Environmental, Social, and Governance risks are increasingly driving and guiding investments, but much of investment remains out of reach for the vast majority of Americans. Jasmine aims to solve this disparity by helping Americans invest simply in stocks, bonds, and cryptocurrencies that align with their personal values. Our naming was very much inspired by Blackrocks Aladdin API
What it does
Jasmine helps individuals invest using historical data, personal values, and an algorithmic recommendation system. We also provide simple and intuitive predictions for stock and crypto prices based on Neural Prophet (machine learning). We use consensus mechanisms to inform and educate our users about crypto ESG concerns.
How we built it
Jasmine was built using Python, Flask, React.js, Google BigQuery, and DataWrapper. We pull data from polygon.io, kaggle, and other historical stock sources.
Challenges we ran into
Finishing an investment platform in 24 hours is difficult even with a fantastic team. Building the front-end work, back-end API, data visualization, and machine learning components was a challenge. Putting those pieces together pushed all of our abilities to the maximum.
Accomplishments that we're proud of
A functional prototype of simple investing putting our future first with ESG. Our algorithm weights performance and values almost equally with emphasis on what the individual believes in.
What we learned
How to take domain knowledge and translate it into a simple to use interface for the everyman/everywoman. It's easy to talk about complex investing topics, but hard to boil them down to quickly grab the attention of the people we want investing. Jasmine is grassroots like the grains of rice passed on to me.
What's next for Jasmine
The goal is to expand functionality and incorporate a larger stock universe with better modeling capabilities, and more sophisticated recommenders based on similar peer relationships. Our current universes were limited by API call resources and model time.