Trading Automation System
An automated workflow for collecting market data, evaluating trading candidates, and executing defined strategies through an engine.
About the system
This project connects the stages of a trading workflow: collecting information from data providers, processing and analysing that information, identifying candidates based on predefined criteria, and passing decisions to an execution engine.
Our role
We designed and implemented the automated data and decision pipeline, from external market-data ingestion through candidate analysis and strategy execution.
How we approached it
The workflow was separated into acquisition, normalisation, analysis, signal selection, and execution stages. Python services connected to external APIs, Pandas and NumPy handled structured market information, and the execution layer transformed validated strategy decisions into orders while keeping each stage independently observable.
Technology context
The system uses Python, Pandas, NumPy, and external APIs to coordinate data processing and strategy execution.
This is one of our own products or internally developed projects.