shubh123a3/Stock-Market-Anomaly-Detection
Analyze GameStop (GME) stock data using various anomaly detection methods including Z-Score, Isolation Forest, DBSCAN, LSTM, and Autoencoder. Visualize results and compare model performances through interactive Streamlit app.
This project helps financial analysts and traders identify unusual activity in stock prices. It takes historical stock data, like that of GameStop (GME), and applies various techniques to highlight abnormal price movements or trading patterns. The output is a clear visualization of these anomalies, helping users spot potential market shifts or trading opportunities.
No commits in the last 6 months.
Use this if you are a financial analyst or trader looking to automatically identify unusual price movements in a stock's historical data.
Not ideal if you need real-time anomaly detection for live trading or want to incorporate complex sentiment analysis from news or social media.
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Last pushed
Oct 15, 2024
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