The client was experiencing slow manual trade decisions, lack of backtesting validation, and inconsistent execution due to human bias and fragmented toolsets. This led to suboptimal trade entries and higher operational risk.
Vedatron performed trading requirement analysis and integrated market data feeds for real-time decisions. We designed low-latency execution pipelines and developed a backtesting framework for historical strategy validation. Risk management modules were embedded to prevent over-exposure and execution errors.
We delivered a Python-based automated trading engine with real-time data feeds, broker connectivity, flexible strategy templates, and risk management. The system employs quantitative logic, automated execution rules, and performance dashboards. Backtesting modules allow scenario evaluation before live deployment.
Let’s build a scalable and performance-driven solution for your organization.
Start Your Project →