TradeTracker is a sophisticated Python tool designed to automate Forex trading decisions based on predictions from two separate machine learning models trained on negative and positive price actions respectively.
The TradeTracker utilizes an AISignal class for handling ML model operations and an OANDATrader class for interfacing with the OANDA Forex trading platform. It is designed to track daily trades, deciding whether to buy, sell, or hold based on the combined predictions of two LSTM models: one trained on negative price actions ("LeftBrain") and the other on positive price actions ("RightBrain").
- Automated trading decisions based on ML predictions.
- Distinct models for positive and negative market movements.
- Daily trade tracking with customizable trade duration.
- Integration with OANDA Forex for trade execution.
This project requires Python 3.12 and depends on several external libraries including numpy, pandas, tensorflow, and others. It is managed with Poetry for easier dependency handling.
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Clone the repository:
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Install dependencies using Poetry:
If you haven't installed Poetry, refer to the official Poetry documentation for guidance.
- Activate the virtual environment:
To utilize TradeTracker, ensure you have both "LeftBrain" and "RightBrain" models trained and saved within the Model directory.
- Initialize TradeTracker:
Instantiate the TradeTracker class. Ensure your OANDA credentials (OANDA_ID and OANDA_TOKEN) are correctly set in configForex.py.
from TradeTracker import TradeTracker
tracker = TradeTracker()
tracker.track_daily_trades(num_days=80, model_left="LeftBrain (Negative).h5", model_right="RightBrain (Positive).h5")
trade_data_df = tracker.get_trade_data()