Instructions to use yusufizzetmurat/fomc-volume-har with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yusufizzetmurat/fomc-volume-har with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("yusufizzetmurat/fomc-volume-har", dtype="auto") - Notebooks
- Google Colab
- Kaggle
yusufizzetmurat/fomc-volume-har
Artefact for the fed-pulse FOMC text analytics project.
- Source code: https://github.com/yusufizzetmurat/fed-pulse
- Live demo: https://fedpulse.yusufizzetmurat.com
- License:
mit
Training corpus
HAR Corsi log-volume regression coefficients + weekday / month-end / quarter-end seasonality block + conformal residual quantiles for horizons h=1, 5, 22. Fit on 180 calendar days of daily ^GSPC volume.
Training command
python -m app.data.late_fusion_volume fit-production-artifact --symbol ^GSPC --period 180d
Attribution
- Daily share-volume series: Yahoo Finance via
yfinance(^GSPCreference symbol). - Fit recipe: per-horizon HAR Corsi regression on log-volume with a weekday + month-end / quarter-end seasonality block; conformal residual quantiles at the 80% / 90% bands.
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