Financial Model Implementation and Practice

Study Board of Market and Management Anthropology, Economics, Mathematics-Economics, Environmental and Resource Management

Teaching language: English
EKA: B560030112, B560030102
Censorship: Second examiner: None
Grading: Pass/Fail, 7-point grading scale
Offered in: Odense
Offered in: Summer school (spring)
Level: Master

Course ID: B560030101
ECTS value: 10

Date of Approval: 25-09-2018


Duration: Intensive course

Course ID

B560030101

Course Title

Financial Model Implementation and Practice

Teaching language

English

ECTS value

10

Responsible study board

Study Board of Market and Management Anthropology, Economics, Mathematics-Economics, Environmental and Resource Management

Date of Approval

25-09-2018

Course Responsible

Name Email Department
Mo Zhang mo@sam.sdu.dk

Offered in

Odense

Level

Master

Offered in

Summer school (spring)

Duration

Intensive course

Mandatory prerequisites

None.

Recommended prerequisites

The basic operations in spreadsheet program like Microsoft are required. Furthermore, this course requires that the student has prior knowledge of financial instruments (e.g. fix income securities, stocks, options) and corporate finance. The student must have an elementary background in mathematics, matrix algebra, statistics and econometrics. The student is familiar with simple optimization methods (e.g., first-order conditions and Lagrange optimization). 

Aim and purpose

The course is numerically intensive and requires a considerable amount of student input. This purpose of the course is that the students can implement some important financial models with extensive use of computer software, for example, Excel/VBA, or other programming languages agreed between the instructor and student, and develop modelling skills for analyzing a variety of financial decision problems by using real-world data. The student obtains competencies to master modelling techniques such as regression analysis, optimization, Monte-Carlo simulation, and binomial trees; and, the student can apply these modelling skills in specific financial contexts such as portfolio management, option pricing, financial risk management, sensitivity analysis in discounted cash flow models and term-structure estimation.

Content

The course is constructed to cover a wide variety of topics in financial modelling:

For example:

  1. Corporate valuation in terms of Discounted Cash Flow models
  2. Portfolio optimization problem in finance
  3. Valuation of options
  4. Fixed income analytics
  5. Financial Risk modelling

Learning goals

To fulfill the purposes of the course the student must be able to:

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

The preparation package will be given two weeks before lecture starts to help the student to get familiar with the theories and models which will be used during lectures.

Workload

Scheduled classes:
  • 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

Exam

Timing

Take-home assignment (part 1):
Exam: August
Reexam: September


Written exam (part 2):
Exam: August
Reexam: September

Tests

Take-home assignment (part 1)

Name

Take-home assignment (part 1)

Form of examination

Take-home assignment

Censorship

Second examiner: None

Grading

Pass/Fail

Identification

Student Identification Card - Exam number

Language

English

Duration

24 hours. Date for submission will appear from the examination plan.

Length

No limitations.

Examination aids

All exam aids allowed. However, it is not allowed to communicate with anybody.

Assignment handover

Course page in Blackboard.

Assignment handin

Via SDUassignment in the course page in Blackboard.

ECTS value

3

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

B560030112

Written exam (part 2)

Name

Written exam (part 2)

Form of examination

Written examination on premises

Censorship

Second examiner: None

Grading

7-point grading scale

Identification

Student Identification Card - Exam number

Language

English

Duration

4 hours

Length

No limitations

Examination aids

All exam aids allowed except for use of the internet. However, it is not allowed to communicate with anybody. 

Assignment handover

In the examination room.

Assignment handin

Via SDUassignment in the course page in Blackboard.

ECTS value

7

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

B560030102

External comment

The student is automatically registered for the first examination attempt when the student is registered for a course or course element with which one or more examinations are associated. Withdrawal of registration is not possible, and students who fail to participate in an examination have used one examination attempt, unless the University has made an exemption due to special circumstances. 


Courses offered

Offer period Offer type Profile Education Semester
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Teachers

Name Email Department City
Mo Zhang mo@sam.sdu.dk Odense

URL for Skemaplan