-
If predicted EPS beats wallstreet estimates
-
If predicted EPS falls within wallstreet estimates
-
If predicted EPS misses wallstreet estimates
-
If EPS can't be predicted based on available data
-
shy chart
-
frontend not really syncing up... but the magic crystal ball says its going to beat wallstreet estimates this upcoming quarter!
Inspiration
One day, we were watching the stock markets and saw a random company gap up 20% after their earnings. We wondered, could this have been predicted? So we looked at data from Google Trends to see if the company's product's search interest would match well with how their earnings report went. Interestingly, some companies' past earnings report history does correlate with their Google Trends search interest! So we proceeded to build this.
What it does
EPSViz does simple linear regression to visualise and predict how companies could perform for their upcoming earnings.
How we built it
We built the backend using NodeJS, R, Express, Postgres, and Docker. Frontend was built using React.
Challenges we ran into
We spent several hours trying to connect R to NodeJS, but after several hours realised that the library we were using was terrible and switched over to another one which worked.
Accomplishments that we're proud of
Figuring out how to connect R to NodeJS
What we learned
How to connect R to NodeJS
What's next for EPSViz
Deeper further analysis of earnings predictions outside of simple linear regression.
Log in or sign up for Devpost to join the conversation.