From MetaTrader to cTrader: how John rebuilt his trading bots for C#
cTrader’s native C# support, modern development tools and built-in cloud infrastructure made moving from MetaTrader a natural choice for John. See how he rebuilt his trading products for cTrader and what stood out along the way.
Moving an established trading product to a new platform doesn’t necessarily mean simply translating the existing code. For John, a Senior Software Engineer with more than 20 years of experience, bringing his algorithmic trading systems from MetaTrader to cTrader became an opportunity to rethink their architecture and build around C# and cTrader’s native capabilities.
We spoke with John about why he decided to expand to cTrader, how he approached the migration and what other developers considering the same move can learn from his experience.
Inspired by John’s story?
If his journey inspired you, discover how you can become a seller on cTrader Store and start building your own story.
From enterprise software to algorithmic trading
John’s background in software development goes back more than two decades. As a Senior Software Engineer, he has spent over 20 years building enterprise distributed systems.
His journey into trading started later. He began trading Forex and CFDs casually in 2018 and started automating his own strategies around three years ago.
What initially began as tools for his own trading gradually developed into commercial algorithmic trading systems.
Why cTrader made sense for a .NET developer
For John, one of the main reasons to bring his products to cTrader was straightforward: C#.
As an experienced .NET engineer, he found cTrader’s native C# support a natural fit for his existing development experience. It also meant he could work with familiar industry-standard development tools.
“Developing for cTrader is a much smoother experience. The biggest difference is developer freedom - you can work within industry-standard IDEs like Visual Studio alongside full modern C# tooling, rather than being restricted to a proprietary environment.”
The platform itself also played a role in his decision. John highlights cTrader’s clean UI and built-in cloud infrastructure as important advantages, particularly because traders can run cBots in the cloud without relying on a separate VPS.
Together, these factors made expanding his products to cTrader an easy decision.
More than a line-by-line port
John didn’t approach the move to cTrader as a simple code conversion.
He kept the underlying trading strategies but redesigned the product architecture to take advantage of C# and cTrader’s native features.
“It was a blend of both. While I preserved the core underlying trading strategies, I completely redesigned the product architecture to take full advantage of C# capabilities and cTrader’s native features rather than performing a line-by-line port.”
That process also came with structural challenges. Instead of trying to reproduce the previous architecture exactly, John rebuilt it from the ground up using Clean Architecture, SOLID principles and Domain-Driven Design (DDD).
Market analysis, execution and risk management were decoupled into separate parts of the system. According to John, this resulted in an architecture that is easier to maintain and extend.
Inspired by John’s story?
If his journey inspired you, discover how you can become a seller on cTrader Store and start building your own story.
Building an adaptive cBot for changing markets
On cTrader Store, John has consolidated the core strengths of his strategies into an adaptive hybrid cBot engine.
The system uses dynamic regime detection to adapt to changing market conditions. Its purpose is to address a common problem with rigid automated strategies: performance can change when market volatility and conditions shift.
For traders discovering John’s work for the first time, he recommends XauUsdUltimateBot_AI.
Designed specifically for XAU/USD (Gold), the cBot uses an adaptive filtering approach and comes pre-trained to identify and avoid high-risk setups. It also learns from live trade outcomes. While it is tuned for Gold, John says its core engine can be optimised for other assets.
A different marketplace audience
John has also noticed differences between traders using MetaTrader and cTrader.
In his experience, the cTrader community tends to be more analytical when evaluating automated trading products.
“The cTrader community tends to be more sophisticated and analytical. Traders on cTrader generally look past over-optimized backtests that fail in live conditions; instead, they prioritize clean execution, sound risk management, and forward-tested performance.”
For sellers, this can influence not only how a product is developed but also how it is presented. John’s experience suggests that demonstrating how a system behaves beyond an optimised backtest can matter to this audience.
His experience with cTrader Store
So far, John’s experience publishing on cTrader Store has been positive.
One aspect that particularly stood out to him is how product visibility works. In his experience, new sellers and products have an opportunity to reach traders rather than visibility being concentrated among an established group of sellers.
“The cTrader Store maintains a level playing field where visibility is merit-driven rather than dominated by a fixed set of sellers, allowing quality products an equal opportunity to reach traders.”
For a developer expanding from another platform, that gives new products an opportunity to build their presence on cTrader Store.
Inspired by John’s story?
If his journey inspired you, discover how you can become a seller on cTrader Store and start building your own story.
What’s next
John isn’t stopping with his current cBot.
Several new strategy models are already in development. Before releasing them, his process includes backtesting, optimisation and live forward testing.
Once those stages are complete, he plans to bring the new strategies to cTrader Store.
His experience moving from MetaTrader to cTrader shows that migration doesn’t have to mean recreating the same product on another platform. For experienced developers, it can be an opportunity to keep the strategy that already works while rebuilding the software around a modern C# development environment and cTrader’s native capabilities.
If you’ve already built trading algorithms for another platform, John’s approach offers one possible path: preserve what matters, rethink what can be improved and build for cTrader rather than simply porting to it.
Aisylu Chanysheva
Aisylu Chanysheva
Sofia Savchenko
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