Deep-Reinforcement-Learning-for-Stock-Trading-DDPG-Algorithm-NIPS-2018

(★ 101)

Practical Deep Reinforcement Learning Approach for Stock Trading. NeurIPS 2018 AI in Finance.

File Explorer

- .DS_Store
- ^DJI.csv
- calculate_return.ipynb
- calculate_return.ipynb copy
- daily_return.xlsx
- ddpg.csv
- dow_jones_10_16.csv
- dow_jones_30_daily_price.csv
- dow_jones_30_ticker.txt
- history.csv
- mean_variance_return copy.xlsx
- mean_variance_return.xlsx
- return_final_quarterly copy.xlsx
- return_final_quarterly.xlsx
- variable list and description.docx
- variable list and description.pdf
- weights_table_20160101.xlsx
- weights_table_20170101.xlsx
- weights_table_20180101.xlsx
- bookdraft2017nov5.pdf
- DowMemberHistory.pdf
- GICS_Global Industry Classification.pdf
- - .DS_Store
  - __init__.py
  - registration.py
- - __init__.py
  - box.py
  - dict.py
  - discrete.py
  - multi_binary.py
  - multi_discrete.py
  - space.py
  - tuple.py
  - utils.py
- - __init__.py
  - atomic_write.py
  - closer.py
  - colorize.py
  - ezpickle.py
  - json_utils.py
  - play.py
  - seeding.py
- - __init__.py
  - async_vector_env.py
  - sync_vector_env.py
  - vector_env.py
- - __init__.py
  - atari_preprocessing.py
  - clip_action.py
  - filter_observation.py
  - flatten_observation.py
  - frame_stack.py
  - gray_scale_observation.py
  - monitor.py
  - pixel_observation.py
  - record_episode_statistics.py
  - rescale_action.py
  - resize_observation.py
  - test_atari_preprocessing.py
  - test_clip_action.py
  - test_filter_observation.py
  - test_flatten_observation.py
  - test_frame_stack.py
  - test_gray_scale_observation.py
  - test_pixel_observation.py
  - test_record_episode_statistics.py
  - test_rescale_action.py
  - test_resize_observation.py
  - test_transform_observation.py
  - test_transform_reward.py
  - time_limit.py
  - transform_observation.py
  - transform_reward.py
- .DS_Store
- __init__.py
- core.py
- error.py
- logger.py
- version.py
.DS_Store
.gitignore
LICENSE
README.md
result_trading.png
run.py

# Installation Guide

1. Get the code

git clone https://github.com/AI4Finance-Foundation/Deep-Reinforcement-Learning-for-Stock-Trading-DDPG-Algorithm-NIPS-2018

Downloads the entire project code from GitHub to your computer.

cd Deep-Reinforcement-Learning-for-Stock-Trading-DDPG-Algorithm-NIPS-2018

Moves into the project folder you just downloaded.

2. Official Install Script

Easy Recommended

Prerequisites

Homebrew A package manager for macOS/Linux.
Python 3 Python is required to use pip.

brew install cmake openmpi

Installs the pre-built package via Homebrew — no source build required.

pip install virtualenv

Installs the package published on PyPI directly — no need to clone the source.

pip install gym

Installs the package published on PyPI directly — no need to clone the source.

pip install gym[atari]

Installs the package published on PyPI directly — no need to clone the source.

✅ After installing, open a new terminal and run the program's version command (e.g. --version) to confirm it worked.

Pulled directly from this repo's README.