Long-Short Fund Trading Algorithm Solution
Long-Short trading strategies are the backbone of many investment managers and traders. An Edge Financial Technologies client requested assistance in improving their investment strategies. The objectives were to:
- Integrate all order flow and market data with Interactive Brokers
- Provide Self-Learning automation where algos could provide more buying power and preference to the strategies making money at that time.
- Provide backtesing and forward testing so that data scientists and traders could have a research environment for improving the algorithms
- Provide 15 years of historical data with a growing list of proprietary statistics and attributes on each symbol.
- Keep technology costs low for both the project and the long term
Issues with Vended Solutions
The client had reviewed a number of vended full solutions. However they found that the access and maintenance of historical data, the tools needed by the data science team, and the traders did not fit very well into any single solution. The first alternative was to look to utilizing multiple solutions. While this was feasible, the cost, especially long term operation costs, were prohibitive.
Edge Financial Technologies possesses the industry knowledge, technical knowledge, and starting components that were able to be brought to the project. These starting components allowed the Long-Short proprietary trading group to behave as if they had their own dedicated IT software engineering team.
- Edge Market Simulation Tool
- Edge Algo Framework
- Edge Interactive Broker API working examples
- Edge Market Data Programming Libraries
- Edge Historical Market Data Framework
- Third Party historical 1 minute bar tick data on 500 + symbols
- Microsoft Azure cloud based servers and databases
Two months after beginning the project with two consultants, the first components of the system went into production. While the traders used this early version to track algo performance the engineers completed the remaining software required to complete the project. The entire project was completed in six months.
At the time that this case study was written the client has been using the full system for over six months. Edge Financial Technologies provides level three support for the client but has been rarely ever called.
The client is trading with their own proprietary algorithms.