Finance Freedom

What it does

Our project essentially provides an unique platform for users to freely choose what sources they would like their recommendations to come from. From WSB subreddit to Twitter users, to ESG (Environment, Social, Governance) scores, our project allows users to weigh different sources differently to have their unique stock recommendations.

How we built it

We built this project using Svelte, NLTK, pandas, tweepy, and more. We combined multiple sentiment analysis models, built our own analysis models, and developed a weighing algorithm.

Accomplishments that we're proud of

One accomplishment we are proud of is building Python sentiment analyses using Twitter API and being able to access specific user tweets and scrape for particular stocker tickers or cryptocurrencies. Another accomplishment we’re proud of is combining multiple models that are unique to stocks, and making an algorithm to weigh based on user choices.

What we learned

As freshman, we learned how developing an app can be difficult and is essential that we need good planning to properly develop our app. We learned a lot about sentiment analysis, and how impactful it can be on stock prices.

What's next for Finance Freedom

In the Future, cryptocurrency, customization of Twitter users (being able to input what Twitter users or keywords you'd want to see), having more parameters, such as political climate, and finally, having an open-source, custom recommendation options for users will ultimately help people have Financial Freedom.