Stock Theory

Inspiration

Our inspiration for this project comes from the uneasy feeling of trying to predict volatile markets when hard-earned money is on the line. In our own experiance of losing to the markets in the past, we now hope that others can learn from the model, which was built from the mistakes we made in the past, and be more successful.

What it does

Stock Theory scavenges the niche and forgotten parts of the business and stock world to formulate a more accurate representation of whats happening on the ground in real-time.

How we built it

Using OpenAI API and beautiful soup for the back-end, we scraped the internet looking for information and fed it to the generative AI model to make predictions on the market. This was all encapsulated in the front end with the use of HTML, CSS, Javascript, and other web applications to make a more palatable experiance for the client.

Challenges we ran into

The information that the AI gave was originally not very accurate. However, we were able to further fine-tune the model by working with it and training it in the OpenAI Playground.

Accomplishments that we're proud of

We are proud of the knowledge of openAI and generative language responses that we have learned while we have been here at hackUTD.

What we learned

We have learned a great deal about generative AI and how the different applications from predicting stock prices to how well an industry is expected to do in the next decade. The different breadths of things we have seen and touched during this project is invaluable to us and out future careers.