This is a database analysis and visualization project. We collaborate with database providers, Fannie Mae, XXX(Healthcare data provider) and Twitter. We also use the lab resources to construct a volatility database and put it in our studies. The databases contain tons of data but what is the better way to visualize them for researchers? This is the core question that we are trying to answer.
We wrap up our visualization results into a website, which is accessible from here. Users can also access each of the four sections from the below list. Specific instructions, including codes and database structures, for database users can also be found in the pages.
- Fannie Mae Database Visualization
- Healthcare Database Visualization
- Twitter Database Visualization
- Volatility Database Visualization
Project Link:
Financial Engineering Virtual Lab
Research Topics:
- Database Construction with PostgreSQL
- Database Visualization with D3.js, Gephi, Python, Plotly and Shiny
- Database Administration
Researchers:
- Database Administration
- Ziwen Ye, Ph.D. Student in Financial Engineering, zye2@stevens.edu
- Fannie Mae
- Gary R. Engler, Ph.D. Candidate in Mathematics, gengler@stevens.edu
- Healthcare
- Xingjia Zhang, Ph.D. Student in Financial Engineering, xzhang21@stevens.edu
- Waris Banthernpaesach, Master Student in Financial Engineering, wbanther@stevens.edu
- Teko Teko-Agbo, Master Student in Financial Engineering, ttekoagb@stevens.edu
- Raju Chiranjeevi, Master Student in Financial Engineering, rchiranj@stevens.edu
- Danyue Gu, Master Student in Financial Engineering, dgu@stevens.edu
- Jian Yang, Master Student in Financial Engineering, jyang19@stevens.edu