DRE 4011 Empirical Asset Pricing
DRE 4011 Empirical Asset Pricing
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.
- 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
- Fixed Income and 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
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
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
5. Fixed Income
Campbell Chapter 8
Cochrane, Chapter 19
Lectures, reading research papers, presenting and discussing them in class.
Performing analysis on data.
Students can use any econometric software that they choose to undertake the required tasks.
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 course leader. 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.
Covid-19
Due to the Covid-19 pandemic, there may be deviations in teaching and learning activities as well as exams, compared with what is described in this course description.
Please see English course description.
| Assessments |
|---|
Exam category: Submission Form of assessment: Written submission Weight: 25 Grouping: Individual Duration: 4 Week(s) Exam code: DRE40111 Grading scale: Point scale leading to ECTS letter grade Resit: All components must, as a main rule, be retaken during next scheduled course |
Exam category: Submission Form of assessment: Written submission Weight: 25 Grouping: Individual Duration: 4 Week(s) Exam code: DRE40111 Grading scale: Point scale leading to ECTS letter grade Resit: All components must, as a main rule, be retaken during next scheduled course |
Exam category: Submission Form of assessment: Written submission Weight: 50 Grouping: Individual Duration: 6 Week(s) Exam code: DRE40111 Grading scale: Point scale leading to ECTS letter grade Resit: All components must, as a main rule, be retaken during next scheduled course |
| Activity | Duration | Comment |
|---|---|---|
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) |
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.