Research Projects by Subject

Note: Each research project will involve background reading for the interns provided by their mentors. Each research project will involve a final presentation by the interns.

Interns are expected to work collaboratively on the same project and/or data set. This may preclude rising seniors from submitting papers based on such projects to the Intel Science Talent Search competition.

Economics

Code Research Project Descriptions
ECO-01 Title: Transportation Choice and Pollution in Taiwan
Primary mentor: Bryan Pratt
Faculty advisor: Prof. Yihsu Chen
Location: UCSC Main Campus
Number of interns: 2

Project description: This research seeks to understand the environmental and welfare impacts of changes in transportation options available for traveling between cities in Taiwan. Most notably, the mentor's research group is examining the impact of the introduction of high-speed rail. The group relies on a broad set of transportation and air quality data to examine the full range of transportation choices over time and their effects on the environment. A key aspect of this research will be to determine what effect the introduction of high-speed rail had on: highway traffic, domestic air traffic, other rail traffic, highway vehicle accidents and fatalities, and emissions from transportation.

Tasks: The SIP interns will work to bring data from various sources together, using ArcMap or QGIS (Geographic Information Systems software) and Stata or R (statistical analysis software) to visualize and analyze the data. The mentor will help the SIP interns to learn at least one each of the GIS and statistics software packages, especially in the early stages. Subsequently, SIP interns will combine and match data, visualize data of interest, and conduct data analysis in partnership with and under the guidance of the mentor. Familiarity with economics and/or statistics not required.

Required skills for interns prior to acceptance: None
Skills intern(s) will acquire/hone: Computer programming; statistical data analysis
Program Week Number: 1 2 3 4 5 6 7 8 9 10
Mentor's availability: ON ON ON ON OFF ON ON ON ON ON


Code Research Project Descriptions
ECO-02 Title: Event Discovery for Options Trading: A Machine Learning Approach
Primary mentor: Sameh Habib
Faculty advisor: Prof. Daniel Friedman
Location: UCSC Main Campus
Number of interns: 2

Project description: This project applies machine learning techniques to identify events defining profitable options trading strategies. The goal is to use security characteristics as well as macroeconomic vairiables as the bases upon which events are discovered. Events are triggered when a set of combinations of the feature space breaks a specific threshold. The project aims to: (1) uncover notable events by iterating through all possible combinations of the features conditional on a threshold being reached, and (2) analyze which events can provide a significant prediction to a profitable trading strategy, conditional on an event being triggered. Given the vast differences between types of options strategies, this process is to be repeated for every different options trading strategy under consideration. 

Tasks: The SIP interns will mostly be working in R compiling data in a format ready for analysis. Depending on the rate of early progress, perhaps the interns can write simple code to clean and do preliminary analysis of the data. Part of the analysis will be to run simple regressions to possibly narrow down the feature space, creating summary statistics tables for different strategies at different periods, and writing functions (preferably in R) that return vectors of strategy specfic returns. 

Required skills for interns prior to acceptance: Computer programming and statistical data analysis experience recommended
Skills intern(s) will acquire/hone: Computer programming; statistical data analysis
Program Week Number: 1 2 3 4 5 6 7 8 9 10
Mentor's availability: REM REM ON ON ON ON ON ON ON ON