Company

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.

System: Web application to display an interactive 3D animation of a truck loading a specified shipment

Client: Private

Technologies: .NET core, C#, Blender, Three.js, SQL

Problem: Create a web application which loads details of a user-specified shipment from a database, and depicts that shipment loading in a user-interactive animation.

Solution: This project integrates a number of separate areas of software engineering, including web development, 3D modelling and dynamic animation. The truck trailer with backgrounds and skybox were modelled in Blender, together with the Cargo bay and truck door opening animations - and these were imported into Three.js. Camera zoom and rotation were enabled using OrbitControls.js. The cargo box loading animation was created in Three.js directly using suitable vector mathematics, and the system mounted in a .NET core based framework. Specification of the shipment to load is provided by the user via a web form.

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.