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oanda-trading-models
keeprich/oanda-trading-models
oanda-trading-models is a machine learning model from keeprich. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
Multi-model classification pipeline predicting BUY / HOLD / SELL signals for major forex pairs using 10 years of H1 candle data.
Access
Public
Updated Jul 11, 2026
Repo size
80.2 MB
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Repo makeup
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.pkl69.1 MB · 93%
At a glance
- License
- apache-2.0
- Access
- Public
- Created
- Jul 9, 2026
- Updated
- Jul 11, 2026
- SHA
- 39ddeb7d
Model card
From the Hugging Face model README
OANDA Trading Signal Models
Multi-model classification pipeline predicting BUY / HOLD / SELL signals for major forex pairs using 10 years of H1 candle data.
Instruments
USD_CHF
Granularity
H1 (1-hour candles)
Model Performance (Test Set)
| Model | Accuracy | F1 (weighted) | Sharpe Ratio | Return % | Max DD % |
|---|---|---|---|---|---|
| xgboost | 0.3895086891225059 | 0.4624705139898039 | 0.0 | 0.0% | 0.0% |
| lightgbm | 0.370521347350354 | 0.4419163108223123 | 0.0 | 0.0% | 0.0% |
| lstm | 0.3868268611885861 | 0.45938959752709685 | -0.476 | -0.0% | -0.0% |
Usage
from huggingface_hub import hf_hub_download
import joblib
# Download and load XGBoost model
path = hf_hub_download(repo_id="keeprich/oanda-trading-models", filename="models/xgboost/EUR_USD_H1/model.pkl")
model = joblib.load(path)
Features
30 engineered technical features including:
- EMA crossovers (8, 21, 50, 200)
- RSI (7, 14), MACD, Stochastic, Williams %R, CCI, ADX
- Bollinger Bands (width, %B), ATR
- Log returns and lagged returns
Target
3-class signal: 0=SELL, 1=HOLD, 2=BUY
Based on 4-bar forward return with ±0.15% threshold.
Training
- Period: 10 years (2016–2026)
- Split: 70% train / 15% val / 15% test (time-ordered, no shuffle)
- Scaling: StandardScaler fitted on train set only
Generated: 2026-07-11
- License
- apache-2.0
- Created
- Jul 9, 2026
- Updated
- Jul 11, 2026