
Financial Model Implementation and Practice
Course ID
Course Title
Teaching language
ECTS value
Responsible study board
Date of Approval
Course Responsible
Offered in
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Offered in
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Mandatory prerequisites
Recommended prerequisites
Aim and purpose
Content
The course is constructed to cover a wide variety of topics in financial modelling:
For example:
- Corporate valuation in terms of Discounted Cash Flow models
- Portfolio optimization problem in finance
- Valuation of options
- Fixed income analytics
- Financial Risk modelling
Learning goals
Description of outcome - Knowledge
Demonstrate knowledge about the course’s focus areas enabling the student to
- Explain the model choice for selected research topics.
- Explain the parameters, characteristics of selected empirical models, e.g. ARCH, GARCH.
- Understand simulation techniques, e.g. Monte Carlo simulation, that can be used to compute values of complicated functions that often have no analytical solution.
Description of outcome - Skills
Demonstrate skills, such that the student is able to:
- Implement theoretical models and numerical computation for enterprise valuation.
- Calculate the variance-covariance matrix and Find optimal portfolios.
- Back-test portfolio performance.
- Apply option pricing models, e.g. the binomial model and alternative models.
- Analyze fixed income attributions, e.g. term structure, duration, with selected models.
- Measure financial risk with Value-at-risk and alternative models.
- Apply numerical methods e.g. Monte Carlo simulation, to the pricing of derivatives, portfolio optimization, and financial risk management.
Description of outcome - Competences
Demonstrate competences, such that the student is able to:
- Use software (for example, Excel/VBA, or alternative software agreed between the student and instructor) to skillfully implement financial models introduced in the course in order to make empirical financial analysis.
- Discuss the meaning of empirical results and the plausible values of its parameters.
- Compare the advantages and disadvantages of different models and argue his/her model choice for specific dataset.
Literature
Examples
- Benninga, Simon: “Financial modelling” The MIT press, newest edition.
- Reading package and lecture notes.
Teaching Method
Workload
- 6 hours of lectures per day (6x5) for 2 consecutive weeks
- Each six-hour teaching session mixes the lecture and in-class exercises
- The course will be conducted in the second half of August
Workload:
The students' workload is expected to be distributed as follows:
Lectures: 60 hours
Preparation, lectures: 140 hours
Preparation, exam: 62 hours
Exam: 8 hours
Total: 270 hours
Examination regulations
Exam
Name
Timing
Take-home assignment (part 1):
Exam: August
Reexam: September
Tests
Take-home assignment (part 1)
Name
Form of examination
Censorship
Grading
Identification
Language
Duration
Length
Examination aids
Assignment handover
Assignment handin
ECTS value
Additional information
The assignment will be handed over at noon (12:00) on the Friday of the first teaching week.
Reexam in same exam term. Form of examination can be changed with short notice.
EKA
Written exam (part 2)
Name
Form of examination
Censorship
Grading
Identification
Language
Duration
Length
Examination aids
Assignment handover
Assignment handin
ECTS value
Additional information
The exam will be on the first Monday after two-week lectures.
The exam tests the achievement of the goals for all the goals mentioned (cf. the goal description) by random check.
Reexam in same exam term. Form of examination can be changed with short notice.
EKA
External comment
Courses offered
Offer period | Offer type | Profile | Education | Semester |
---|---|---|---|---|
Spring 2019 | Optional | Accounting and Finance | MSc in Economics and Business Administration | Master of Science (Msc) in Economics and Business Administration | Esbjerg, Soenderborg, Slagelse, Odense, Kolding | |
Spring 2019 | Optional | Master of Science in Economics (with profile in Health Care Management and Economics) | MSc in Economics | Master of Science (MSc) in Economics | Odense | |
Spring 2019 | Optional | Master of Science in Economics (with profile in Finance and Economics) | MSc in Economics | Master of Science (MSc) in Economics | Odense | |
Spring 2019 | Optional | Master of Science in Economics (with profile in Microeconomics) | MSc in Economics | Master of Science (MSc) in Economics | Odense | |
Spring 2019 | Optional | Master of Science in Economics (with profile in Accounting and Economics) | MSc in Economics | Master of Science (MSc) in Economics | Odense | |
Spring 2019 | Optional | Master of Science in Economics (with profile in Macroeconomics: Growth and Fluctuations) | MSc in Economics | Master of Science (MSc) in Economics | Odense | |
Spring 2019 | Optional | Master of Science in Economics (with profile in Economics) | MSc in Economics | Master of Science (MSc) in Economics | Odense | |
Spring 2019 | Optional | Master of Science in Economics (with profile in Economics and Project Management) | MSc in Economics | Master of Science (MSc) in Economics | Odense | |
Spring 2019 | Optional | Master of Science in Economics (with profile in Finance) | MSc in Economics | Master of Science (MSc) in Economics | Odense |