Asset managers and investors face the challenge of incorporating ESG information into their funds. While most of them are still working with a simple exclusion approach, which is a simple removal of assets with low ESG scores from their universe, this may entail other issues such as finding suboptimal portfolios or mandate-breaching funds.
The penalty method in optimization can help tilt the allocation toward assets with higher ESG scores. The MATLAB based workflow proposed solves many of the challenges practitioners face, including data retrieval, visualization, model implementation, and portfolio backtesting.