Invest with Code
Invest with Code
Goal
I built Invest with Code with two primary goals. First, to provide active investors with robust, intuitive market indicators, covering stocks, bonds, and commodities, helping them manage diversified portfolios. Second, we aim to teach programming enthusiasts how to replicate our strategies with Python, offering both basic and advanced methods in quantitative finance.
Challenges
A major challenge was integrating user management and subscriptions with Stripe, ensuring smooth transactions. When real money is involved the implementation has to be robust so users do not loose access to features they already paid for.
The project also needs seamless data integration between the python backend and the js frontend. The backend uses advanced data processing libraries like pandas, numpy and bayesloop and the frontend needs custom data visualisation tools to communicate the data to the customer.
I wrote a custom plotting library for this purpose to one the one hand reproduce matplotlib-like graphs on the frontend but still have extended interactivity for the user in the browser.
Implementation
Our dynamic portfolios are built with Bayesian statistics, adjusting weekly to market changes. Users can follow along by replicating these strategies with our built-in tools. The platform also includes a Python course for those interested in coding their own algorithms, making quantitative finance more accessible to a wider audience.