FIN551 Advanced Data Analysis in Empirical Asset Pricing
Autumn 2023Spring 2024
In this workshop we will delve into a set of important databases used in empirical work in finance, including the IBES, Compustat, and 13-F filings databases. These databases all have large unbalanced panels complicating data analysis. The class will discuss tools for handling such data and their application in frontier papers in asset pricing. The students will program in either Stata, MatLab, Python, Julia, or R. We will replicate key parts of select important recent papers in finance, focusing on Demand-based Asset Pricing, Financial Frictions, and Subjective Expectations. The goal of the class is to enable students to immediately and with substantially reduced fixed costs commence high-level research in empirical finance.
After successfully completing the course, the candidates:
- will understand the current research frontier in asset pricing
Will be able to:
- formulate problems, plan and carry out original research within asset pricing
Will be able to:
- communicate and discuss research with a peer audience
- do independent research on the topics of this course
The course will consist of a combination of Zoom lectures and discussions and three days of in-person teaching on April 26, 27, and 28.
The course will be open to all PhD students at NHH as well as PhD candidates from other Norwegian institutions (subject to meeting the prerequisites mentioned above).
The prerequisites are successful completion of a PhD level course on both theoretical asset pricing and on empirical asset pricing.
Each student must submit a 4-10 page write-up of a project.
Individual 30-minute presentation of a class research project in empirical asset pricing.
Pass - Fail
The students will program in either Stata, MatLab, Python, Julia, or R.
The workshop is based on selected articles from top-tier finance and economics journals, as well as recent notable working papers in empirical asset pricing.
- ECTS Credits
- Teaching language
Spring. Offered spring 2023.
Lars Lochstoer, Adjunct Professor of Finance NHH, UCLA
NHH contact person, Associate Professor Konrad Raff