Finance, Economics and Computation Projects
Luke Raskopf, PoliSci major and Xinyi (Lucy) Lu, Stats/CompSci major, spent ten weeks investigating the effectiveness of policies to combat unemployment and wage stagnation faced by working and middle-class families in the State of North Carolina. They worked closely with Allan Freyer at the North Carolina Justice Center. Project Results The team used regression and...
Xixi Lei (CS), Raffey Rana (CS/Econ), and Fan Zhu (Stats) spent ten weeks building tools to enable DUMAC to track and visualize its investments and their performance. The team cleaned data, met with stakeholders, and delivered an interactive dashboard in Tableau. View the team’s project poster here Watch the...
Most phenomena that data scientists seek to analyze are either spatially or temporally correlated. Examples of spatial and temporal correlation include political elections, contaminant transfer, disease spread, housing market, and the weather. A question of interest is how to incorporate the spatial correlation information into modeling such phenomena. In this...
Our team used artificial intelligence to help Duke University Management Company (DUMAC) operate more efficiently by building a cost optimization tool and analyzing and visualizing venture capital data. In our first project centered around cost optimization, we designed a Python script that suggests optimal cash transfers between prime brokers. In...
Carrying forward the work of a 2019-20 Bass Connections team, our Data+ team has worked to better understand the state of the home mortgage market leading up to the financial crisis. The team has built a more in-depth analysis of North Carolina to understand its different regions. We have also...
Our team used years of unanalyzed data in a cloud computing environment to conduct exploratory data analysis using natural language processing techniques, as well as visualizations, for Fleet Management Limited. Through this, and preliminary predictive modelling, we hope to help management decrease the number of preventable incidents as each one...
The Protecting American Investors project investigates the evolving structure and content of financial advice from the early 20th century to the birth of the Internet. By converting and cleaning thousands of investment advice columns from historical newspapers and magazines, we assembled a large corpus to address our research questions. Through...
Maksym Kosachevskyy (Economics) and Jaehyun Yoo (Statistics/Economics) spent ten weeks understanding temporal patterns in the used construction machinery market and investigating the relationship between these patterns and macroeconomic trends. They worked closely with a large dataset provided by MachineryTrader.com, and discussed their findings with analytics professionals from a leading asset management firm. Click...
Cecily Chase (Applied Math), Brian Nieves (Computer Science), and Harry Xie (Computer Science/Statistics) spent ten weeks understanding how algorithmic approaches can shed light on which data center tasks (“stragglers”) are typically slowed down by unbalanced or limited resources. Working with a real dataset provided by project clients Lenovo, the team created a monitoring framework that flags...
Jett Hollister (Mechanical Engineering) and Lexx Pino (Computer Science, Math) joined Economics majors Shengxi Hao and Cameron Polo in a ten week study of the late 2000s housing bubble. The team scraped, merged, and analyzed a variety of datasets to investigate different proposed causes of the bubble. They also created interactive visualizations of their data which will...
Showing all 10 results