Inspiration: Our project is inspired by the belief that underrepresented communities can make more informed decisions in the stock market with the right tools and resources. By providing accessible predictions and insights, we aim to empower these individuals to navigate the complexities of investing.
What It Does: We developed a model trained on stock market data from 2013 to 2019, which predicts future stock prices. Users can compare these predictions with actual market prices, allowing them to gauge the accuracy and reliability of the model. This feature enhances their ability to make educated investment choices.
How We Built It: Our application was built using Python for the backend and React for the frontend, enabling seamless interaction between the user interface and the predictive algorithms.
Challenges We Ran Into: One of the main challenges we encountered was navigating GitHub. Managing version control and collaboration among team members proved to be a learning curve, but it ultimately strengthened our teamwork skills.
Accomplishments That We're Proud Of: We are particularly proud of successfully implementing the chatbot feature. This addition enhances user engagement by providing real-time assistance and guidance, making the stock analysis process more interactive and user-friendly.
What We Learned: Collaboration was key to our success. Throughout the project, we learned a great deal about integrating chatbots into software systems, as well as how to effectively connect backend and frontend components. This experience significantly enhanced our coding knowledge and technical skills.
What's Next for Stock Analyzer: Looking ahead, we plan to expand our project into a comprehensive stock management portfolio. This will include additional features such as personalized investment strategies, risk assessment tools, and performance tracking, further empowering users to take control of their financial futures.
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