Finbot

Inspiration

I was inspired to create FinBot by my passion for both computer science and finance. I have always been fascinated by how technology can solve real-world problems, and I also wanted to understand the stock market more deeply and become a part of the finance world. I realized that many people, especially beginners, find financial data confusing and overwhelming, and I wanted to build a tool that could make investing more approachable and understandable.

At the same time, I wanted to challenge myself to learn and grow academically. One of my goals was to research this topic rigorously and publish a research paper. Through this process, I explored stock valuation, sector analysis, and real-time data retrieval, combining finance knowledge with programming skills. As of this submission, I have successfully published my research paper, which was a major milestone in my learning journey.

What it does

FinBot gives users clear, real-time financial insights, helps them compare stocks to sector benchmarks, and provides news updates, all in an easy-to-understand format. Users can ask natural-language questions about stocks, including valuation, market cap, dividends, and recent news headlines.

How I built it

FinBot is built with Python, leveraging:

• yFinance and Pandas for stock data and analysis
  
• BeautifulSoup and Requests for live news scraping
  
• A Google Colab notebook for an interactive, accessible experience
  

The project combines programming skills with finance knowledge to make real-time stock insights available to anyone.

Challenges I ran into

One challenge was handling real-time financial data reliably while keeping the interface simple and understandable. Another challenge was normalizing sector names and calculating benchmarks dynamically to provide accurate comparisons.

Accomplishments that I'm proud of

• Successfully built a functional AI-powered financial assistant
  
• Published a research paper based on the underlying financial analysis
  
• Made the project accessible via both Python script and Google Colab
  

What I learned

I learned how to integrate real-time data, perform financial analysis, and design a conversational interface that translates complex stock data into plain language. I also gained experience publishing research and documenting code for others to use.

What's next for FinBot

Future improvements include expanding the types of financial insights provided, improving natural-language understanding, and adding more interactive features to make investing even more approachable.

Built With

• beautiful-soup
• github
• google-colab
• pandas
• python
• requests
• yfinance