A custom trading app for testing and running a unique strategy

We developed a bespoke tool for trading algorithms that require more control than standard platforms allow.

Behind the idea

The global algorithmic trading market is projected to grow from $2.53 billion in 2025 to $4.06 billion by 2032, at a CAGR of 7%. As more players enter the market, trading strategies become more diverse. While many of these strategies can be tested on ready-made platforms, unique and constantly evolving algorithms often need a custom solution that offers full control over logic, data, and execution. That was exactly the approach our client took.

An independent trader had developed a proprietary trading algorithm and wanted to validate its performance on historical data. However, working manually offered no reliable way to measure results and increased the risk of errors. To address these limitations, the client decided to develop a bespoke solution to backtest, simulate, and run the algorithm in real market conditions.

For this, the trader needed a partner with proven expertise in building trading platforms. After reviewing our portfolio and discussing the concept with our engineers, the client endorsed our approach and decided to partner with EffectiveSoft.

Client
An individual trader
Country
The U.S.
Domain
Trading
Service
Desktop app development
Type of engagement
Time and materials

How we worked

We started with a discovery phase to gather requirements and clarify the underlying solution logic. Focused on usability, we designed a UI prototype to visualize how the user would set parameters; switch between testing, simulation, and trading modes; and review results.

As the project progressed, requirements continued to evolve as the trader introduced new ideas and adjustments to the algorithm. This is where our Agile processes proved essential, enabling our team to deliver incremental releases and implement updates while keeping the project on track.

Following this approach, we released an MVP in three months and then continued to extend the functionality of the solution over the next three years while the algorithm evolved.

What we built

We developed a standalone Windows app that allows users to find optimal strategy parameters for selected trading instruments and evaluate strategy performance. The solution integrates with Interactive Brokers (IB), providing access to both historical and real-time market data, as well as direct order management. This means the user can backtest their strategy on accurate tick-level and M1 data, monitor live price feeds, and make market orders inside the app. This integration enables the support of different types of trading assets, including stocks, forex, and ETFs.

Solution structure

The app is designed around three modes that cover key stages of strategy validation and execution:

Testing mode: The user selects historical data to backtest strategy parameters. The app simulates trades based on this data and displays results on a real-time chart.
Simulation mode: The app connects to a real-time data feed and simulates trades internally without sending any orders to the broker.
Trading mode: The app sends real market orders to IB, executing trades automatically or allowing the user to place and close orders manually.

Each mode provides a real-time, interactive chart and live updates on balance, profit/loss, and trade history.

Core features

The app includes the following features to facilitate strategy testing and trading:

Secure access: The app is password-protected and supports running multiple independent instances on the same or different machines. Each instance works with its own settings and broker credentials.
Multi-tab workspace: The user can run multiple tabs simultaneously with different instruments and parameters, with each tab supporting only one active order per instrument.
Customizable charts: The user can choose time frames (M1, M5, M30, H1, H4), switch chart type (line or mountain), and use zoom/pan.
Built-in data collection: If tick data is not available for download, the app collects and stores it during runtime, ensuring a reliable dataset for testing and analysis.

Automated trading software

Algorithmic trading software development allows financial institutions and professionals to successfully profit from a wider range of financial markets than would otherwise be possible. Using customized trading robots means a more consistent and efficient execution of proprietary strategies.

Result

Our client moved from manual trading to a controlled, automated platform that enabled strategy validation on historical data, secure real-time testing, and order execution directly through the app. The new workflow reduced the risk of human errors, minimized potential losses, saved time on routine operations, and provided a flexible framework for refining the trading algorithm.

The collaboration was equally valuable for our team, allowing us to strengthen our expertise in building such platforms and refine our Agile practices. This project demonstrated that even with a constantly evolving algorithm, it is possible to maintain steady progress and deliver a reliable solution.