Course content

The topics taught in this course are:

• Optimization in complete financial plans
• Statistical analysis of stock prices and stock returns
• Computation of risk measures
• Portfolio construction and optimization
• Capital market models
• Option pricing models and option valuation
• Time series modeling
• Simulation.

Essential Excel capabilities to be employed are:

• Built-in and user defined Excel functions
• Related data tables and pivot tables
• Goal Seek and data tables
• Excel Solver
• Data Analysis Tool Pack
• Visual Basic for Application
• Intersection with other Software/Programming environments like Python and Matlab

Learning outcome

Knowledge

In this course the student strengthens and extents principles in finance, statistics, risk analysis and optimization.

Skills

In this course the student learns how to translate and implement financial data and financial models by means of Excel spreadsheets and Visual Basic for Applications.

• The student will be able to generate meaningful graphical representations of financial data, to statistically analyze financial data and to solve financial decision problems and market models.
• The student also learns how to identify properties of financial models with respect to software implementation and solvability.
• With respect to financial data and applications, the student will be able to use elementary and complex built-in Excel functions or add-inns like the Solver or Data Analysis Tool Pack.
• For problems that require repeated computations or do not fit into the two-dimensional spreadsheet representation, the student learns to use Visual Basic for Applications (VBA) and Office Scripts.
• The Student will be made aware of and acquire basic knowledge to use Excel within other programming environments like Python.

General competence

• The student learns how to apply his knowledge and skills in different practical situations.
• The student will be encouraged to reflect about advantages, shortcomings and further reaching implications of his models and solutions.

Learning methods and activities

Lectures (Physical or digital), videos and data exercises.

Compulsory assignments

• Two mandatory assignment

Required previous knowledge

This course requires knowledge from elementary courses in mathematics and statistics.

Course materials

The curriculum will be announced when the course commences and supplementary literature will be provided/referred to throughout the course.