Company

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: The Golang-based application comprises core application GUI, which may be hosted separately, and is designed to operate in the low latency environment of a local network. Arbitrary event-driven show logic is supported via an internal scripting system. Rapidly changing data is cached externally (with Memcached) to prevent loss of state in the event the core application goes down.

Client: Technical Productions

Technologies: Golang, Echo, Javascript, MySQL, Memcached

Problem: A centralised piece of software is needed to coordinate sound, lighting and other IoT devices in interactive show venues.

Solution: Devices,  device commands, network setup, show "actions" and responses to events can all be defined by show operators to create arbitrary show scenarios. The software interfaces with popular software favoured for sound and lighting, and includes a versatile distributed dashboard scheme which allows custom dashboards to be created that can be hosted across multiple machines. 

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.