Financial Data Forecasting

Program Type:

Thesis

Non Thesis

Course Code:

FE 621

P:

3

Lab:

0

Credits:

3

ECTS:

10

Course Language:

English

Course Objectives:

The aim of this course is to teach the student how to model volatility with high frequency data, interpret hedge ratios and use option pricing. Models will be transferred to students theoretically and practically. Thus, it will be ensured that the student learns to make financial estimations with a lower margin of error.

Course Content:

The course starts with the concept of volatility; recognition of high frequency data, modeling of volatility, measures of volatility, estimation and estimation of volatility. Afterwards, the models are expanded with multiple models and hypothesis testing. These stages are reinforced with various applications. In the last stage, hedging rates and option pricing are handled by establishing a connection with the previously discussed topics.

Teaching Methods:

1: Lecture, 2: Question-Answer, 3: Discussion, 4: Simulation, 5: Case Study

Assessment Methods:

A: Testing, B: Experiment, C: Homework, Q: Quiz

Vertical Tabs

Course Learning Outcomes

Learning Outcomes	Programme Learning Outcomes	Teaching Methods	Assessment Methods


Covering regression models, predictions and problems in regression	1,2,3,5	1,2,3	A, C
Understanding and using Econometric models to be used in program courses	1,2,3,5	1,2,3	A, C
Modeling high frequency volatility and using models	1, 5	1,2,3	A, C
Comprehensive review of ARCH, GARCH, APARCH, FIGARCH, FIAPARCH models	1, 5	1,2,3	A, C
Giving the necessary theoretical and applied econometrics knowledge for thesis writing	1, 2, 5	1,2,3	A, C
Being able to recognize and apply multiple models and hypothesis tests	1, 2, 5	1,2,3	A, C
Acquisition of asset pricing techniques with machine learning	1, 2, 5	1,2,3	A, C
Interpretation of hedge ratios and predictions of models	1, 2, 5	1,2,3	A, C
Ability to price options	1, 2, 5	1,2,3	A, C

Course Flow

COURSE CONTENT
Week	Topics	Study Materials
1	Introduction	Chapter 1
2	Analysis of High Frequency Financial Data	Chapter 2
3	Modeling and Realization of Volatility	Chapter 3
4	Day Volatility Measures	Chapter 4
5	Day Volatility Patterns	Chapter 5
6	Day Volatility Patterns	Chapter 6
7	Midterm Exam	Chapter 7
8	Estimating Volatility	Chapter 8
9	Multiple Models and Hypothesis Testing	Chapter 9
10	Applications
11	HAR-RV-J and HEAVY Models	Chapter 10
12	Hedge Rates	Chapter 11
13	Option Pricing	Chapter 12
14	End of Term Activities
15	Final sınavı	All Content

Recommended Sources

RECOMMENDED SOURCES
Textbook			- Stavros Degiannakis and Christos Floros, (2015). Forecasting High Frequency Financial Data, Palgrave Macmillan
Additional Resources			Course Notes Course website, lecture notes, financial markets laboratory, financial calculator, online resources, excel type software.

Material Sharing

MATERIAL SHARING
Documents			Guidelines and additional examples for Lecture Topics and Homework Assignments
Assignments			Homework assignments
Exams			Midterm Exam and Final Exam

Assessment

ASSESSMENT
IN-TERM STUDIES	NUMBER	PERCENTAGE
Mid-Term	1	20
Class Performance	6	20
Final Exam	1	60
	Total	100
CONTRIBUTION OF FINAL EXAMINATION TO OVERALL GRADE		60
CONTRIBUTION OF IN-TERM STUDIES TO OVERALL GRADE		40
	Total	100

Course’s Contribution to Program

COURSE'S CONTRIBUTION TO PROGRAMME
No	Program Learning Outcomes	Contribution
No	Program Learning Outcomes	1	2	3	4	5
1	To comprehend the basic principles of finance and to be able to apply these principles in national and international areas.					X
2	To use modern information technologies and current financial tools effectively.		X
3	To comprehend the ethical rules and social responsibility understanding accepted by financial professional organizations and to apply them in the decisions to be taken.		X
4	To have the infrastructure that will enable them to do business in multicultural, multilingual and interdisciplinary environments.
5	To have information about the markets and the functioning of the markets and to analyze the developments in these markets.			X
6	To recognize the 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 analyze how new developments will affect this structure.
8	To be able to use the ability of critical thinking in the decision making process.		X
9	To transfer the acquired leadership, teamwork and communication skills to the lifelong learning process.
10	To be able to manage the process with analytical and creative approaches by anticipating the opportunities and problems that dynamic working conditions may create.

ECTS

ECTS ALLOCATED BASED ON STUDENT WORKLOAD BY THE COURSE DESCRIPTION

Activities	Quantity	Duration (Hour)	Total Workload (Hour)
Course Duration (Including the exam week: 15x Total course hours/week)	16	3	48
Hours for off-the-classroom study (Pre-study, practice, review/week)	16	4	96
Homework	5+1(Proje)	60	60
Mid-term	1	10	20
Final	1	15	30
Total Work Load			254
Total Work Load / 25 (h)			10.16
ECTS Credit of the Course			10

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