Company

System: Web Based Trading Robot

Client: Private

Technologies: Python, Asyncio, Selenium, Headless Chrome, WebSockets

Problem: Requirement to automate a specific trading strategy on a target trading platform

Solution: The interface with the target platform is made with headless Chrome controlled via Selenium. Information such as asset price and order book changes are tracked by inspecting the websocket connection; trades are automatically placed using custom web automation methods when a set of user defined criteria are met.

System: Stock price history pattern matching utility

Technologies: Python (asyncio matplotlib mplfinance pandas...)

Problem: Build a system which identifies stocks that are currently in the process of repeating previously observed price history patterns, based on low-high and high-low trend time intervals.

Solution: Our solution involves iterative analysis of a large large database of stocks, gathered from web sources. Price histories are divided into progressively smaller time period bins, with duration labelled the "granularity" of the iteration. The pattern of trends across bins is compared with recent price movements to identify matching segments. We then used a visualisation system based on Japanese "renko" diagrams to depict matches in an easy-to-digest format.

Note this is a bespoke system created upon request; we provided no advice on stock selection methods.

System: A utility to accurately extract financial information from company financial statements in arbitrary format. Specific details are subject to NDA.

Client: Protected by NDA

Technologies: Raku, Python

Problem: The arbitrary format of company financial statements presents a problem for automated analysis

Solution: Our solution takes advantage of the standard accounting terms classification system as well as known financial mathematical relationships to produce output above a certain desired accuracy threshold. Specific details are NDA protected.