Inspiration: Taking the Goldman Sachs's sponsor challenge as an opportunity to employ our different skill sets (given our different backgrounds) whilst a collective challenge as a team to think both inside and outside the box, both as a client and an employee of Goldman Sachs.
What it does: Calculates conventional metrics such as risk, reward, opportunity in regards to ESG factors and nonconventional metrics such as Sentimental Scores, Environment Scores, Social Scores and Governmental Scores alongside risk evaluation.
How we built it: Power BI as a visualizer, Excel, AWS, Xinerva, Simply Wallstreet, Yahoo Finance, Discord for communication and Bloomberg.
Challenges we ran into: Every step was a challenge: Lack of direction, finding a proper data set, getting data, manipulating data, data modeling, constructing user interface, categorizing sheer volume of data, making an overperforming portfolio
Accomplishments that we're proud of: All of it. Every single step.
What we learned: Being such an open ended topic made it difficult to create parameters that we didn't know belonged or not.
What's next for ESGPIO: Hopefully, we can synthesize it to make it a functional product that Goldman clientele and employees can use in the future.
Log in or sign up for Devpost to join the conversation.