Robert J. Shiller, Sterling Professor of Economics, Department of Economics and School of Management (firstname.lastname@example.org) and William N. Goetzmann, Edwin J. Beinecke Professor of Finance and Management Studies, School of Management (email@example.com)
The research project involves implementing various natural language processing (NLP) methods on textual data from investor surveys and financial news outlets to evaluate feedback in narrative structures. The RA team will help prepare the raw data for processing and assist with some of the NLP implementations (e.g., hand-coding documents, using statistical tools to describe the data, programming routines to process large text databases). The goal of the SRO project will be to quantify narrative structures used in financial media, and examine whether and/or how they may propagate to investor beliefs. The work is joint with Dasol Kim at the Office of Financial Research.
Requisite Skills and Qualifications:
The project requires the RA team to organize, clean and possibly hand-code data, and help prepare tables and graphs for papers and presentations. There may be opportunities to provide statistical support in analyzing data. A strong background in econometrics and mathematics is required, as well as experience using programming languages such as R and PYTHON.