Business Case Context
The Argentine market presented many inefficiencies in pricing, allowing traders to take advantage of them by buying and selling financial instruments to earn a small spread on each transaction. I noticed that these actions were primarily done manually, and the inefficiencies persisted for a considerable amount of time in the market. During that period, political leaders were introducing several changes on a daily basis, making it difficult for brokers to stay updated on these developments. As a result, brokers were not able to keep track of all these changes consistently.
Since I was proficient in Python, which was not very common at the time, I began developing these algorithms that were extremely innovative. This enabled my company to capitalize on these opportunities. This initiative was key to my professional growth, leading me to take on leadership roles in the trading desk and later in the Business Intelligence team that I managed.
Find this project on my GitHub repository.
Note: This repo contains only files related to this specific objective and may lack the higher-level engine, as these resources were part of a larger software system I created. The purpose of this repo is not to provide a ready-to-use solution but to demonstrate my ability to build software relevant to its title.
Resources Used
- REST APIs
- Scheduling
- Tkinter
- Websockets
- Notify (push notifications to my mobile phone)
- Multithreading management (actually multiprocessing + Pools, Queues, Locks & Memory management)