ECTS - Computational Methods of Mathematical Finance
Computational Methods of Mathematical Finance (MATH417) Course Detail
| Course Name | Course Code | Season | Lecture Hours | Application Hours | Lab Hours | Credit | ECTS |
|---|---|---|---|---|---|---|---|
| Computational Methods of Mathematical Finance | MATH417 | 2 | 0 | 2 | 3 | 6 |
| Pre-requisite Course(s) |
|---|
| Math 316 |
| Course Language | English |
|---|---|
| Course Type | N/A |
| Course Level | Bachelor’s Degree (First Cycle) |
| Mode of Delivery | Face To Face |
| Learning and Teaching Strategies | Lecture, Question and Answer, Problem Solving. |
| Course Lecturer(s) |
|
| Course Objectives | The goal of the course is to introduce the students to numerical methods in finance and option theory. |
| Course Learning Outcomes |
The students who succeeded in this course;
|
| Course Content | Introduction to MATLAB, finite difference formulae, the explicit and implicit finite difference methods, The Crank-Nicolson method, European option pricing by the heat equation, pricing by the Black-Scholes equation, pricing by an explicit, an implicit and Crank-Nicolson method, pricing American options, projected SOR and tree methods, pseudo-rando |
Weekly Subjects and Releated Preparation Studies
| Week | Subjects | Preparation |
|---|---|---|
| 1 | Introduction to MATLAB | pp. 263-286 |
| 2 | Finite difference formulae | pp. 195-199 |
| 3 | The explicit finite difference method | pp. 203-214 |
| 4 | The fully implicit method | pp. 215-219 |
| 5 | The Crank-Nicolson method | pp. 220-225 |
| 6 | European option pricing by the heat equation | pp. 226-233 |
| 7 | Problem solving and review | |
| 8 | Midterm Exam | |
| 9 | Pricing by the Black-Scholes equation | pp. 234-244 |
| 10 | Pricing American options, Projected SOR and tree methods | pp. 245-262 |
| 11 | Pseudo-Random numbers, Inverse transform method | pp. 140-148 |
| 12 | Acceptance-Rejection and Box-Muller methods, The polar method of Marsaglia | pp. 149-155 |
| 13 | Monte Carlo integration | pp. 160-165 |
| 14 | Option pricing by Monte Carlo simulation | pp. 166-178 |
| 15 | Problem solving and review | |
| 16 | Final Exam |
Sources
| Course Book | 1. An Introduction to Computational Finance, Ö. Uğur, Imperial College Press, 2009. |
|---|---|
| Other Sources | 2. Options, Futures and Other Derivatives, J. Hull, Prentice Hall, 2006. |
| 3. The Mathematics of Financial Derivatives: A student introduction, P. Wilmott,S. Howison and J. Dewynne, Cambridge University Press, 1995. |
Evaluation System
| Requirements | Number | Percentage of Grade |
|---|---|---|
| Attendance/Participation | - | - |
| Laboratory | - | - |
| Application | - | - |
| Field Work | - | - |
| Special Course Internship | - | - |
| Quizzes/Studio Critics | - | - |
| Homework Assignments | 5 | 20 |
| Presentation | - | - |
| Project | - | - |
| Report | - | - |
| Seminar | - | - |
| Midterms Exams/Midterms Jury | 1 | 35 |
| Final Exam/Final Jury | 1 | 45 |
| Toplam | 7 | 100 |
| Percentage of Semester Work | 55 |
|---|---|
| Percentage of Final Work | 45 |
| Total | 100 |
Course Category
| Core Courses | |
|---|---|
| Major Area Courses | X |
| Supportive Courses | |
| Media and Managment Skills Courses | |
| Transferable Skill Courses |
The Relation Between Course Learning Competencies and Program Qualifications
| # | Program Qualifications / Competencies | Level of Contribution | ||||
|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | ||
| 1 | Has the ability to apply scientific knowledge gained in the undergraduate education and to expand and extend knowledge in the same or in a different area | X | ||||
| 2 | Can apply gained knowledge and problem solving abilities in inter-disciplinary research | X | ||||
| 3 | Has the ability to work independently within research area, to state the problem, to develop solution techniques, to solve the problem, to evaluate the obtained results and to apply them when necessary | X | ||||
| 4 | Takes responsibility individually and as a team member to improve systematic approaches to produce solutions in unexpected complicated situations related to the area of study | X | ||||
| 5 | Can develop strategies, implement plans and principles on the area of study and can evaluate obtained results within the framework | X | ||||
| 6 | Can develop and extend the knowledge in the area and to use them with scientific, social and ethical responsibility | X | ||||
| 7 | Has the ability to follow recent developments within the area of research, to support research with scientific arguments and data, to communicate the information on the area of expertise in a systematically by means of written report and oral/visual presentation | X | ||||
| 8 | To have an oral and written communication ability in at least one of the common foreign languages ("European Language Portfolio Global Scale", Level B2) | X | ||||
| 9 | Has software and hardware knowledge in the area of expertise, and has proficient information and communication technology knowledge | X | ||||
| 10 | Follows scientific, cultural, and ethical criteria in collecting, interpreting and announcing data in the research area and has the ability to teach. | X | ||||
| 11 | Has professional ethical consciousness and responsibility which takes into account the universal and social dimensions in the process of data collection, interpretation, implementation and declaration of results in mathematics and its applications. | X | ||||
ECTS/Workload Table
| Activities | Number | Duration (Hours) | Total Workload |
|---|---|---|---|
| Course Hours (Including Exam Week: 16 x Total Hours) | 16 | 2 | 32 |
| Laboratory | 16 | 2 | 32 |
| Application | |||
| Special Course Internship | |||
| Field Work | |||
| Study Hours Out of Class | 14 | 3 | 42 |
| Presentation/Seminar Prepration | |||
| Project | |||
| Report | |||
| Homework Assignments | 5 | 8 | 40 |
| Quizzes/Studio Critics | |||
| Prepration of Midterm Exams/Midterm Jury | 1 | 12 | 12 |
| Prepration of Final Exams/Final Jury | 1 | 20 | 20 |
| Total Workload | 178 | ||