This repository contains the source code of the STAIRS project (see official pages). The University of Luxembourg and the European Investment Bank (EIB) through the STAREBEI programme are working together to encourage private equity partners to invest in innovative and sustainable technologies. The funded research project “Sustainable and Trustworthy Artificial Intelligence Recommitment System (STAIRS) ” proposes an innovative approach to generate efficient recommitment strategies to guide institutional investors with the aid of AI-based algorithms.
We strongly recommend to create a virtual environment to avoid any interaction with your system python. Please note that only Python 3.6+ are supported.
$> sudo apt install build-essential git
$> python3 -m venv stairs-env
$> source stairs-env/bin/activate
$(stairs-env)> git clone git@github.com:ekieffer/stairs-code.git
$(stairs-env)> cd stairs-env
$(stairs-env)> python3 -m pip install -r requirements.txt
$(stairs-env)> cd stairs; python setup.py build_ext --inplace; cd ..- Create ESG score with specific skewness and correlation
python3 -m stairs.esg_score --plot --save ./data/lib_cashflows_esg.h5 --strategy proba -a 50 -c 0.9 ./data/lib_cashflows.h5- Create initial portfolios with overcommitment for training and validation
python3 -m stairs.setup_portfolios -p 1000 -o 0 ./data/lib_cashflows_esg.h5 ./data/training_portfolios.h5
python3 -m stairs.setup_portfolios -p 250 -o 0.3 ./data/lib_cashflows_esg.h5 ./data/validation_portfolios.h5- Start Parallel training with config file
nohup ipcluster start -n 10 &
python3 -m stairs.experiment.py configs/example.cfg
ipcluster stop- Test the heuristics obtained from parallel training
python3 -m stairs.validation configs/example.cfg- Generate statistics and plots from portfolios obtained after validation
python3 -m stairs.statistics /tmp/dir_portfolios/portfolios-heuristic0.h5 /tmp/dir_portfolios/portfolios-heuristic1.h5 /tmp/dir_portfolios/portfolios-heuristic2.h5