COURSE UNIT TITLE

: FINANCIAL DATA ANALYSIS

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
IBS 4351 FINANCIAL DATA ANALYSIS ELECTIVE 3 0 0 4

Offered By

International Business and Trade

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

ASISTANT PROFESSOR ERDOST TORUN

Offered to

International Business and Trade
BUSINESS ADMINISTRATION

Course Objective

This course focuses on the financial time series models empirically. Statistical and econometrical features of aforementioned models, their estimation processes, and interpretation of model results will be discussed at introductory level in the course.

Learning Outcomes of the Course Unit

1   Use quantitative methods for analyzing high frequency financial data.
2   Understand basic properties of fundamental statistical and econometric models
3   Use basic financial data analysis software to estimate models and interpret the estimation results.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

ECN 1904 - PRINCIPLES OF MACROECONOMICS

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Financial Time Series and Their Features
2 Basic Statistics
3 Linear Relationship in Time Series analysis Classical Linear Regression Model (CLRM)
4 Linear Time Series Analysis CLRM Assumptions
5 Linear Time Series Analysis CLRM Assumptions
6 Univariate Time Series Modelling
7 Multivariate Models
8 Multivariate Models
9 Modelling Long Run Relationships in Finance
10 Modelling Long Run Relationships in Finance
11 Modelling Volatility
12 Modelling Volatility

Recomended or Required Reading

1. Analysis of Financial Data, Gary Koop, Wiley Publishing.

Planned Learning Activities and Teaching Methods

1. Lectures
2. Problem session
3. Computer program application sessions.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MT Midterm
2 FN Final
3 FCG FINAL COURSE GRADE MT * 0.40 + FN * 0.60
4 RST RESIT
5 FCGR FINAL COURSE GRADE (RESIT) MT * 0.40 + RST * 0.60

Further Notes About Assessment Methods

None

Assessment Criteria

1. The learner will show understanding the basic statistical and properties of fundamental financial data analysis models.
2. The learner will model financial data through computer programs and interpret the results.

Language of Instruction

English

Course Policies and Rules

1. Plagiarism of any type will result in disciplinary action.
2. Attending at least 70 percent of lectures is mandatory.

Contact Details for the Lecturer(s)

erdost.torun@deu.edu.tr

Office Hours

Wednesday, 12:00 - 13:00

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 12 3 36
Tutorials 0 0 0
Preparation for midterm exam 1 5 5
Preparations before/after weekly lectures 12 3 36
Preparation for final exam 1 10 10
Final 1 1,5 2
Midterm 1 1,5 2
Quiz etc. 0 0 0
TOTAL WORKLOAD (hours) 91

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11PO.12PO.13PO.14PO.15
LO.1444334434
LO.2442244444
LO.3422333