Vortex Trend Capture Trading Strategy with ATR Trailing Stops

This article describes a professional trend-following trading strategy implemented in Backtrader that uses the Vortex Indicator to identify trend signals, filtered by a long-term moving average and a volatility condition. The strategy employs ATR-based trailing stops to manage risk and capture profits during sustained trends.

Strategy Overview

The Vortex Trend Capture Trading Strategy integrates the following components:

• Vortex Indicator: Uses a 30-day period to measure bullish (VI+) and bearish (VI-) trend strength, with crossovers signaling potential trend changes.
• Long-Term Trend Filter: Employs a 30-day Simple Moving Average (SMA) to ensure trades align with the prevailing trend direction (price above SMA for buys, below for sells).
• Volatility Filter: Requires the 7-day Average True Range (ATR) to be less than 5% of the current price to avoid trading in excessively volatile conditions.
• ATR Trailing Stops: Sets dynamic stop-loss levels using a 7-day ATR multiplied by 3.0, updated based on the highest/lowest price since entry for long/short positions.
• Position Management: Ensures no new trades are placed when an order is pending, maintaining disciplined execution.

Code Implementation

Below is the complete Backtrader code for the strategy:

import backtrader as bt

class VortexTrendCaptureStrategy(bt.Strategy):
    """
    A professional trend-following system that uses the Vortex Indicator for entry
    signals, filtered by a long-term MA and a volatility condition.
    """
    params = (
        # Vortex Indicator
        ('vortex_period', 30),
        # Macro Trend Filter
        ('long_term_ma_period', 30),
        # Volatility Filter
        ('atr_period', 7),
        ('atr_threshold', 0.05), # Max ATR as % of price to allow trades
        # Risk Management
        ('atr_stop_multiplier', 3.0),
    )

    def __init__(self):
        self.order = None

        # --- Indicators ---
        self.vortex = bt.indicators.Vortex(self.data, period=self.p.vortex_period)
        self.long_term_ma = bt.indicators.SimpleMovingAverage(self.data, period=self.p.long_term_ma_period)
        self.atr = bt.indicators.AverageTrueRange(self.data, period=self.p.atr_period)

        # Crossover for the Vortex signal
        self.vortex_cross = bt.indicators.CrossOver(self.vortex.lines.vi_plus, self.vortex.lines.vi_minus)

        # --- Trailing Stop State ---
        self.stop_price = None
        self.highest_price_since_entry = None
        self.lowest_price_since_entry = None

    def notify_order(self, order):
        if order.status in [order.Submitted, order.Accepted]: 
            return
        if order.status in [order.Completed]:
            if self.position and self.stop_price is None:
                if order.isbuy():
                    self.highest_price_since_entry = self.data.high[0]
                    self.stop_price = self.highest_price_since_entry - (self.atr[0] * self.p.atr_stop_multiplier)
                elif order.issell():
                    self.lowest_price_since_entry = self.data.low[0]
                    self.stop_price = self.lowest_price_since_entry + (self.atr[0] * self.p.atr_stop_multiplier)
            elif not self.position:
                self.stop_price = None
                self.highest_price_since_entry = None
                self.lowest_price_since_entry = None
        self.order = None

    def next(self):
        if self.order: 
            return

        if not self.position:
            # --- Filter Conditions ---
            # 1. Is market volatility stable?
            is_stable = (self.atr[0] / self.data.close[0]) < self.p.atr_threshold
            # 2. Is price aligned with the macro trend?
            is_macro_uptrend = self.data.close[0] > self.long_term_ma[0]
            is_macro_downtrend = self.data.close[0] < self.long_term_ma[0]
            # 3. Has a Vortex crossover signal occurred?
            is_buy_signal = self.vortex_cross[0] > 0
            is_sell_signal = self.vortex_cross[0] < 0

