Untangled Processes: Stock Exchange Trading Bot Automation

We’ve created a desktop application that ingests market data, visualizes indicators in a live dashboard, and interacts with the broker API. A built-in trading bot searches for opportunities and places orders according to a defined strategy and risk limits for the optimal results.

Our client operated a successful trading platform, but it drained lots of resources to maintain and scale, reducing ROI. That’s why we were asked to cut operational risk, streamline workflows, control API costs, and give traders a transparent, responsive interface.

The team composition varied from 2 to 6 specialists across engineering, data analytics, and trading advisory.

Throughout the work process, we’ve faced the following limitations and found new ways to overcome them:

• Limited market-data expertise: While the client’s team had strong trading knowledge, they lacked experience with large volumes of streaming market data. That’s why they needed our help to automate Microsoft Excel datasheets and embed best practices for data validation, normalization, and historical tracking.
• Slippery ground for fast decisions: To make data-driven decisions, the client needed normalized, auditable analytics. The client’s current tools were primarily based on manual processing and scattered datasheets, which affected decision-making.
• Operational challenge: Careful planning was vital for a smooth transition from outdated Excel/C++ tools to a unified C# desktop application, preventing downtime and offering traders a quicker, more seamless user experience.

C#, .NET for the desktop interface, SQL for storage and aggregation, and a REST-based broker API integration.

All requirements and challenges combined, we’ve delivered a comprehensive solution to gather stock exchange data, analyze trends and portfolios, and buy and sell stocks within the predetermined strategy.

We’ve re-implemented critical Excel/C++ utilities in C# and united them with a bot under a single desktop UI with a real-time dashboard and persisted stock snapshots. The full functionality included the following features and options:

• extracting data about indexes from the platform,
• market analysis for trends and stock portfolio,
• interpreting and visualizing results on real-time dashboards,
• the trading bot has scanned the stocks in the market and analyzed them for further purchase,
• stock operations under a defined market strategy.

To guarantee data integrity, transparency, and complete traceability for each trade and analytical snapshot, we have constructed a single data pipeline with standardized schemas and SQL-based storage.

With a shorter data-to-action time, the team replaced manual, error-prone stages with a solid, traceable workflow. The economic metrics were related directly to the API price, enabling effective and low-maintenance results.