keeprich/oanda-trading-models

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