Activation: Activate the trailing stop after a certain number of pips in profit.
• Profit Target:
  • Set a modest profit target that can be hit frequently. Given gold’s volatility, a reasonable target might be 20-50 pips, but you can optimize this during backtesting.
• Stop Loss:
  • Calculate stop loss based on the percentage risk setting. For example, if you are risking 1% of the account per trade, the stop loss should reflect this value based on the lot size and account balance.
• Exit After Bars:
  • You could add a rule to exit the trade if it hasn’t hit the profit target or stop loss within a specific number of bars (e.g., after 50 bars on H1).
• Exit Rule:
  • Use a custom indicator or logic for additional precision. For example, exit trades if the RSI is overbought/oversold on H1, or when the MACD histogram flips direction.

5. Risk Management:

• Risk % on Account:
  • Set a risk percentage (e.g., 1% or 2%) for each trade. This will limit the amount of capital you are risking on each position.
  • This can be implemented in StrategyQuant X by setting the risk to a fixed percentage of the account balance for each trade. The software will adjust the stop loss distance or position size accordingly.
  • Leverage: Ensure that leverage is factored in, especially with volatile assets like gold.

Example Strategy Steps in StrategyQuant X:

1. Entry Conditions:
   • H1: Enter a long trade when the price crosses above the 50-period MA, and the RSI is above 50 (indicating upward momentum).
   • H4: Confirm the trade only if the 200-period MA is sloping upwards (trend confirmation).
2. Exit Conditions:
   • Exit when the trailing stop is hit.
   • Exit when the profit target (e.g., 30 pips) is hit.
   • Exit after 50 bars if none of the other exit conditions are met.
3. Position Size:
   • Set 0.01 lots per $100 balance.
   • Risk 1-2% of the account balance on each trade.
4. Backtesting & Optimization:
   • Run the strategy through backtests on historical data for gold to optimize parameters like:
     • Profit target and trailing stop distance.
     • Moving average periods (e.g., experiment with 20, 50, 200 MA).
     • Risk percentage.
   • Use Monte Carlo simulations to assess how the strategy performs under different market conditions.