Reinforcement-learning-for-portfolio-allocation

Optimistic Bull or Pessimistic Bear: Adaptive Deep Reinforcement Learning for Stock Portfolio Allocation

If you feel that our code is helpful to you, please cite our paper:

Xinyi Li, Yinchuan Li, Yuanchen Zhan, Xiao-Yang Liu, "Optimistic Bull or Pessimistic Bear: Adaptive Deep Reinforcement Learning for Stock Portfolio Allocation," International Conference on Machine Learning (ICML) Workshop on AI in Finance, May 2019.

Please follow the instructions below to run the code:

Prerequisites

Python 3.6 envrionment

Anaconda3

Tensorflow

OpenMPI

Installation of system packages OpenMPI

Install gym under tensorflow

pip install gym

Download Official Baseline Package and install it

git clone https://github.com/openai/baselines.git cd baselines pip install -e . ```

Find the following files and change the address in the files into your address

./gym/envs/init.py ./gym/envs/portfolio/ portfolio_env.py ./gym/envs/portfolio/ portfolio_testenv.py

Baseline

• Find your baselines folder, and replace it with baseline in this repository

Gym

• Find your gym folder, and replace it with gym in this repository

Code description

./baselines/baselines/run.py used for train or test ./baselines/baselines/common/cmd_util.py used for parameter configuration ./baselines/calculate_table.py used for generating data for Table 1 in paper ./baselines/plot_financial.py used for generating figure for Figure1 in paper ./baselines/plot_property.py used for generating figure for Figure 5 and Figure 6 in paper