COURSE UNIT TITLE

: FINANCIAL TIME SERIES ANALYSIS

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
IST 4141 FINANCIAL TIME SERIES ANALYSIS ELECTIVE 3 0 0 5

Offered By

Statistics

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

PROFESSOR DOCTOR ESIN FIRUZAN

Offered to

Statistics
Statistics(Evening)

Course Objective

The course objective is to provide the student to be able to make forecasts and to model financial time series data by introducing basic characteristics of financial data and financial econometric models.

Learning Outcomes of the Course Unit

1   Time series data, return calculation, financial terms
2   Random Walk Process, White Noise Process, Stationary, Time-invariant properties, Wiener Process
3   To detect Unit Root and Unit Root Tests
4   To detect the structural break and Structural Break Tests
5   Causality Analysis
6   Cointegration Analysis
7   Trend Analysis
8   Moving Average Methods
9   ARIMA Models
10   ARCH/GARCH Models

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Introduction to financial variables (interest rate, asset return etc.)
2 Economic variables (supply, demand, unemployment etc.)
3 Econometric models
4 Time series components
5 Modelling deterministic trend
6 Modelling stochastic trend
7 Removing trend
8 Midterm exam
9 Unit roots and regression residuals
10 Dickey-Fuller test
11 Augmented Dickey-Fuller Test
12 Detection structural break
13 Unit root tests in presence of structural break
14 Weakness and strengths of unit root tests in presence of structural break

Recomended or Required Reading

Textbook(s): Enders W., (2004) Applied Econometric Time Series, Wiley Series
Supplementary Book(s):
1. Maddala G. S., (1992) Introduction to Econometrics, MacMillan

Planned Learning Activities and Teaching Methods

Lecture format, built around the textbook readings and computer applications with numerous examples chosen to illustrate theoretical concepts. Lots of drill with emphasis on practice. Questions are encouraged and discussion of material stressed.

Lecture, project and presentation.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 ASG ASSIGNMENT
3 FIN FINAL EXAM
4 FCG FINAL COURSE GRADE MTE * 0.30 + ASG * 0.30 + FIN * 0.40
5 RST RESIT
6 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.30 + ASG * 0.30 + RST * 0.40


Further Notes About Assessment Methods

None

Assessment Criteria

Evaluation of project, presentation and exams

Language of Instruction

Turkish

Course Policies and Rules

Student responsibilities:
Attendance to at least 70% for the lectures is an essential requirement of this course and is the responsibility of the student. It is necessary that attendance to the lecture and homework delivery must be on time. Any unethical behavior that occurs either in presentations or in exams will be dealt with as outlined in school policy. You can find the undergraduate policy at http://web.deu.edu.tr/fen

Contact Details for the Lecturer(s)

DEU Fen Fakültesi Istatistik Bölümü
e-mail: esin.firuzan@deu.edu.tr
Tel: 0232 301 85 61

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 13 3 39
Preparations before/after weekly lectures 12 1 12
Preparation for midterm exam 1 21 21
Preparation for final exam 1 28 28
Preparing assignments 1 12 12
Final 1 2 2
Midterm 1 2 2
TOTAL WORKLOAD (hours) 116

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11PO.12PO.13PO.14
LO.155453
LO.2555
LO.355453
LO.4553
LO.55553
LO.6
LO.7
LO.8
LO.9
LO.10