- config: default YAML config containing all the parameters that can be tuned
- models: details of the model runs contained in the following files:
- <model time stamp>_config.yaml: contains the configuration of the model run
- <model time stamp>_metrics.yaml: contains the test set metrics
- reference: some random reference pdfs
- scripts: random scripts e.g. run analysis on all the model/*metrics.yaml files
- src: main code, this contains these important files:
- fx_env.py: defines the trading environment using a subclass of gym.ENV
- fx_model.py: defines the deep learning model and memory classes
- helpers.py: defines helper functions
- indicators.py: defines functions for calculating technical indicators for trading
- main.py: main script where the env is created, model is trained, etc.
- optimze_params.py: bayesian optimization script of all the variables found in config/config.yaml
-
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Automated trading system for foreign exchange trading using Deep Q-Learning with a deep neural network (CNN) and some intelligent trading strategies
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