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FIRST CYCLE - BACHELOR'S DEGREE
SCHOOL OF APPLIED SCIENCES
CAPITAL MARKET DEPARTMENT
424 CAPITAL MARKET (Evening Classes)
Course Information
Course Learning Outcomes
Course's Contribution To Program
ECTS Workload
Course Details
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COURSE INFORMATION
Course Code
Course Title
L+P Hour
Semester
ECTS
SER 152
-MODELLING IN FINANCIAL MARKETS
3 + 0
7th Semester
4
COURSE DESCRIPTION
Course Level
Bachelor's Degree
Course Type
Elective
Course Objective
-The main aim of this lesson is to help students develop and evaluate time series, classic linear, semi logarithmic and logarithmic regression models.
Course Content
-Micro Economic Models, Macro Economic Models, Time Series Patterns; Time Series Analysis and Models, The identification of trend, examples, Time Series Models, Static equation, dynamic equation, unit root, moving average MA equation, autoregressive AR equation, ARMA Autoregressive moving average, Autoregressive integrated moving average ARIMA , Data creation process; Static and Dynamic Stochastic Processes; Random walk process, Autoregressive processes AR (q), Moving average process MA (q);Autoregressive moving average ARMA (pq), Dynamic process model ARIMA (pdq) and the examples will be discussed as the main topics during the semester.
Prerequisites
No the prerequisite of lesson.
Corequisite
No the corequisite of lesson.
Mode of Delivery
Face to Face
COURSE LEARNING OUTCOMES
1
Interprets the estimation techniques
2
Synthesises the time series analysis techniques related
3
Distinguishes the time series analysis of issues relating
COURSE'S CONTRIBUTION TO PROGRAM
PO 01
PO 02
PO 03
PO 04
PO 05
PO 06
PO 07
PO 08
PO 09
PO 10
LO 001
5
5
LO 002
5
5
LO 003
5
5
Sub Total
15
15
Contribution
0
0
0
0
5
0
5
0
0
0
ECTS ALLOCATED BASED ON STUDENT WORKLOAD BY THE COURSE DESCRIPTION
Activities
Quantity
Duration (Hour)
Total Work Load (Hour)
Course Duration (14 weeks/theoric+practical)
14
3
42
Hours for off-the-classroom study (Pre-study, practice)
14
4
56
Mid-terms
1
2
2
Final examination
1
4
4
Total Work Load
ECTS Credit of the Course
104
4
COURSE DETAILS
Select Year
All Years
2023-2024 Fall
2022-2023 Fall
2021-2022 Fall
2020-2021 Fall
2019-2020 Fall
2018-2019 Fall
2017-2018 Fall
Course Term
No
Instructors
Details
2023-2024 Fall
1
SERKAN DURMAZ
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Course Details
Course Code
Course Title
L+P Hour
Course Code
Language Of Instruction
Course Semester
SER 152
-MODELLING IN FINANCIAL MARKETS
3 + 0
1
Turkish
2023-2024 Fall
Course Coordinator
E-Mail
Phone Number
Course Location
Attendance
Lecturer SERKAN DURMAZ
serkand@pau.edu.tr
Course location is not specified.
%70
Goals
-The main aim of this lesson is to help students develop and evaluate time series, classic linear, semi logarithmic and logarithmic regression models.
Content
-Micro Economic Models, Macro Economic Models, Time Series Patterns; Time Series Analysis and Models, The identification of trend, examples, Time Series Models, Static equation, dynamic equation, unit root, moving average MA equation, autoregressive AR equation, ARMA Autoregressive moving average, Autoregressive integrated moving average ARIMA , Data creation process; Static and Dynamic Stochastic Processes; Random walk process, Autoregressive processes AR (q), Moving average process MA (q);Autoregressive moving average ARMA (pq), Dynamic process model ARIMA (pdq) and the examples will be discussed as the main topics during the semester.
Topics
Weeks
Topics
1
Introduction to model Index
2
The capital asset pricing model
3
Arbitrage pricing model
4
Time Series Models
5
The Unit Root testing
6
Moving Average MA equation
7
Autoregressive AR Equation
8
ARMA Autoregressive Moving Average Equation
9
Exam week
10
Random walk process
11
Time Series Patterns
12
Microeconomic Models
13
Macroeconomic Models
14
ADF test
Materials
Materials are not specified.
Resources
Course Assessment
Assesment Methods
Percentage (%)
Assesment Methods Title
Final Exam
60
Final Exam
Midterm Exam
40
Midterm Exam
L+P:
Lecture and Practice
PQ:
Program Learning Outcomes
LO:
Course Learning Outcomes
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Home Page
About University
Name And Address
Acedemic Authorities
General Discription
Academic Calendar
General Admission Requirements
Recognition of Prior Learning
General Registration Procedures
ECTS Credit Allocation
Academic Guidance
Information For Students
Cost Of Living
Accommodation
Meals
Medical Facilities
Facilities for Special Needs Students
Insurance
Financial Support for Students
Student Affairs
Learning Facilities
International Programs
Language Courses
Internships
Sports Facilities and Leisure Activities
Student Associations
Practical Information for Mobile Students
Degree Programmes