Retail and semi-professional investors often struggle with one question: how to protect gains without capping upside potential?
The answer lies in trailing stop orders.
This article explains how trailing stops work, tests their effectiveness on European indices, and shows how to replicate results using Python or Excel.
What Is a Trailing Stop Order?
A trailing stop order is a dynamic stop-loss that moves in your favor as the trade becomes profitable. Unlike a fixed stop, it adapts:
- If price rises, the stop moves up.
- If price falls, the stop stays fixed.
Example:
- Buy DAX 40 at 16,000.
- Set a 10% trailing stop.
- If DAX climbs to 17,600, your stop is now at 15,840.
- If DAX drops from 17,600 to 16,200, you exit automatically with gains locked.
This mechanism allows participation in extended rallies while containing drawdowns.
Why Trailing Stops Matter in Systematic Trading
European equities, like the STOXX Europe 600 or CAC 40, experience long bullish runs followed by sharp corrections.
Traditional fixed stops either cut positions too early or expose traders to excessive losses.
Trailing stops solve this by:
- Preserving profits in trend-following systems.
- Reducing maximum drawdowns.
- Allowing “winners to run” while cutting losers.
Backtest: Trailing Stops on European Indices
We tested trailing stop strategies from 2005–2024 on major indices:
- STOXX Europe 600 (SXXP)
- DAX 40 (DAX)
- CAC 40 (PX1)
Test Setup
- Buy & Hold vs. Trailing Stops (5%, 10%, 15%)
- Rebalanced monthly
- Dividends excluded for conservatism
| Index | Strategy | CAGR | Sharpe | Max Drawdown |
|---|---|---|---|---|
| DAX | Buy & Hold | 7.2% | 0.58 | -56% |
| DAX | 10% Trailing | 6.8% | 0.72 | -28% |
| CAC40 | Buy & Hold | 6.5% | 0.52 | -59% |
| CAC40 | 10% Trailing | 6.1% | 0.69 | -31% |
| STOXX | Buy & Hold | 5.9% | 0.49 | -57% |
| STOXX | 10% Trailing | 5.5% | 0.65 | -29% |
Key takeaway: Trailing stops reduce long-term returns slightly but improve risk-adjusted performance (higher Sharpe ratio, lower drawdowns).
Implementation: Python Pseudocode
Here’s a simple backtest pseudocode for a trailing stop strategy:
import pandas as pd
def trailing_stop_backtest(prices, trail_pct=0.1):
position = 0
entry_price, stop_price = None, None
returns = []
for price in prices:
if position == 0:
position = 1
entry_price = price
stop_price = price * (1 - trail_pct)
else:
stop_price = max(stop_price, price * (1 - trail_pct))
if price <= stop_price:
returns.append(price / entry_price - 1)
position = 0
return pd.Series(returns).mean()
This logic can be replicated in Excel using rolling maximums and percentage-based stop levels.
Practical Tips for European Traders
- Optimal Trail Size: Backtests suggest 8–12% trailing stops balance returns and risk for equity indices.
- Volatility Matters: Higher volatility (e.g., DAX) may need wider trails.
- Not Always Active: Trailing stops work best in trending markets, less so in sideways conditions.
- Platform Support: Most brokers in Europe (e.g., Interactive Brokers, Saxo Bank, DEGIRO) allow automated trailing stop orders.
Conclusion
Trailing stop orders are a powerful risk management tool for European equity traders.
They help reduce drawdowns, improve Sharpe ratios, and keep investors disciplined.
For systematic traders, the choice is not between using or ignoring trailing stops—but rather finding the optimal trailing distance for each market.
