Course Objective

The course builds on the mathematics that has been offered at high
school ("Wiskunde A"). After taking this course, the student should have
the knowledge:
- understands the concepts of differentiation, integration and
optimization of functions of one and more variables.
- is able to work with limits, sequences and series.
- is familiar with the basics of stochastic vectors and (multivariate)
probability density functions.

and quantitative skills:
- can analytically optimize (constrained) functions, applying his
knowledge about (partial) derivatives.
- is able to analyse linear regression models.

Course Content

In this Pre-MSc course, students study the necessary knowledge and
skills for quantitative analysis required throughout the MSc program. We
cover a broad range of topics, such that you can easily handle the
mathematical content encountered in the courses investments, Asset
Pricing, Derivatives and Empirical Finance. You develop a thorough
understanding of (partial) differentiation and optimization of functions
with one and more variables. In addition, you understand the concept of
limits, sequences and series, which are frequently used in time-series
models. Finally, you get a primer of stochastic vectors and multivariate
probability functions, which come back in the research methods related
topics in the master program. e.g. the linear regression model, which is
one of the most used models in finance.

Teaching Methods

The course consists of 18 sessions over a period of six weeks. Each
session takes 2 hours, and will be in particular instruction sessions
with the purpose of practicing by doing exercises. In addition, the
sessions will be brief lectures with the purpose of exposing the
subject matter.

Method of Assessment

The assessment consists of a final exam, which is made up of open


The course relies on the following book: K. Sydsaeter & P. Hammond,
Essential Mathematics for Economic Analysis, 5th Edition, Pearson, 2016,
ISBN 9781292074610. The VU-bookshop offers a special edition
with an access code for online training ("MyMathLab
Global access card"). Using MyMathLab is not mandatory for this course,
and it is not supported by the teachers. Additional documents that are
essential for this course will be available at the Canvas system.

Last modification: October 29, 2018

General Information

Course Code E_PM_MATH
Credits 6 EC
Period P4
Course Level 300
Language of Tuition English
Faculty School of Business and Economics
Course Coordinator dr. T. Artiga Gonzalez
Examiner dr. T. Artiga Gonzalez
Teaching Staff dr. L. Lu
dr. S.A. Borovkova
dr. T. Artiga Gonzalez

Practical Information

You need to register for this course yourself

Last-minute registration is available for this course.

Teaching Methods Lecture
Target audiences

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