Algorithmic Trade

Course Code:

AFN 420

Course Type:

Area Elective

P:

3

Application:

0

Credits:

3

ECTS:

6

Prerequisite Courses:

Statistics

Course Language:

İngilizce

Course Objectives:

With algorithmic trading, traders create their instructions based on conditions related to price, quantity and other market factors using a software, which automatically executes buy and sell orders as per the instructions. Use of algorithmic trading decreases human errors due to emotions or behaviour and allow investors consider several factors at the same time when trading. It also allows for faster trading, which is essential in markets today. This class is an introduction to algorithmic trading where we will learn how to create and execute algo trading methodologies. At the end of the class students will learn about algorithmic trading programs, have experience in basic algorithmic trading applications and understand pros and cons of algorithmic trading.

Course Content:

Algorithmic Trading, Fundamental Concepts, Algo Trading types and Strategies, Order Types, Execution Tactics, Multi-asset Trading, Reaction to News, Data Mining and Artificial Intelligence

Course Methodology:

1: Anlatım, 2: Soru-Cevap, 3: Tartışma, 4: Benzetim 5: Vaka Çalışması

Course Evaluation Methods:

A: Sınav, B: Sunum, C: Ödev, D: Proje, E: Laboratuvar

Vertical Tabs

Course Learning Outcomes

Learning Outcomes	Program Learning Outcomes	Teaching Methods	Assessment Methods
1. To be able to describe the fundamental concepts regarding algo trading	2,5	1, 2, 3, 5	A, B, C
2. to have an experience in algo trading application	2,5	1, 2, 3, 5	A, B, C
3. To be able to understand pros and cons of algo trading	1,2,5,7	1, 2, 3, 5	A, B, C

Course Flow

COURSE CONTENT
Week	Topics	Study Materials
1	Introduction
2	Fundamental Concepts,	Textbook and Lecture Notes
3	Fundamental Concepts	Textbook and Lecture Notes
4	Types of Algorithmic Trading	Textbook and Lecture Notes
5	Algo Trading Strategies	Textbook and Lecture Notes
6	Order Types	Textbook and Lecture Notes
7	Order Types	Textbook and Lecture Notes
8	Midterm Exam
9	Execution Orders	Textbook and Lecture Notes
10	Execution Orders	Textbook and Lecture Notes
11	Execution Orders	Textbook and Lecture Notes
12	Multi-asset Trading	Textbook and Lecture Notes
13	Reaction to News	Textbook and Lecture Notes
14	Data Mining and Artificial Intelligence	Textbook and Lecture Notes
15	Project Presentations	Textbook and Lecture Notes

Recommended Sources

Textbook	Algorithmic Trading & DMA: An introduction to direct access trading strategies, Barry Johnson, 4Myeloma Press, London
Additional Resources	Online resources

Material Sharing

Documents	Lecture Notes and Project Guidelines
Assignments
Exams	Midterm Exam and Final Exam

Assessment

ASSESSMENT
IN-TERM STUDIES	NUMBER	PERCENTAGE

Midterms	1	35
Homework/Case Studies	1	30
Total		100
CONTRIBUTION OF FINAL EXAMINATION TO OVERALL GRADE		35
CONTRIBUTION OF IN-TERM STUDIES TO OVERALL GRADE		65
Total		100

COURSE CATEGORY

Expertise/Field Courses

Course’s Contribution to Program

COURSE'S CONTRIBUTION TO PROGRAM
	Program Learning Outcomes	Contribution
	Program Learning Outcomes	1	2	3	4	5
	1. To understand the core principles of finance and to be able to apply them both nationally and internationally.						X
	2. To formulate solutions to finance problems by effectively using contemporary information technologies and up-to-date financial instruments.			X
	3. To judge the best possible outcome to problems that require ethical and social responsibility-based thinking by identifying stakeholders and weighing alternative solutions.	X
	4. To develop the necessary background to be able to work in multicultural and multilingual environments.	X
	5. To analyze the developments in financial markets by interpreting and distinguishing among the factors affecting them.					X
	6. To recognize management tools and models specific to multinational companies and to be able to apply them where necessary.
	7. To understand the structure of the global economic system and to be able to analyze how new developments will affect this structure.	X
	8. To be able to use critical thinking ability in decision making process.						X
	9. To develop and demonstrate the leadership, teamwork and communication skills that may be transferred to the lifelong learning process.
	10. To interpret environmental and sustainability issues by implementing quality management processes.

ECTS

ECTS ALLOCATED BASED ON STUDENT WORKLOAD BY THE COURSE DESCRIPTION
Activities	Quantity	Duration (Hour)	Total Workload (Hour)
Course Duration (Including the exam week: 16x Total course hours)	15	3	45
Hours for off-the-classroom study (Pre-study, practice)	15	4	60
Mid-terms	1	12,5	12,5
Project	1	3	30
Final examination	1	10	10
Total Work Load			157,5
Total Work Load / 25 (h)			6,30
ECTS Credit of the Course			6

None

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