Feature: Advance Trading Strategies

Supported Trading Sequences

Here is a breakdown of the strategy options available:

,
Strategy Description
1. No Strategy Default mode. Bot trades with a fixed size; no sequence is applied.
2. Martingale Increases trade size after a loss to recover previous losses. Resets on win.
3. Reverse Martingale Increases trade size after a win to capitalize on streaks. Resets on loss.
4. Fibonacci Follows the Fibonacci sequence to increase size after losses, decrease after wins.
5. Reverse Fibonacci Follows Fibonacci logic but increases size on wins and reduces on losses.
6. 3-2-6-3 / Reverse A cyclic strategy based on pre-defined 3-2-6-3 bet sizing. Reverse mode flips logic.
7. D’Alembert / Reverse Increases size linearly after losses, decreases after wins. Reverse mode inverts this.

How It Works

  • You select the preferred strategy at the bot configuration level.
  • ot adjusts next trade size based on the result of the previous trade:
    • Win → Reset or increase (depends on strategy).
    • Loss → Increase or decrease (depends on strategy).
  • Sequence management is automatic and works in the background—no manual tracking needed.
  • Strategies can be applied per symbol or via global bot strategy templates.

Why Use Trading Sequences?

These methods are time-tested money management systems used by traders and gamblers alike for centuries. Their purpose is to optimize risk exposure, recover drawdowns, or amplify gains in trending conditions.

Benefits of Advanced Trading Strategies

1. Profit Optimization

Reverse Martingale and Reverse Fibonacci help maximize gains during winning streaks, allowing you to capitalize when your strategy is aligned with the market.

2. Loss Recovery

Strategies like Martingale, Fibonacci, and D'Alembert help recover from losing trades by scaling position sizes appropriately, aiming to turn a profit on the next trade.

3. Smart Risk Distribution

By automating trade size adjustments, the bot reduces your reliance on emotional or random position sizing decisions.

4. Drawdown Management

Algorithms like D’Alembert provide more gradual recovery, ideal for avoiding the high-risk exposure of pure Martingale while still managing drawdowns effectively.

5. Behavioral Discipline

Forces a rule-based approach to capital allocation—preventing overleveraging and impulsive decision-making.

6. Cycle-Based Recovery & Expansion

Cyclical patterns like 3-2-6-3 provide a balanced rhythm of trade sizing that performs well in range-bound markets.

7. Easy Integration with Other Features

Seamlessly combines with:.

  • Trade Condition Groups
  • Smart Stop-Loss
  • Cooldowns
  • Symbol Templates
  • Trailing Profits

Use Case Scenarios

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Strategy Best For
Martingale Short-term recovery in mean-reverting markets
Reverse Martingale Trend trading and momentum strategies
Fibonacci Controlled risk recovery with gradual scaling
3-2-6-3 Balanced sizing in uncertain or sideways markets
D’Alembert Conservative capital recovery with reduced risk

Real-World Example

You configure Fibonacci Strategy for BTC/USDT:

  • 1st trade: Loss (position size: $10)
  • 2nd trade: Loss (size: $10 → $20)
  • 3rd trade: Win (size: $20 → $10 based on sequence step back)
  • Result: Position sizes adapt dynamically while minimizing the risk of overexposure.

Risk Note

  • Always configure trade rules, conditions, and cooldown settings for each individual symbol.
  • Define clear stop-loss and take-profit levels to protect your capital and lock in profits.
  • Ensure your strategy has a realistic 50%+ win rate over time to maintain a positive expectancy.
  • Use the built-in strategy building and backtesting tool to test your setups against historical data.
  • Start with demo trading before applying strategies to live markets, especially for aggressive patterns like Martingale.

Statistical Edge

With proper configuration and market-aligned strategies, using trading sequences can reduce the long-term chance of unrecoverable loss to <5%, especially when combined with:

  • Volatility filtering
  • Symbol-specific tuning
  • Market condition awareness

Summary

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