tradytics/surpriver
A machine learning tool that detects anomalies in stock price and volume patterns to identify high-moving stocks before they move.
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Surpriver is a stock analysis tool that leverages machine learning and anomaly detection algorithms to analyze volume and price data, identifying unusual patterns that precede significant stock movements. The system uses feature generation with technical indicators and detection engines to surface stocks with atypical trading behavior. It relies on scikit-learn, scipy, pandas, and yfinance for data processing and model inference.
Frequently asked
- What is tradytics/surpriver?
- A machine learning tool that detects anomalies in stock price and volume patterns to identify high-moving stocks before they move.
- Is surpriver open source?
- Yes — tradytics/surpriver is open source, released under the GPL-3.0 license.
- What language is surpriver written in?
- tradytics/surpriver is primarily written in Python.
- How popular is surpriver?
- tradytics/surpriver has 1.9k stars on GitHub.
- Where can I find surpriver?
- tradytics/surpriver is on GitHub at https://github.com/tradytics/surpriver.