Build a strategy in StrategyQuant X

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.