FIN551 Advanced Data Analysis in Empirical Asset Pricing

• Topics

  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.

• Learning outcome

  After successfully completing the course, the candidates can:

  Knowledge

  • Understand the current research frontier in asset pricing.

  Skills

  • Formulate problems, plan and carry out original research within asset pricing.

  Competence:

  • Communicate and discuss research with a peer audience.
  • Conduct independent research on the topics of this course.

• Teaching

  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.

• Restricted access

  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).

• Required prerequisites

  The prerequisites are successful completion of a PhD level course on both theoretical asset pricing and on empirical asset pricing.

• Compulsory Activity

  Each student must submit a 4-10 page write-up of a project.

• Assessment

  Individual 30-minute presentation of a class research project in empirical asset pricing.

• Grading Scale

  Pass - Fail

• Computer tools

  The students will program in either Stata, MatLab, Python, Julia, or R.

• Literature

  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.