GRA 6560 Strategic Asset Allocation

GRA 6560 Strategic Asset Allocation

Course code: 
GRA 6560
Department: 
Finance
Credits: 
6
Course coordinator: 
Costas Xiouros
Course name in Norwegian: 
Strategic Asset Allocation
Product category: 
Master
Portfolio: 
MSc in Quantitative Finance
Semester: 
2023 Autumn
Active status: 
Active
Level of study: 
Master
Teaching language: 
English
Course type: 
One semester
Introduction

Strategic asset allocation (SAA) is one of the most challenging problems in finance. It deals with long-term investment, that is, how households, pension funds, and sovereign wealth funds--for example the Norwegian sovereign wealth fund that is managed by Norges Bank Investment Management--should allocate their wealth across large asset classes. The difficulty of the problem stems partly from the lack of sufficient data to be able to assess different strategies over long periods of time. For this reason, state-of-the-art practices require a deep understanding of both static and dynamic asset pricing theories, good knowledge of empirical facts, and the ability to combine the above with econometric and advanced financial modeling. 

In this course, we will go over key elements, theories, and modern practices of SAA. We will start with the objective, framework, and importance of SAA. We will cover practical aspects of mean-variance investing, move to dynamic theories and models, then to the modern approach of factor investing, "alpha" generation, and, if time permits, alternative investments. The course oscillates between the normative practice of an investor achieving its objective and the positive approach of trying to understand the statistical properties of asset prices and returns. 

Learning outcomes - Knowledge

The students by the end of the course will know

  • The main elements and importance of an asset allocation strategy
  • The main theories, both static and dynamic, regarding the equilibrium relation between risk and return, underpinning strategic asset allocation
  • Relevant empirical and historical facts about asset returns that are necessary to consider for strategic asset allocation
Learning outcomes - Skills

The students by the end of the course will be able to

  • Formulate an asset allocation problem, characterize the optimal strategy, and understand the connection between optimal strategy and assumptions
  • Implement, evaluate the past performance, and simulate the future performance of a strategy
General Competence

The students by the end of the course will be able to analyze an asset allocation problem, tailored to the needs of the investor, and propose and present clearly and coherently a strategy.

Course content

The course will cover the following topics (provided enough time):

  • The problem and objective of strategic asset allocation
  • Static investment strategies
  • Long-run investing
  • Dynamic asset allocation
  • Factor theory, factors, and factor investing
  • Generating "alpha"
  • Alternative investments (if time permits)
  • Sustainability and SAA (if time permits)
Teaching and learning activities

The class will be interactive and applied. During classes, we will be going over relevant theories, models, articles, different approaches and strategies of asset allocation, as well as empirical evidence. There will be discussions and student presentations and students are expected to participate actively in class.

Some parts of the course are quite technical and we will also program in R, therefore, some prior knowledge of R is required. I will provide codes in R and students are expected to familiarize themselves and perform analyzes with the codes.

There will be group work. All students should participate in one group presentation. Also, there will be a final group project or assignment.

The course is designed, not only to develop certain technical skills and learn relevant methods but most importantly to combine these skills with the insight required to evaluate asset allocation strategies and be able to present them in a clear and coherent manner.

Software tools
R
Additional information

The exam for this course has been changed starting academic year 2023/2024. The course now has two exam codes instead of one. It is not possible to retake the old version of the exam. Please note new exam codes in the Exam section of the course description. 

It is the student’s own responsibility to obtain any information provided in class.

Honour Code
Academic honesty and trust are important to all of us as individuals and represent values that are encouraged and promoted by the honor code system. This is a most significant university tradition. Students are responsible for familiarizing themselves with the ideals of the honor code system, to which the faculty are also deeply committed. Any violation of the honor code will be dealt with in accordance with BI’s procedures for cheating. These issues are a serious matter to everyone associated with the programs at BI and are at the heart of the honor code and academic integrity. Please ask if you have any questions about your responsibilities under the honor code.

Qualifications

All courses in the Masters programme will assume that students have fulfilled the admission requirements for the programme. In addition, courses in second, third and/or fourth semester can have specific prerequisites and will assume that students have followed normal study progression. For double degree and exchange students, please note that equivalent courses are accepted.

Disclaimer

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

Required prerequisite knowledge

This course assumes that students have followed the asset management track, that is, that they have taken Investments, Asset Management, and Fixed Income Securities, or similar courses. Also, the students are expected to know well the mathematics, statistics and programming taught during the first year.

Exam categoryWeightInvigilationDurationSupport materialsGroupingComment exam
Exam category:
Submission
Form of assessment:
Written submission
Exam code:
GRA 65602
Grading scale:
ECTS
Grading rules:
Internal examiner
Resit:
Examination when next scheduled course
40No1 Semester(s)Group (2 - 3)Group project/assignment on strategic asset allocation
Exam category:
Submission
Form of assessment:
Written submission
Exam code:
GRA 65603
Grading scale:
ECTS
Grading rules:
Internal examiner
Resit:
Examination when next scheduled course
60Yes3 Hour(s)
  • BI-approved exam calculator
  • Simple calculator
  • Bilingual dictionary
Individual Mid-term school exam under supervision
Exams:
Exam category:Submission
Form of assessment:Written submission
Weight:40
Invigilation:No
Grouping (size):Group (2-3)
Support materials:
Duration:1 Semester(s)
Comment:Group project/assignment on strategic asset allocation
Exam code:GRA 65602
Grading scale:ECTS
Resit:Examination when next scheduled course
Exam category:Submission
Form of assessment:Written submission
Weight:60
Invigilation:Yes
Grouping (size):Individual
Support materials:
  • BI-approved exam calculator
  • Simple calculator
  • Bilingual dictionary
Duration:3 Hour(s)
Comment:Mid-term school exam under supervision
Exam code:GRA 65603
Grading scale:ECTS
Resit:Examination when next scheduled course
Type of Assessment: 
Ordinary examination
All exams must be passed to get a grade in this course.
Total weight: 
100
Student workload
ActivityDurationComment
Teaching
24 Hour(s)
Digital resources
12 Hour(s)
Asynchronous teaching activities like videos, walk-through programming scripts, and quizzes with feedback.
Student's own work with learning resources
84 Hour(s)
Weekly studying and mid-term preparation.
Group work / Assignments
50 Hour(s)
Work on group presentation and project/assignment.
Sum workload: 
170

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.