In this dashboard, we visualize the ESG scores and market performance of S&P 500 companies from 2015 to 2023.
All plots are interactive through Plotly and can be found on the respective tabs.
In our relationship model, we display average market-weighted monthly returns by company, GICS Sector, GICS Industry, GICS Industry Group, or GICS Sub-Industry against twelve possible ESG metrics. Users can select any time period in which to examine this relationship.
In our predictive model, we see if ESG scores have any impact on performance. We use a Lasso model to predict the monthly returns of a company based on its ESG scores and selected financial metrics, comparing predicted returns from our model against actual returns.
The coefficients of each model are shown below the plot.
In the ESG Metric Details tab, we view the distribution of ESG metrics and the relationships between them.
Data is sourced from Bloomberg, and our final set is available in the inputs folder. Each row is unique by ticker and date, representing a snapshot at the end of each month for companies in the S&P 500 from 2015 to 2023.
To run from your own machine, clone the repo and install requirements of requirements.txt to a new environment.
conda create --name esg-dashboard
conda activate esg-dashboard
python -m pip install -r requirements.txtFrom the main directory, run the following from the main repository to start the app:
streamlit run app.pyMany thanks to @donbowen for the guidance!