Inspiration: I wanted to democratize data-driven, emotion-free trading tools for retail investors who traditionally lack access to expensive institutional software.
What it does: MomentumX Engine is an interactive quantitative dashboard that ingests real-time market data to instantly calculate momentum vectors and flash definitive Buy, Sell, or Hold signals.
How I built it: I engineered the platform using a rapid Python stack featuring yfinance for live data, pandas for vectorized math, Plotly for interactive charts, and Streamlit for a dark-themed web dashboard.
Challenges I ran into: I had a hard time importing yfinance into the application.
Accomplishments that i'm proud of: I managed to build a platform that people would spend money on to look at a trading platform that didn't need gut instinct.
What I learned: I discovered that clean data structures and modern Python frameworks allow developers to build professional, high-performance web tools with zero frontend overhead.
What's next for MomentumX Engine: The next steps are wiring the logic engine directly into sandbox broker APIs for automated order execution and implementing statistical pairs trading algorithms.
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