TradeMaster

Inspiration

We were inspired by financial literacy throughout America and wanted to propose a game that would allow people to learn more about stocks in a simple and effective way, with feedback received through LLMs.

What it does

We generate real-time data for companies and generate graphs for them, allowing people to play a 24/7 stock market game that will always adapt to the market, while also taking a unique approach to developing the algorithm to use elements of probability to change the price.

How we built it

We built this project using React for the frontend, while using Flask in the backend to connect everything in the frontend. We also used MongoDB Atlas to store our data generated from stocks and retrieve that data to generate graphs. Python was used to generate the mathematical functions, while HuggingFace was used in order to build a LLM chatbot.

Challenges we ran into

We ran into difficulties with combining the frontend and the backend for integration testing. We also had issues deploying our LLM approach, with the end condition for displaying the summary not being reached. The frontend played a large role in this, as trying to add a case for LLMs made it so that the other buttons would not work.

Accomplishments that we're proud of

We are proud that we were able to get a significant portion of this concept done in such a short time, simulating stock prices in a way that hasn't really been done before.

What we learned

We learned a lot about the world of stock pricing along with various stochastic processes. We also gained significant experience in the frontend area with React and Flask serving as our guide to completing this project. We also learned to implement a mathematical algorithm to simulate stock prices, which is what we did in this case.

What's next for TradeMaster

We would like to make sure that the LLM front works properly along with getting the timings for the market accurate. We may also make it so that advice can be asked during the game and a multiplayer concept is implemented in the game.