TR
11111

COURSE INTRODUCTION AND APPLICATION INFORMATION

itf.ieu.edu.tr

Course Name
Code
Semester
Theory
(hour/week)
Application/Lab
(hour/week)
Local Credits
ECTS
Fall/Spring
Prerequisites
None
Course Language
Course Type
Elective
Course Level
-
Mode of Delivery -
Teaching Methods and Techniques of the Course
Course Coordinator
Course Lecturer(s) -
Assistant(s) -
Course Objectives
Learning Outcomes The students who succeeded in this course;
  • will be able to define classical linear regression model with the significance and hypothesis testing.
  • will be able to analyze classical linear regression model in advance level and multiple regression models in econometric software.
  • will be able to determine the difference between assumptions of classical linear regression model and Durbin Watson and Godfrey autocorrelation tests.
  • will be able to identify the univariate time series modelling, the approriate time series models for a given data series and the characteristics of various types of stochastic process
  • will be able to describe multivariate models with Granger causality tests and VARs in econometric software in order to explain relative advantages and disadvantages of them.
  • will be able to estimate forecasts from GARCH models and ARCH effects in time series data.
  • will be able to explain the difference between pure simulation, bootstrapping and Monte Carlo simulation which are main simulation methods.
  • will be able to explain the basic features of financial data and econometrics by distinguishing different types of data and creating an econometric model to calculate the return on assets.
Course Description

 



Course Category

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

 

WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

Week Subjects Required Materials
1 Introduction
2 Stylized facts regarding financial data and econometricsa) Distinguish between different types of data b) Describe the steps involved in building an econometric model c) Calculate asset price returns and accomplish simple tasks in econometric software Chris Brooks, “Introductory Econometrics for Finance”, 2. Basım, Second Edition., 126
3 Klasik doğrusal regresyon modelia) Parametrelerin ve standart hatalarının tahminini yapabilmek için EKKY formülünün türetilmesib) Anlamlılık testi ve güven aralığı yaklaşımları ile hipotez testleric) Ekonometri paketlerinde regresyon modellerinin tahmini ve tek hipotezi testi. Chris Brooks, “Introductory Econometrics for Finance”, 2. Basım, Second Edition, 2781.
4 Overview of the classical linear regression model a) Derive OLS formulae for estimating parameters and their standard errors. b) Test hypothesis using the test of significance and confidence interval approaches c) Estimate regression models and test single hypotheses in econometric software. Chris Brooks, “Introductory Econometrics for Finance”, 2. Basım, Second Edition, 2781.
5 Further development and analysis of the classical linear regression model.a) Construct models with more than one explanatory variable b) Test multiple hypotheses using an Ftest and determine how well a model fits the datac) Estimate multiple regression models and test multiple hypotheses in econometric software. Chris Brooks, “Introductory Econometrics for Finance”, 2. Basım, Second Edition, 88128.
6 Classical linear regression model assumptions and diagnostic tests a) Describe the steps involved in testing regression residuals for heteroscedasticity and autocorrelation b) Distinguish between the DurbinWatson and Breusch—Godfrey tests for autocorrelation c) Determine whether the residual distribution from a regression differs significantly from normality and investigate whether the model parameters are stable Chris Brooks, “Introductory Econometrics for Finance”, 2. Basım, Second Edition, 129205.
7 Univariate time series modelling and forecasting a) Explain the defining characteristics of various types of stochastic processes b) Identify the appropriate time series model for a given data series and produce forecasts for ARMA and exponential smoothing models c)Evaluate the accuracy of predictions using various metrics and estimate time series models and produce forecasts from them in econometric software Chris Brooks, “Introductory Econometrics for Finance”, 2. Basım, Second Edition, 206264.
8 Univariate time series modelling and forecasting a) Explain the defining characteristics of various types of stochastic processes b) Identify the appropriate time series model for a given data series and produce forecasts for ARMA and exponential smoothing models c)Evaluate the accuracy of predictions using various metrics and estimate time series models and produce forecasts from them in econometric software Chris Brooks, “Introductory Econometrics for Finance”, 2. Basım, Second Edition, 206264.
9 Article Presentation
10 Project topic selection
11 Multivariate modelsa) Describe several methods for estimating simultaneous equations models and explain the relative advantages and disadvantages of VAR modelingb) Estimate optimal lag lengths, impulse responses and variance decompositions c) Conduct Granger causality tests and construct simultaneous equations models and VARs in econometric software Chris Brooks, “Introductory Econometrics for Finance”, 2. Basım, Second Edition, 265317.
12 Modelling volatility and correlationa) Discuss the features of data that motivate the use of GARCH models and explain how conditional volatility models are estimatedb) Test for ‘ARCHeffects’ in time series datac) Produce forecasts from GARCH models d) Estimate univariate and multivariate GARCH models in econometric software using maximum likelihood Chris Brooks, “Introductory Econometrics for Finance”, 2. Basım, Second Edition, 379450.
13 Modelling volatility and correlationa) Discuss the features of data that motivate the use of GARCH models and explain how conditional volatility models are estimatedb) Test for ‘ARCHeffects’ in time series datac) Produce forecasts from GARCH models d) Estimate univariate and multivariate GARCH models in econometric software using maximum likelihood Chris Brooks, “Introductory Econometrics for Finance”, 2. Basım, Second Edition, 379450.
14 Simulation methodsa) Design simulation frameworks to solve a variety of problems in financeb) Explain the difference between pure simulation and bootstrappingc) Monte Carlo simulation d) Implement a simulation analysis in econometric software Chris Brooks, “Introductory Econometrics for Finance”, 2. Basım, Second Edition, 546584.
15 Project submission
16 Review of the Semester  
Course Notes/Textbooks Book Chapters and Powerpoint slides
Suggested Readings/Materials Journal of Financial EconometricsJournal of EconometricsJournal of Applied EconometricsEconometric ReviewsJournal of Empirical FinanceFinancial TimesWall Street Journal

