DRE 4011 Empirical Asset Pricing

DRE 4011 Empirical Asset Pricing

Course code: 
DRE 4011
Department: 
Finance
Credits: 
6
Course coordinator: 
Richard Priestley
Course name in Norwegian: 
Empirical Asset Pricing
Product category: 
PhD
Portfolio: 
PhD Finance courses
Semester: 
2024 Autumn
Active status: 
Active
Level of study: 
PhD
Teaching language: 
English
Course type: 
One semester
Introduction

This course is intended for PhD students in finance and related fields. The course is an introduction to empirical research in finance. Topics include tests of asset pricing models, return predictability, present values and VARs, conditional and unconditional tests. The aim is to familiarize students with essential empirical approaches and with important empirical facts and areas of current research interest.

Learning outcomes - Knowledge
  • To understand the testable implications of asset pricing models
  • To understand how to test asset pricing models
  • To understand the role of predictability of returns and excess volatility
  • To understand the implications of time-varying expected returns on tests of asset pricing models
  • To understand empirical approaches to testing factor models of returns
  • To understand the approaches to testing production and consumption based asset pricing models
Learning outcomes - Skills
  • To understand the current state of research in empirical asset pricing.
  • To formulate empirical tests of asset pricing models using econometric techniques.
  • To construct test of alternative asset pricing models
  • To be able to differentiate and assess the appropriateness of cross-sectional and time series tests of AP models
General Competence

To be able to:

  • critically review research papers at the forefront of empirical asset pricing, 
  • evaluate their strengths and weaknesses,
  • identify potential extensions, and
  • develop empirical strategies to address the weaknesses and extensions
Course content

1.  A Recap of the SDF and properties of returns
Campbell Chapters 3 and 4
Cochrane Chapters 1, 2 and 4

2.  Return Predictability
Campbell Chapter 5
Cochrane Chapter 20
Ferson Chapter 30, 32

3. The Cross-section of Expected Stock Returns
Campbell Chapter 3 and 4
Cochrane Chapter 9-15, 20, 21
Ferson Chapter 12-22, 33

(a) Testing Methodologies: Time-series, cross-section.
(b) CAPM and APT
(c) Characteristic based factors
(d) The factor zoo

4. Testing the Consumption and Production CAPMs: Habit and LRR
Campbell Chapter 6 and 7
Ferson Chapter 29, 31
 

Teaching and learning activities

Lectures, reading research papers, presenting and discussing them in class.

Performing analysis on data.

Software tools
No specified computer-based tools are required.
Additional information

Students can use any econometric software that they choose to undertake the required tasks.

Qualifications

Enrollment in a PhD Programme is a general requirement for participation in PhD courses at BI Norwegian Business School.
External candidates are kindly asked to attach confirmation of enrollment in a PhD programme when signing up for a course. Other candidates may be allowed to sit in on courses by approval of the courseleader. Sitting in on a course does not permit registration for the course, handing in exams or gaining credits for the course. Course certificates or confirmation letters will not be issued for sitting in on courses.

Disclaimer

Deviations in teaching and exams may occur if external conditions or unforeseen events call for this.

Required prerequisite knowledge

Please see English course description.

Assessments
Assessments
Exam category: 
Submission
Form of assessment: 
Submission PDF
Exam/hand-in semester: 
First Semester
Weight: 
100
Grouping: 
Individual
Duration: 
12 Week(s)
Exam code: 
DRE 40112
Grading scale: 
ECTS
Resit: 
Examination when next scheduled course
Type of Assessment: 
Ordinary examination
Total weight: 
100
Student workload
ActivityDurationComment
Group work / Assignments
50 Hour(s)
Specified learning activities (including reading).
Teaching
30 Hour(s)
Student's own work with learning resources
100 Hour(s)
Sum workload: 
180

A course of 1 ECTS credit corresponds to a workload of 26-30 hours. Therefore a course of 6 ECTS credits corresponds to a workload of at least 160 hours.