Course Details

Course Information

Semester	Course Unit Code	Course Unit Title	T+P+L	Credit	Number of ECTS Credits	Last Updated Date
1	DSBE532	NUMERICAL METHODS FOR ADVANCED FINANCE	3+0+0	3	7,5	13.05.2025

Course Details

Language of Instruction	English
Level of Course Unit	Master's Degree
Department / Program	DATA SCIENCE
Type of Program	Formal Education
Type of Course Unit	Elective
Course Delivery Method	Face To Face
Objectives of the Course	Providing an understanding of fundamental concepts in financial econometrics for advanced finance. Analyzing volatility modeling, asymmetric volatility models and granger causality. Practicing applications of mathematical knowledge to financial accounts and models.
Course Content	In this course, it is aimed to provide necessary theoretical and practical background for devising financial analysis and financial models and solving financial problems by using basic statistical and mathematical concepts and tools. Subjects such as implementations of financial calculations and models in real problems, implementations of models and analysis techniques learnt throughout the course in financial problems by collecting data from existing sources, and related topics are covered.
Course Methods and Techniques	Traditional in class lectures and real life applications and cases will be utilized.
Prerequisites and co-requisities	None
Course Coordinator	Associate Prof.Dr. Umut Türk umut.turk@agu.edu.tr
Name of Lecturers	None
Assistants	None
Work Placement(s)	No

Recommended or Required Reading

Resources	-
Course Notes	Course materials will be provided throughout the semester

Course Category

Mathematics and Basic Sciences	%35
Social Sciences	%15
Field	%50

Planned Learning Activities and Teaching Methods

Activities are given in detail in the section of "Assessment Methods and Criteria" and "Workload Calculation"

Assessment Methods and Criteria

In-Term Studies	Quantity	Percentage
Yarıyıl İçi Çalışmalarının Başarı Notunun Katkısı	1	% 20
Quiz/Küçük Sınav	4	% 20
Ödev	4	% 20
Final examination	1	% 40
Total	10	% 100

ECTS Allocated Based on Student Workload

Activities	Quantity	Duration	Total Work Load
Yazılı Sınav	2	2	4
Ev Ödevi	3	15	45
Sınıf İçi Aktivitesi	3	10	30
Sunum için Hazırlık	1	20	20
Sunum	1	5	5
Kişisel Çalışma	14	4	56
Takım/Grup Çalışması	4	2	8
Yüz Yüze Ders	14	3	42
Derse Devam	14	1	14
Final Sınavı	1	2	2
Total Work Load			Number of ECTS Credits 7,5 226

Course Learning Outcomes: Upon the successful completion of this course, students will be able to:

No	Learning Outcomes
1	Explain how formulas used in advanced finance are found by combining basic finance information with mathematical and statistical concepts.
2	Apply financial calculations and models to real problems.
3	Apply the models and analysis techniques learned in the course to financial problems by collecting data from available sources.
4	Interpret data analysis results.

Weekly Detailed Course Contents

Week	Topics	Study Materials	Materials
1	Introduction and overview of financial econometrics	Review syllabus	Syllabus
2	Structure of financial data and descriptive statistics	Explore sample dataset	Lecture notes
3	Regression analysis: basic models	Revise basic regression concepts	Textbook chapter
4	Multiple regression and model assumptions	Prepare ANOVA example	Application file
5	Time series data and stationarity	Study the ADF test	Reading material
6	Autocorrelation and heteroskedasticity	Run example in EViews or R	Lecture notes
7	Volatility and ARCH/GARCH models	Prepare ARCH vs. GARCH comparison	Article
8	Midterm Exam	Review previous topics	-
9	Asymmetric volatility models (EGARCH, TGARCH)	Prepare dataset for volatility model	Academic paper
10	Granger causality test	Identify variable relationships	Application guideline
11	Simulation and Monte Carlo methods	Try basic Monte Carlo simulation	Lecture notes
12	Financial optimization and numerical solutions	Prepare optimization example in Excel/R	Software output
13	Student presentations and data-driven case studies	Finalize and rehearse project presentation	Presentation files
14	Final review and exam preparation	Review and solve sample questions	Course summary

Contribution of Learning Outcomes to Programme Outcomes

Contribution: 1: Very Slight 2:Slight 3:Moderate 4:Significant 5:Very Significant

https://sis.agu.edu.tr/oibs/bologna/progCourseDetails.aspx?curCourse=76793&lang=en