ECTS - Mathematics of Financial Derivatives
Mathematics of Financial Derivatives (MATH316) Course Detail
| Course Name | Course Code | Season | Lecture Hours | Application Hours | Lab Hours | Credit | ECTS |
|---|---|---|---|---|---|---|---|
| Mathematics of Financial Derivatives | MATH316 | Elective Courses | 3 | 0 | 0 | 3 | 6 |
| Pre-requisite Course(s) |
|---|
| N/A |
| Course Language | English |
|---|---|
| Course Type | Elective Courses |
| Course Level | Bachelor’s Degree (First Cycle) |
| Mode of Delivery | Face To Face |
| Learning and Teaching Strategies | Lecture, Question and Answer, Drill and Practice. |
| Course Lecturer(s) |
|
| Course Objectives | Mathematical modelling of finance is a new area of application of mathematics; it is expanding rapidly and has great importance for world financial markets. The course is concerned with the valuation of financial instruments known as derivatives. The course aims to enable students to acquire active knowledge and understanding of some basic concepts in financial mathematics including stochastic models for stocks and pricing of financial derivatives. |
| Course Learning Outcomes |
The students who succeeded in this course;
|
| Course Content | Introduction to options and markets, European call and put options, arbitrage, put call parity, asset price random walks, Brownian motion, Ito?s Lemma, derivation of Black-Scholes formula for European options, Greeks, options for dividend paying assets, multi-step binomial models, American call and put options, early exercise on calls and puts on a |
Weekly Subjects and Releated Preparation Studies
| Week | Subjects | Preparation |
|---|---|---|
| 1 | Introduction to Options and Markets, Probability | pp. 1-13 Other source 2: pp. 1-25 |
| 2 | Brownian motion (Weiner Process), Geometric Brownian Motion | Other source 2: pp. 26-35 |
| 3 | Asset price random walks, Ito’s Lemma | pp. 18-30 |
| 4 | One step and multi-step binomial model for option pricing | pp. 180-187 |
| 5 | European call and put options. Payoffs and strategies, No arbitrage principle | pp. 33-40 |
| 6 | Black-Scholes equation, Final and boundary conditions | pp. 41-48 |
| 7 | Problem solving and review | |
| 8 | Midterm | |
| 9 | Greeks, Hedging | pp. 51-52 |
| 10 | Options for dividend payoff assets | pp. 90-97 |
| 11 | American call and put options, early exercise on calls and puts on a non-dividend-paying stocks | pp. 106-108 |
| 12 | American options as the free boundary value problems | pp. 109-120 |
| 13 | Exotic options | pp. 195-209 |
| 14 | Interest rate models. | pp. 263-268 |
| 15 | Problem solving and review | |
| 16 | Final Exam |
Sources
| Course Book | 1. The Mathematics of Financial Derivatives: A student introduction, P. Wilmott,S. Howison and J. Dewynne, Cambridge University Press, 1995. |
|---|---|
| Other Sources | 2. Options, Futures and Other Derivatives, J. Hull, Prentice Hall, 2006. |
| 3. . An Elementary Introduction to Mathematical Finance. Options and Other Topics. (Second Edition), by Sheldon M. Ross, Cambridge University Press, 2003, | |
| 4. An Introduction to the Mathematics of Financial Derivatives, by Salih N. Neftci, Academic Press, 2000. |
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 | Acquires skills to use the advanced theoretical and applied knowledge obtained at the mathematics bachelors program to do further academic and scientific research in both mathematics-based graduate programs and public or private sectors. | X | ||||
| 2 | Transplants and applies the theoretical and applicable knowledge gained in their field to the secondary education by using suitable tools and devices. | X | ||||
| 3 | Acquires the skill of choosing, using and improving problem solving techniques which are needed for modeling and solving current problems in mathematics or related fields by using the obtained knowledge and skills. | X | ||||
| 4 | Acquires analytical thinking and uses time effectively in the process of deduction | X | ||||
| 5 | Acquires basic software knowledge necessary to work in the computer science related fields and together with the skills to use information technologies effectively. | X | ||||
| 6 | Obtains the ability to collect data, to analyze, interpret and use statistical methods necessary in decision making processes. | X | ||||
| 7 | Acquires the level of knowledge to be able to work in the mathematics and related fields and keeps professional knowledge and skills up-to-date with awareness in the importance of lifelong learning. | X | ||||
| 8 | Takes responsibility in mathematics related areas and has the ability to work affectively either individually or as a member of a team. | X | ||||
| 9 | Has proficiency in English language and has the ability to communicate with colleagues and to follow the innovations in mathematics and related fields. | X | ||||
| 10 | Has the ability to communicate ideas with peers supported by qualitative and quantitative data. | X | ||||
| 11 | Has professional and 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) | |||
| Laboratory | |||
| Application | |||
| Special Course Internship | |||
| Field Work | |||
| Study Hours Out of Class | 14 | 3 | 42 |
| Presentation/Seminar Prepration | |||
| Project | |||
| Report | |||
| Homework Assignments | 5 | 10 | 50 |
| Quizzes/Studio Critics | |||
| Prepration of Midterm Exams/Midterm Jury | 1 | 16 | 16 |
| Prepration of Final Exams/Final Jury | 1 | 22 | 22 |
| Total Workload | 130 | ||