Data science / Final project
Bluesky Sentiment and Stock Movement
A modeling pipeline that merges Bluesky sentiment with Yahoo Finance hourly data to test short-term stock movement signals.
Analysis surface
Modeling Pipeline
- 01Audit
Merge Bluesky social sentiment data with Yahoo Finance hourly OHLCV data.
- 02Feature
Aggregate to ticker-hours, split by intraday/overnight, and build rolling features.
- 03Model
Train baseline and tree-based ensembles using strict chronological train/test splits.
- 04Evaluate
Compare F1 and ROC-AUC scores to test for actionable, short-term directional signal.
Problem
The project tests whether social sentiment adds anything useful once timestamps, targets, and train/test splits are handled carefully.
Approach
I structured collection, audit, feature engineering, modeling, evaluation, and dashboard work into reusable notebooks and Python modules.
Result
The repo includes EDA figures, processed feature tables, trained models, and result tables.