FACULTY OF ENGINEERING

Department of Industrial Engineering

IE 375 | Course Introduction and Application Information

Course Name
Financial Engineering
Code
Semester
Theory
(hour/week)
Application/Lab
(hour/week)
Local Credits
ECTS
IE 375
Fall/Spring
3
0
3
5

Prerequisites
None
Course Language
English
Course Type
Elective
Course Level
First Cycle
Mode of Delivery -
Teaching Methods and Techniques of the Course Lecture / Presentation
Course Coordinator
Course Lecturer(s)
Assistant(s) -
Course Objectives To familiarize students both with the concepts underlying the economic analysis of engineering projects, as well as with the type of mathematical derivations needed in the analysis.
Learning Outcomes The students who succeeded in this course;
  • Will be able to familiarize with the concepts underlying the economic analysis of engineering projects
  • Will be able to develop related mathematical derivations needed in the analysis
  • Will be able to evaluate investment opportunities
  • Will be able to determine optimal decisions by using mathematical optimization models
  • Will be able to solve sequential optimization problems by using simulation models
Course Description Students will learn to make decisions by taking into account such features as interest rates, and rates of return. They will learn about the concept of arbitrage, and when consideration of such is sufficient to price different investments. Applications to call and put options will be given. Students will learn when arbitrage arguments are not sufficient to evaluate investment opportunities. They will learn to make use of utility theory and mathematical optimization models to determine optimal decisions. Dynamic programming will be introduced and used to solve sequential optimization problems. The use of simulation in financial engineering will be explored.

 



Course Category

Core Courses
Major Area Courses
X
Supportive Courses
Media and Management Skills Courses
Transferable Skill Courses

 

WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

Week Subjects Related Preparation
1 Introduction, Interest Rates and Present Value An Elementary Introduction to Mathematical Finance: Options and Other Topics, Second ed., Sheldon Ross, Cambridge University Press, 2003 Ch1
2 Rate of Returns An Elementary Introduction to Mathematical Finance: Options and Other Topics, Second ed., Sheldon Ross, Cambridge University Press, 2003 Ch2
3 Arbitrage and its use in Pricing An Elementary Introduction to Mathematical Finance: Options and Other Topics, Second ed., Sheldon Ross, Cambridge University Press, 2003 Ch3
4 The Arbitrage Theorem An Elementary Introduction to Mathematical Finance: Options and Other Topics, Second ed., Sheldon Ross, Cambridge University Press, 2003 Ch3
5 Applications of the Arbitrage Theorem An Elementary Introduction to Mathematical Finance: Options and Other Topics, Second ed., Sheldon Ross, Cambridge University Press, 2003 Ch3
6 Review and Midterm Exam
7 Geometric Brownian Motion An Elementary Introduction to Mathematical Finance: Options and Other Topics, Second ed., Sheldon Ross, Cambridge University Press, 2003 Ch4
8 Option Pricing Theory An Elementary Introduction to Mathematical Finance: Options and Other Topics, Second ed., Sheldon Ross, Cambridge University Press, 2003 Ch5
9 Optimization Models in Financial Engineering An Elementary Introduction to Mathematical Finance: Options and Other Topics, Second ed., Sheldon Ross, Cambridge University Press, 2003 Ch6
10 Solving Optimization Models by Dynamic Programming An Elementary Introduction to Mathematical Finance: Options and Other Topics, Second ed., Sheldon Ross, Cambridge University Press, 2003 Ch6
11 Dynamic Programming models An Elementary Introduction to Mathematical Finance: Options and Other Topics, Second ed., Sheldon Ross, Cambridge University Press, 2003 Ch6
12 Pricing by Expected Utility An Elementary Introduction to Mathematical Finance: Options and Other Topics, Second ed., Sheldon Ross, Cambridge University Press, 2003 Ch7
13 Simulation and Variance Reduction An Elementary Introduction to Mathematical Finance: Options and Other Topics, Second ed., Sheldon Ross, Cambridge University Press, 2003 Ch8
14 Simulation Analysis of Exotic Options and Final Review An Elementary Introduction to Mathematical Finance: Options and Other Topics, Second ed., Sheldon Ross, Cambridge University Press, 2003 Ch8
15 General review and evaluation
16 Review of the Semester  

 

Course Notes/Textbooks Textbook: An Elementary Introduction to Mathematical Finance: Options and Other Topics, Second ed., Sheldon Ross, Cambridge University Press, 2003
Suggested Readings/Materials

 

EVALUATION SYSTEM

Semester Activities Number Weigthing
Participation
1
10
Laboratory / Application
Field Work
Quizzes / Studio Critiques
Portfolio
Homework / Assignments
10
10
Presentation / Jury
1
10
Project
Seminar / Workshop
Oral Exams
Midterm
1
30
Final Exam
1
40
Total

Weighting of Semester Activities on the Final Grade
28
60
Weighting of End-of-Semester Activities on the Final Grade
1
40
Total

ECTS / WORKLOAD TABLE

Semester Activities Number Duration (Hours) Workload
Theoretical Course Hours
(Including exam week: 16 x total hours)
16
3
48
Laboratory / Application Hours
(Including exam week: '.16.' x total hours)
16
0
Study Hours Out of Class
14
2
28
Field Work
0
Quizzes / Studio Critiques
0
Portfolio
0
Homework / Assignments
10
2
20
Presentation / Jury
1
15
15
Project
0
Seminar / Workshop
0
Oral Exam
0
Midterms
1
17
17
Final Exam
1
22
22
    Total
150

 

COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

#
Program Competencies/Outcomes
* Contribution Level
1
2
3
4
5
1

To have adequate knowledge in Mathematics, Science and Industrial Engineering; to be able to use theoretical and applied information in these areas to model and solve Industrial Engineering problems.

X
2

To be able to identify, formulate and solve complex Industrial Engineering problems by using state-of-the-art methods, techniques and equipment; to be able to select and apply proper analysis and modeling methods for this purpose.

X
3

To be able to analyze a complex system, process, device or product, and to design with realistic limitations to meet the requirements using modern design techniques.

4

To be able to choose and use the required modern techniques and tools for Industrial Engineering applications; to be able to use information technologies efficiently.

X
5

To be able to design and do simulation and/or experiment, collect and analyze data and interpret the results for investigating Industrial Engineering problems and Industrial Engineering related research areas.

6

To be able to work efficiently in Industrial Engineering disciplinary and multidisciplinary teams; to be able to work individually.

7

To be able to communicate effectively in Turkish, both orally and in writing; to be able to author and comprehend written reports, to be able to prepare design and implementation reports, to present effectively; to be able to give and receive clear and comprehensible instructions

8

To have knowledge about contemporary issues and the global and societal effects of Industrial Engineering practices on health, environment, and safety; to be aware of the legal consequences of Industrial Engineering solutions.

9

To be aware of professional and ethical responsibility; to have knowledge of the standards used in Industrial Engineering practice.

10

To have knowledge about business life practices such as project management, risk management, and change management; to be aware of entrepreneurship and innovation; to have knowledge about sustainable development.

X
11

To be able to collect data in the area of Industrial Engineering; to be able to communicate with colleagues in a foreign language.

12

To be able to speak a second foreign at a medium level of fluency efficiently.

13

To recognize the need for lifelong learning; to be able to access information, to be able to stay current with developments in science and technology; to be able to relate the knowledge accumulated throughout the human history to Industrial Engineering.

X

*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest

 


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