Statusmelding

Kun tilgjengelig på engelsk

FIN 3616 Financial Modelling in Practice

FIN 3616 Financial Modelling in Practice

Course code: 
FIN 3616
Department: 
Finance
Credits: 
7.5
Course coordinator: 
Ivan Alfaro
Course name in Norwegian: 
Financial Modelling in Practice
Product category: 
Bachelor
Portfolio: 
Bachelor of Finance - Programme Courses
Semester: 
2023 Spring
Active status: 
Active
Level of study: 
Bachelor
Teaching language: 
English
Course type: 
One semester
Introduction

A central element of the job of any professional in corporate finance, fund management, security analysis, or risk management is the real-world application of financial theories to provide quantitative answers to various problems. As those theories are usually presented in a sterile, simplified environment for pedagogical reasons, it is often not straightforward how they can be implemented in practice. This course aims at showing students how the sometimes abstract models and theories are used to address real-world problems encountered in practice. The practical implementation of the theories and models also facilitates the complete understanding of them. Additionally the students will be benefited by having created throughout the course a collection of templates that can be readily used later on in practice.

Probably the most widely used tool by financial practitioners is Excel. During the course students will learn how to use this powerful program to apply a series of financial models which the students will likely have encountered in their previous courses. For each concept applied the course will provide a brief overview of the relevant theory or model but focus mostly on the practical side of the implementation. It will explain how these models can be implemented in Excel using its built-in functions, matrix calculation, and programming language (VBA). The course will also highlight which real-world financial data is the appropriate input for those models. It will point out different modeling options and discuss advantages and limitations of those approaches. The content of the course will employ theories that have been taught in previous classes. In various areas, the course will delve deeper and provide students with state of the art models that go beyond what was covered in previous courses. Thus, a good understanding of the material covered in the previous finance courses is required to fully benefit from this course.

Learning outcomes - Knowledge

The students will acquire a good understanding of how different financial models can be efficiently implemented with the help of a spreadsheet program. More specifically the students will develop an understanding of the following topics:

  • Basic financial calculations (present value, future value, NPV, IRR, etc)
  • Portfolio optimization and Black-Litterman model
  • Corporate valuation model (WACC, enterprise value)
  • Excel VBA programming
  • Monte Carlo simulation in Excel
Learning outcomes - Skills

During the acquisition of the above mentioned knowledge the students will acquire the following skills:

  • Advanced Excel handling: functions, matrix calculation, Excel solver, data table
  • Solving optimal portfolio in Excel, such as:
    • How to solve retirement planning problem in Excel
    • How to construct optimal portfolio using historical data and Excel
    • Working knowledge of Bloomberg
  • Solve financial problems using Excel, such as:
    • How to evaluate stock price using corporate valuation theory
  • Programming skills in Excel VBA, such as: 
    • How to write new functions in Excel VBA
  • Simulate financial models in Excel
General Competence

The students having successfully completed this course will be able not only to apply the various finance models and theories taught throughout their studies but also understand the applicability of these theories in light of the working assumptions required for those theories to be useful in practice.

Course content
  • Introduction to Excel and Bloomberg
  • Valuation and Capital Budgeting
  • Portfolio Choice and Black-Litterman Model
  • CAPM and Cost of Capital
  • Excel VBA Programming
  • Monte Carlo Simulation in Excel
Teaching and learning activities

Excel provides a completely digital platform that can easily connect data, analysis, and results. To take advantage of this digital platform, this course provides students trainings to describe, abstract, and solve challenging problems in a digital way. Given the global impact of Excel, mastering Excel is essential for the international job market.

The course will include a combination of lectures and computer workshops. The lectures will focus on the exposition of the relevant theories as well as the exposition of the assumptions and limitations of the theories. The workshops will be based on hands-on experience of both the implementation of the models and the development of Excel capabilities. One or more lecture and workshop sessions will be spent on Bloomberg with the focus on how to obtain and transfer data to Excel.

The lectures will be plenary sessions. The computer workshops (Excel and Bloomberg workshops) may be divided into multiple repeating sessions due to limited room capacity. Moreover, students may be provided a virtual machine during the semester that will run the exact same version of Excel and same operating system for all students. This will allow students to have a common learning environment and software to use during the Workshops.

This is a course with continuous assessment (several exam components) and one final exam code. Each exam component is graded by using points on a scale from 0-100. All components will be weighted together according to the information below in order to calculate the final letter grade for the examination code (course). Students who fail to participate in one/some/all exam elements will get a lower grade or may fail the course. Specific information regarding student evaluation beyond the information given in the course description will be provided in class.

At re-sit all exam components must, as a main rule, be retaken during next scheduled course.

Course is taught in English. Depending of the pace of the course (e.g., Covid-19 limitations, general skill set of students at the beginning of the course, etc.,), there may be deviations in teaching and learning activities as well as exams, compared to what is described in this course description.

Software tools
Software defined under the section "Teaching and learning activities".
Additional information

At re-sit it will be required that the entire evaluation process is conducted again, and that students who do not achieve points in one or more exam components will get a lower grade or fail the course. Previously conducted examination components will not be part of the assessment for a new grade.

Qualifications

Higher Education Entrance Qualification

Disclaimer

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

Required prerequisite knowledge

FIN 3521 Corporate Finance or EXC3671 Corporate Finance, or equivalent.

Assessments
Assessments
Exam category: 
Submission
Form of assessment: 
Written submission
Weight: 
30
Grouping: 
Group (2 - 4)
Duration: 
1 Semester(s)
Comment: 
group assignments
Exam code: 
FIN36161
Grading scale: 
Point scale leading to ECTS letter grade
Resit: 
All components must, as a main rule, be retaken during next scheduled course
Exam category: 
Submission
Form of assessment: 
Written submission
Invigilation
Weight: 
70
Grouping: 
Individual
Support materials: 
  • BI-approved exam calculator
  • Simple calculator
  • Bilingual dictionary
  • Interest table
Duration: 
3 Hour(s)
Comment: 
Final Exam
Exam code: 
FIN36161
Grading scale: 
Point scale leading to ECTS letter grade
Resit: 
All components must, as a main rule, be retaken during next scheduled course
Type of Assessment: 
Continuous assessment
Grading scale: 
ECTS
Total weight: 
100
Student workload
ActivityDurationComment
Teaching
21 Hour(s)
Seminar groups
21 Hour(s)
Computer workshops.
Prepare for teaching
42 Hour(s)
Submission(s)
84 Hour(s)
Student's own work with learning resources
32 Hour(s)
Sum workload: 
200

A course of 1 ECTS credit corresponds to a workload of 26-30 hours. Therefore a course of 7,5 ECTS credit corresponds to a workload of at least 200 hours.