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2014/2015  KAN-CFIVO1001U  Quantitative Methods

English Title
Quantitative Methods

Course information

Language English
Course ECTS 7.5 ECTS
Type Mandatory
Level Full Degree Master
Duration One Semester
Course period Autumn
Timetable Course schedule will be posted at calendar.cbs.dk
Study board
Study Board for MSc in Economics and Business Administration
Course coordinator
  • Peter Raahauge - Department of Finance (FI)
Main academic disciplines
  • Finance
  • Statistics and mathematics
Last updated on 04-07-2014
Learning objectives
When presented with a problem dealt with in the course, the student should be able to solve the problem using the appropriate software in a way similar to how the problem was solved during the course. When presented with a problem, which is similar but different from the problems dealt with in the course, the student should be able to solve the problem, based on a theoretical understanding of the problems dealt with in the course.
Quantitative Methods:
Exam ECTS 7,5
Examination form Written sit-in exam
Individual or group exam Individual
Assignment type Written assignment
Duration 4 hours
Grading scale 7-step scale
Examiner(s) One internal examiner
Exam period December/January
Aids allowed to bring to the exam Limited aids, see the list below and the exam plan/guidelines for further information:
  • Additional allowed aids
  • Books and compendia brought by the examinee
  • Notes brought by the examinee
  • Allowed calculators
  • Allowed dictionaries
Make-up exam/re-exam
Same examination form as the ordinary exam
If the number of registered candidates for the make-up examination/re-take examination warrants that it may most appropriately be held as an oral examination, the programme office will inform the students that the make-up examination/re-take examination will be held as an oral examination instead.
Description of the exam procedure

Open book exam with limited Internet access.

Course content and structure

The course provides the quantitative tools necessary for following courses like Investments and Empirical Finance successfully.

The course takes a hands-on approach to the material, and a central part of course is worked examples (exercises with guiding solutions), which the students are supposed to implement using appropriate IT-tools like Excel, VBA, and/or R. The course uses a "flipped classroom" approach, see http://en.wikipedia.org/wiki/Flip_teaching: The theoretical foundation for the worked examples is explained using screencasts available on the Internet for viewing on demand. The students work with the worked examples. The scheduled classes are used for personalized guidance with respect to theory and implementation of the worked examples.

Theoretical topics covered in the worked examples include:

Analysis: Functions and their properties, Differentiation and Taylor series approximations, Equation solving, Optimization, Integration

Linear Algebra: Vector and matrix algebra, Linear equation systems

Statistics: Random variables and probability distributions, Inference, Hypothesis testing, Regression models, Panel data, Monte Carlo methods

To the extent the theoretical topics are known from prerequisite courses, the topics will be elaborated (ex: two- or N-dimensional stochastic distributions), addressed in alternative ways (ex: Monte Carlo "proof" of formulas for stochastic variables), and/or used to introduce software functionality.

IT topics covered in the worked examples, to the extend time permits, include:

Excel: Data import and data types, Formulas, references and names, Tables, Graphs, Solver add-in, Data analysis add-in

VBA: Functions, Subs, Local variables, Arrays, For-loops and If-statements, Debugging

R: RStudio IDE, Data import, Data types and selected functions, Scripts, Plots, For-loops and If-statements, Functions, Debugging, Random numbers and Monte Carlo analysis, Linear algebra, Optimization, Integration with Excel

Teaching methods
Flipped classroom with on-line lectures, worked examples (exercises with guiding solutions), and classes with personalized guidance.
Student workload
On-line lectures 33 hours
Preparation for on-line lectures 33 hours
Working with examples incl. reading and personalized guidance 140 hours
Exam 4 hours
Expected literature

Mandatory literature

  • Sydsæter and Hammond: Essential Mathematics for Economic Analysis; 3rd ed., 2008, Prentice Hall (or similar).
  • Braun and Murdoch: A First Course in Statistical Programming with R; 1st ed., 2007, Cambridge University Press (or similar).
  • David Skovmand: Supplementary Notes on: Linear Algebra, Probability and Statistics for Empirical Finance, 2013, downloadable.
  • Robert L. McDonald: An Introduction to VBA in Excel, 2000, downloadable.
  • Notes and Worked Examples.

Supplementary literature:

  • 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.
  • Selected sections of Financial Markets and Investments, Claus Munk, 2014, downloadable, will help motivating the curriculum.
Last updated on 04-07-2014