            # --- Entry Logic ---
            if is_stable and is_macro_uptrend and is_buy_signal:
                self.order = self.buy()
            elif is_stable and is_macro_downtrend and is_sell_signal:
                self.order = self.sell()
                
        elif self.position:
            # --- Manual ATR Trailing Stop Logic ---
            if self.position.size > 0: # Long
                self.highest_price_since_entry = max(self.highest_price_since_entry, self.data.high[0])
                new_stop = self.highest_price_since_entry - (self.atr[0] * self.p.atr_stop_multiplier)
                self.stop_price = max(self.stop_price, new_stop)
                if self.data.close[0] < self.stop_price: 
                    self.order = self.close()
            elif self.position.size < 0: # Short
                self.lowest_price_since_entry = min(self.lowest_price_since_entry, self.data.low[0])
                new_stop = self.lowest_price_since_entry + (self.atr[0] * self.p.atr_stop_multiplier)
                self.stop_price = min(self.stop_price, new_stop)
                if self.data.close[0] > self.stop_price: 
                    self.order = self.close()

Strategy Explanation

1. VortexTrendCaptureStrategy

The strategy uses the Vortex Indicator with trend and volatility filters to trade trend changes:

• Indicators:

  • Vortex Indicator: Calculates bullish (VI+) and bearish (VI-) trend strength over a 30-day period, with crossovers indicating potential trend shifts (VI+ crossing above VI- for bullish, below for bearish).
  • Long-Term MA: A 30-day SMA to filter trades in the direction of the macro trend (price above SMA for buys, below for sells).
  • ATR: A 7-day Average True Range to assess volatility and set trailing stop levels.
  • Vortex Crossover: Uses Backtrader’s CrossOver indicator to detect when VI+ crosses above (buy signal) or below (sell signal) VI-.

• Trading Logic (next):

  • Pending Order Check: Skips trading if an order is pending to avoid overlapping trades.
  • Filter Conditions:
    • Volatility Filter: Ensures the ATR is less than 5% of the current price, avoiding excessively volatile conditions.
    • Trend Filter: Requires the price to be above the 30-day SMA for buy signals or below for sell signals.
    • Vortex Signal: Detects a buy signal when VI+ crosses above VI- (positive crossover) or a sell signal when VI+ crosses below VI- (negative crossover).
  • Entry Conditions:
    • Bullish Entry: Enters a buy order if volatility is stable, the price is above the long-term MA, and a Vortex buy signal occurs.
    • Bearish Entry: Enters a sell order if volatility is stable, the price is below the long-term MA, and a Vortex sell signal occurs.
  • Trailing Stop Logic:
    • For long positions: Updates the stop to the highest price since entry minus 3 times the ATR, ensuring the stop moves up with favorable price action. Exits if the price falls below the stop.
    • For short positions: Updates the stop to the lowest price since entry plus 3 times the ATR, ensuring the stop moves down with favorable price action. Exits if the price rises above the stop.
  • Position Check: Only enters trades if no position is currently held, ensuring one trade at a time.

• Order Management (notify_order):

  • Ignores submitted or accepted orders, resetting the order tracker when completed.
  • Sets the initial trailing stop upon trade execution:
    • For long positions: Sets stop as the entry high minus 3 times ATR.
    • For short positions: Sets stop as the entry low plus 3 times ATR.
  • Resets stop and price tracking variables when the position is closed.

Key Features

• Vortex Trend Detection: Uses the Vortex Indicator to identify trend changes based on directional movement, capturing strong trends.
• Trend Alignment: Filters trades with a 30-day SMA to ensure alignment with the macro trend, reducing counter-trend trades.
• Volatility Filter: Limits trading to stable volatility conditions (ATR < 5% of price), avoiding erratic market moves.
• ATR Trailing Stops: Dynamically adjusts stop-loss levels based on volatility, protecting profits while allowing trades to follow trends.
• Disciplined Execution: Prevents multiple simultaneous positions or overlapping orders, maintaining clear trade logic.

Potential Improvements

• Parameter Tuning: Adjust vortex_period, long_term_ma_period, atr_period, atr_threshold, or atr_stop_multiplier to optimize for specific assets or market conditions.
• Additional Filters: Incorporate volume or other momentum indicators (e.g., MACD, RSI) to further confirm trend signals.
• Fixed Stop-Loss: Add a fixed stop-loss alongside trailing stops for additional risk control.
• Performance Metrics: Include analyzers for returns, Sharpe ratio, drawdown, and trade statistics to evaluate strategy effectiveness.
• Multi-Asset Testing: Apply the strategy to multiple assets to assess performance across different markets.

This strategy is designed for trending markets where the Vortex Indicator can effectively capture directional moves, suitable for assets like forex, stocks, or cryptocurrencies, and can be backtested to evaluate its effectiveness across various timeframes and assets.