Inspiration
The inspiration for the Stock Bot came from our desire to make stock investing more accessible and data-driven. We wanted to empower both new and experienced investors with cutting edge tools to better understand market trends
What it does
Our stock performance predictor allows users to enter a stock ticker and receive a detailed analysis of the stock’s historical performance, displayed through a detailed chart. Additionally, it uses an AI model to predict future stock prices based on historical market data and recent news events.
How we built it
We built the application using React.js for the front end interface while integrating many APIs to fetch real time stock data and predictions. Under the hood, the backend use a random forest classification machine learning algorithm to predict market trends. Each ticker gets it's own custom model and feature set to better cater to making accurate predictions. This data is then formatted and displayed using a JavaScript charting library to deliver a seamless experience to the user. In addition, we use train and test sets with a 60 - 40 split to access and examine the model's accuracy. The user is informed of this accuracy rate.
Challenges we ran into
We were faced with many challenges with ensuring real time data synchronization and handling API delays effectively. Integrating machine learning predictions with consistent accuracy while maintaining a user-friendly interface was a very complex yet rewarding task. Additionally, optimizing performance and managing large datasets in real time was a huge hurdle we had to tackle.
Accomplishments that we're proud of
We are proud of creating a functional and visually appealing application within a limited time frame. Successfully integrating machine learning driven predictions and real-time data analysis was a significant achievement. Our user friendly design and the seamless flow between components and APIs also made the app easy to use.
What we learned
My team and I learned how to manage and process real time financial data and the importance of optimizing API calls for a responsive user experience. We also deepened our understanding of predictive modeling and how to effectively integrate AI models into a front end application. Additionally, we gained valuable experience working as a team under a 24 hour deadline.
What's next for Stock Bot
In the future, we plan to enhance the machine learning model for better prediction accuracy and integrate more advanced features, such as an analysis on top investors. We also aim to add personalized investment recommendations and expand the applications scope to cover more financial markets and investment strategies. Our ultimate goal is to make the app a comprehensive tool for all investors.
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