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Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS VYA 5024 TIME SERIES AND FORECASTING TECHNIQUES ELECTIVE 3 0 0 4

Offered By

DATA MANAGEMENT AND ANALYSIS

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

ASSOCIATE PROFESSOR EMRAH GÜLAY

Offered to

DATA MANAGEMENT AND ANALYSIS

Course Objective

Calculations on time series data and the use of forecasting methods based on such data are aimed.

Learning Outcomes of the Course Unit

1   1. To be able to understand the visual analysis of time series data 2   2. To be able to classify and organize these data 3   3. To be able to use the calculation methods adopted on these data 4   4. To be able to summarize these data correctly 5   5. To be able to use forecasting methods based on time series data correctly

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 Definition and classification of data types 2 Graphic representation of financial data 3 Interest Calculations 4 Installment Calculations 5 Rent Calculations 6 Stock Calculations 7 Moving average method 8 Applications 9 Multistages moving averages 10 Exponential correction method 11 Multi-stages exponential correction 12 Stochastic correction and Holt Winter s 13 Options and arbitrage accounts 14 Applications

Recomended or Required Reading

1. Statistics and Data Analysis for Financial Engineering (Springer Texts in Statistics) David Ruppert, 2010. 2. Analysis of Financial Data by Gary Koop ISBN 978-0-470-01321-2 November 2005, ©2006 Paperback.

Planned Learning Activities and Teaching Methods

1- Lecture Method, 2- Demonstration Method with Applications, 3-Determined Cases Discussed Analysis Method

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA 1 MTE MIDTERM EXAM 2 STT TERM WORK (SEMESTER) 3 FIN FINAL EXAM 4 FCG FINAL COURSE GRADE MTE * 0.30 + STT * 0.30 + FIN* 0.40 5 RST RESIT 6 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.30 + STT * 0.30 + RST* 0.40 *** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

The weighted average of the midterm grade, the midterm work and the final grade must be 75 and above.

Language of Instruction

Turkish

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

To be announced.

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours) Lectures 14 3 42 Preparations before/after weekly lectures 10 2 20 Preparation for midterm exam 1 10 10 Preparation for final exam 1 10 10 Preparing assignments 5 3 15 Midterm 1 3 3 Final 1 3 3 TOTAL WORKLOAD (hours) 103

Contribution of Learning Outcomes to Programme Outcomes

PO/LO PO.1 PO.2 PO.3 PO.4 PO.5 PO.6 LO.1 1 1 LO.2 1 1 1 1 1 LO.3 1 LO.4 1 1 1 1 LO.5 1 1 1 1 1 1