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COURSE INFORMATION
Course CodeCourse TitleL+P HourSemesterECTS
ISY 642DATA ANALYSIS IN ECONOMETRICS AND STATISTICS SOFTWARE3 + 01st Semester10

COURSE DESCRIPTION
Course Level Doctorate Degree
Course Type Elective
Course Objective Some econometric and statistical softwares (SPSS, STATA, E-Views, Excel) will be introduced so that Ph.D. students will be able to conduct modelling and testing financial data.
Course Content Provisions is given concrete examples of concepts via example data sets, a data set econometric problems encountered can be overcome by what means knowledge gained
Prerequisites No the prerequisite of lesson.
Corequisite No the corequisite of lesson.
Mode of Delivery Face to Face

COURSE LEARNING OUTCOMES
1knows the statistical and econometric concepts
2knows properties of financial data
3recognize the econometric problems of financial data
4use one packet program at least
5to explain data analysis can be reached at the end of the process of finding with financial arguments

COURSE'S CONTRIBUTION TO PROGRAM
PO 01PO 02PO 03PO 04PO 05PO 06PO 07
LO 0015552533
LO 0023552533
LO 0033552533
LO 0045552533
LO 0053552533
Sub Total19252510251515
Contribution4552533

ECTS ALLOCATED BASED ON STUDENT WORKLOAD BY THE COURSE DESCRIPTION
ActivitiesQuantityDuration (Hour)Total Work Load (Hour)
Course Duration (14 weeks/theoric+practical)14342
Hours for off-the-classroom study (Pre-study, practice)14570
Assignments41560
Mid-terms12525
Final examination13030
Presentation / Seminar Preparation31133
Total Work Load

ECTS Credit of the Course






260

10
COURSE DETAILS
 Select Year   


 Course TermNoInstructors
Details 2023-2024 Fall1DÜNDAR KÖK


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Course Details
Course Code Course Title L+P Hour Course Code Language Of Instruction Course Semester
ISY 642 DATA ANALYSIS IN ECONOMETRICS AND STATISTICS SOFTWARE 3 + 0 1 Turkish 2023-2024 Fall
Course Coordinator  E-Mail  Phone Number  Course Location Attendance
Prof. Dr. DÜNDAR KÖK dkok@pau.edu.tr İİBF A0128 %80
Goals Some econometric and statistical softwares (SPSS, STATA, E-Views, Excel) will be introduced so that Ph.D. students will be able to conduct modelling and testing financial data.
Content Provisions is given concrete examples of concepts via example data sets, a data set econometric problems encountered can be overcome by what means knowledge gained
Topics
WeeksTopics
1 Risk-Return Relationship in Finance and Feature of Financial Time Series (Equal Weighted and Exponentially Weighted Moving Average Approaches)
2 Classical Linear Regression Model and Its Assumptions (Asset Pricing Models: CAPM and APT APPLICATIONS)
3 Classical Linear Regression Model and Its Assumptions (Asset Pricing Models: CAPM and APT APPLICATIONS)
4 Classical Linear Regression Model and Its Assumptions (Asset Pricing Models: CAPM and APT APPLICATIONS)
5 Time Series Models: Random Process, Autocovariance and Autocorrelation Functions, Left and Right Sided Unit Root Tests (EFFECTIVE MARKET HYPOTHESIS, DETECTION OF PRICE BALLOONS)
6 ARMA Model Construction and Forecasting Dynamics with Box-Jenkins Methodology in aman Series (SAMPLES FROM FINANCIAL MARKETS)
7 Time Series Analysis in Multiple Equation Systems (VAR Models, Action-Response Functions, Variance Decomposition, Causality, Cointegration,) (EXAMPLES FROM FINANCIAL MARKETS)
8 Midterm Exam
9 Case study
10 Case study
11 Case study
12 Case study
13 Case study
14 Case study
Materials
Materials are not specified.
Resources
ResourcesResources Language
1. Chris Brooks, Intraductory Econometrics For Finance, 2nd Edition, Cambridge Unv.Press, 2008, 2014.English
2.Walter Enders, Applied Econometric Time Series, Fourth Ed, John Wiley & Sons Inc, 2015.English
3. Philip Hans Franses and Dick Van Dijk, Non-Linear Time Series Models in Empirical Finance, Cambridge University Press, 2nd Edition, USA, 2003English
4. Evdokia Xekalaki, S. Degiannakis, ARCH Models for Financial Applications, John Wiley & Sons Ltd,2010.English
5. Roman Kozhan, Financial Econometrics with EViews, 2009, Ventus Publishing ApSEnglish
Course Assessment
Assesment MethodsPercentage (%)Assesment Methods Title
Final Exam50Final Exam
Midterm Exam50Midterm Exam
L+P: Lecture and Practice
PQ: Program Learning Outcomes
LO: Course Learning Outcomes