MILLION: A General Multi-Objective Framework with Controllable Risk for Portfolio Management

Datasets

Users can access the the used dataset in our paper through google driver as shown in the following link.

https://drive.google.com/drive/folders/1idb8NpiCaAzHLaklw6KhTxuJnIQYiM9W?usp=drive_link

Users can train MILLION framework through the following code:

python main.py

For the hyper-parameters, users can manually set in config.py file.

Users can follow the jupyter notebooks, i.e., interpolation_plot.ipynb and improvement_plot.ipynb, to conduct risk control experiments.

Name		Name	Last commit message	Last commit date
Latest commit History 2 Commits
README.md		README.md
config.py		config.py
dataset.py		dataset.py
improvement_plot.ipynb		improvement_plot.ipynb
interpolation_plot.ipynb		interpolation_plot.ipynb
layers.py		layers.py
main.py		main.py
model.py		model.py
sensitivity_analysis.ipynb		sensitivity_analysis.ipynb
test.py		test.py
train.py		train.py
utils.py		utils.py