Optimise cTrader Backtest Settings in Xen

This guide explains how to optimise your cTrader backtest settings before using Xen to analyse the results. A structured optimisation process produces more reliable data and makes Xen’s analysis significantly more useful. Poor optimisation leads to misleading results, even if the report looks strong on the surface.

Video Guide

Tip: Set the video quality to HD (1080p) for the best viewing experience.

Why Optimisation Matters

Optimisation allows you to test different parameter combinations and evaluate how they affect performance under historical conditions. When used correctly, it helps you identify stronger settings, remove weak parameter ranges, and understand how sensitive your strategy is to changes. The resulting data provides a better foundation for Xen to analyse.

Before You Start

Before running optimisation, your strategy must already be stable. Optimising a broken or incomplete system will only produce misleading results.

Make sure your cBot:

• compiles successfully in cTrader Algo
• runs without runtime errors
• uses valid input parameters
• produces sensible results in a standard backtest

What to Optimise

Focus only on parameters that directly influence strategy behaviour. These typically include indicator settings, entry thresholds, and risk-related values.

Common examples include:

• indicator periods
• entry or exit thresholds
• stop loss and take profit values
• trade filters
• session or time-based conditions

Avoid selecting too many variables at once, as this makes the results harder to interpret.

Best Practice

A controlled approach produces more meaningful results. Start with a baseline and introduce optimisation gradually.

A typical process is:

1. Run a standard backtest on the baseline strategy
2. Select one to three important parameters
3. Run optimisation on those inputs
4. Review the strongest and most consistent ranges
5. Retest the best candidates
6. Export the final report for Xen analysis

This approach helps isolate meaningful improvements instead of generating noise.

Avoid Over-Optimisation

Over-optimisation occurs when a strategy is fitted too closely to historical data. This often produces strong backtest results that do not hold up in live trading.

Warning signs include:

• extremely high profit with unstable equity
• very narrow winning parameter ranges
• large performance differences between similar values
• strong results limited to a single time period

What to Look For

When reviewing optimisation results, focus on consistency and balance rather than maximum returns.

Key metrics to consider include:

• net profit
• drawdown
• profit factor
• number of trades
• consistency across parameter ranges

The objective is to find settings that are robust and repeatable, not just those that perform best under specific conditions.

Using Xen with Optimisation Reports

After completing optimisation, export the report and upload it into Xen for analysis.

Xen can help you:

• evaluate optimisation results
• identify weak or unstable settings
• compare parameter quality
• highlight potential overfitting
• suggest areas for improvement

The quality of the optimisation directly affects the value of the analysis.

Recommended Workflow

For consistent results, follow a structured process:

1. Build and validate a working baseline
2. Run a standard backtest
3. Optimise a small number of inputs
4. Review stable parameter ranges
5. Export the report
6. Upload the report into Xen

Related Guide

After optimisation, the next step is to generate and access the report correctly:

• How to Backtest and Access Reports

Final Advice