 

EVALUATION SYSTEM

Semester Activities Number Weigthing
Participation
10
Laboratory / Application
Field Work
Quizzes / Studio Critiques
Portfolio
Homework / Assignments
Presentation / Jury
1
20
Project
Seminar / Workshop
Oral Exam
Midterm
Final Exam
Total

Weighting of Semester Activities on the Final Grade
100
Weighting of End-of-Semester Activities on the Final Grade
Total

ECTS / WORKLOAD TABLE

Semester Activities Number Duration (Hours) Workload
Course Hours
(Including exam week: 16 x total hours)
16
3
48
Laboratory / Application Hours
(Including exam week: 16 x total hours)
16
Study Hours Out of Class
16
3
Field Work
Quizzes / Studio Critiques
Portfolio
Homework / Assignments
Presentation / Jury
1
10
Project
39
Seminar / Workshop
Oral Exam
Midterms
Final Exams
    Total
106

 

COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

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

To become individuals having high intellectual capacity, improved social skills, positive thinking, the ability to adapt to different environments and institutions

 X
2

To have technical equipment, flexible thinking and action ability and multiple language skills to be capable of working in international platforms

 X
3

To be able to utilize the basic knowledge they obtained with an interdisciplinary approach to business, economics, etc. in creating expertise in the fields of International Trade and Finance in accordance with the requirements of the globalized business world

 X
4

To be able to monitor and analyze the dynamics of international trade and financial markets which are the two fields observed intensively in the current conjuncture of globalization

 X
5

To develop suggested solutions and recommendations by informing the people and institutions predicting regional, national and international problems in the fields of international trade and finance with a proactive approach

 X
6

To possess the ability of analytical thinking and the ability to synthesize with quantitative proficiency as required in the program

 X
7

To have the characteristics to inquire and investigate the knowledge and skills acquired during the education process in relation to the requirements of existing market conditions

 X
8

To identify and analyze the validity of theories related to the international trade and finance and their relationships regarding current conditions

 X
9

To possess the knowledge of a second foreign language to the extent of their individual abilities, besides the competency in the English language to be able to communicate effectively
10

To have the qualifications of managing and being managed to solve existing and potential problems encountered in practice
11

To be able to organize activities that will contribute to the personal and professional development of the employees in the department where he/she holds an executive position

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

 

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