no-YOLO Portfolio

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  Cover

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  Initial portfolio upload

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  Stock view 1 showing how stocks are suggested to users following them uploading their portfolio.

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  Stock view 2 showing how users can select one of their portfolio's stocks.

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  Stock view 3 showing how users are given multiple diversifying stock options to see analyses of.

Inspiration

We were inspired by portfolios that go all in on one industry or one type of stock and lose it all in a sudden flash. Many investors, especially new ones, tend to chase trends rather than diversify, leaving them vulnerable to market volatility. We wanted to create a tool that actively helps investors mitigate risk through strategic diversification.

What it does

Our platform analyzes a user’s stock portfolio and recommends uncorrelated stocks for better diversification. Users upload their portfolio file, and we apply covariance analysis to suggest stable investments from different sectors.

How we built it

• Financial Modeling Prep & Stock APIs – For real-time stock data and news.
• Streamlit – To build a simple, interactive dashboard.
• Matplotlib, Pandas, NumPy, nltk, fmp, etc – For data processing, visualization, and covariance calculations.

Challenges we ran into

• Integrating multiple data sources and ensuring accuracy.
• Optimizing covariance analysis to recommend genuinely unrelated stocks.
• Handling API limits while keeping analysis real-time.

Accomplishments that we're proud of

• Built an intuitive dashboard with real-time stock recommendations.
• Implemented covariance analysis for precise diversification.

What we learned

• Small errors in data can impact financial models significantly.
• Optimizing covariance analysis improves recommendation quality.

What's next for no-YOLO portfolio

• Enhancing covariance analysis with more time intervals.
• Expanding support for bonds and ETFs.
• Automating portfolio tracking with brokerage integration.

Built With

• numpy
• pandas
• plotly
• python
• streamlit