Frank G
- Research Program Mentor

PhD candidate at University of Delaware

Expertise

Economics, Python, Optimization, Engineering

Bio

Hello! My name is Frank Gentile and I'm an Economics PhD student at the University of Delaware. My research interests revolve around environmental economics, climate change, and energy economics. I hope to use data and advanced econometric models to advise policy on clean energy transitions! On the personal side, I've lived in Houston TX as well as Paris France since graduating from college in 2019, and am currently living in Wilmington DE. I like to play basketball, cook, travel, and play video games in my spare time!

Project ideas

Project ideas are meant to help inspire student thinking about their own project. Students are in the driver seat of their research and are free to use any or none of the ideas shared by their mentors.

Analyze your music listening data from Spotify!

Use Python to analyze your music or podcast streaming data (easily downloaded from Spotify) to show trends, your most popular music genres, or whatever else you can think of! Then design a dashboard to view these trends, and deploy it online.

Calculate the optimal time to buy a house in your city

Analyze home price data from Zillow (data available by zip code) to find what year was the optimal time to buy a house! Use Python to calculate total cost of a house using average interest rates, and think through the macroeconomic factors which might make for an encompassing measure of the "time to buy"!

Create an NBA trade simulator

Scrape NBA statistics using python or google sheets and basketballreference.com, identify a metric to compare different players on different teams, and run a statistical hypothesis test to determine if the teams involved would accept the potential trade! Then create an interface to run your simulator and view the result

Do crypto markets predict daily market returns?

The NYSE is open for trading from 9:30 am to 4 pm EST, however currency markets (including crypto markets) never sleep. Taking advantage of this- trading in crypto markets might be correlated with how traditional stock markets trade both throughout the day, and off hours. If you were to view how crypto markets were trading before 9:30 am, and that were to influence your position at market open, could you stand to profit?