| Learning objectives |
Upon completion of the course, students should be
able to
- apply and do derivations with relevant mathematical tools and
concepts such as those relating to functions, differentiation, and
linear algebra,
- solve problems relating to optimization,
- compute probability-theoretical quantities,
- solve problems relating to random variables and their
distributions,
- apply Monte Carlo methods and IT tools to solve numerical
problems,
- apply and interpret relevant statistical methods and concepts
such as those relating to inference, hypothesis testing, and
regression, and
- identify relevant solution methods for quantitative problems
relating to the above topics.
|
| Examination |
|
Quantitative
Methods:
|
| Exam
ECTS |
7,5 |
| Examination form |
Written sit-in exam on CBS'
computers |
| Individual or group exam |
Individual exam |
| Assignment type |
Written assignment |
| Duration |
4 hours |
| Grading scale |
7-point grading scale |
| Examiner(s) |
One internal examiner |
| Exam period |
Autumn |
| Aids |
Limited aids, see the list below:
The student is allowed to bring - USB key for uploading of notes, books and compendiums in a
non-executable format (no applications, application fragments, IT
tools etc.)
- Any calculator
- In Paper format: Books (including translation dictionaries),
compendiums and notes
The student will have access to - Access to Canvas
- Access to the personal drive (S-drive) on CBS´ network
- Advanced IT application package
|
| Make-up exam/re-exam |
Same examination form as the ordinary exam
The number of registered candidates for the make-up
examination/re-take examination may warrant that it most
appropriately be held as an oral examination. The programme office
will inform the students if the make-up examination/re-take
examination instead is held as an oral examination including a
second examiner or external
examiner.
|
|
| Course content, structure and pedagogical
approach |
|
The course provides the quantitative tools necessary for
successfully following courses like Investments, Empirical Finance,
and Derivatives and Fixed Income.
The topics covered include:
Analysis: Functions and their properties, Differentiation
and Taylor series approximations, Equation solving, Optimization
without or with constraints, Integration.
Linear Algebra: Vector and matrix algebra, Linear equation
systems.
Statistics: Random variables and probability
distributions, Inference, Hypothesis testing, Regression models,
Monte Carlo methods.
Examples from finance and economics are given throughout.
The course also introduces students to how IT tools
(e.g., Excel) can be used for solving quantitative problems in
finance.
|
| Research-based teaching |
|
CBS’ programmes and teaching are research-based. The following
types of research-based knowledge and research-like activities are
included in this course:
Research-based knowledge
- Classic and basic theory
- Methodology
- Models
Research-like activities
- Discussion, critical reflection, modelling
|
| Description of the teaching methods |
| Lectures, exercises, assignments |
| Feedback during the teaching period |
In the exercise sessions students have the
opportunity to check whether they are able to solve relevant
exercises.
Online or in-class quizzes may be added in order to give students
immediate feedback on their understanding of a given topic.
Students are encouraged to participate actively in lectures and
exercise classes through questions and comments upon which the
teachers try their best to provide immediate feedback. |
| Student workload |
| Lectures |
33 hours |
| Exercises |
14 hours |
| Preparation for lectures |
66 hours |
| Preparation for exercise classes |
66 hours |
| Exam |
4 hours |
| Final preparation for exam |
15 hours |
| Assignments |
8 hours |
|
| Expected literature |
|
Mandatory literature: selected chapters from
- Alexander, Carol. Market Risk Analysis, Volume 1: Quantitative
Methods in Finance, Wiley, 2009
Supplementary literature could include:
- Sydsæter, Hammond, Strøm and Carvajal: Essential Mathematics
for Economic Analysis; 5th ed., Pearson, 2016
- Robert L. McDonald: An Introduction to VBA in Excel, 2000,
downloadable
- Reference books on Excel and VBA. Popular bestsellers like
'Excel 2013 Bible' and 'Excel 2013 Power Programming
with VBA' by John Walkenbach are each very extensive (>1000
pages) and available on-line at CBS for free.
- David Skovmand: Supplementary Notes on: Linear Algebra,
Probability and Statistics for Empirical Finance, 2013,
downloadable.
|
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