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Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS EMT 4021 FINANCIAL TIME SERIES ELECTIVE 3 0 0 5

Offered By

Econometrics

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

ASSOCIATE PROFESSOR EMRAH GÜLAY

Offered to

Econometrics Econometrics (Evening)

Course Objective

This course covers methodologies pertaining to financial time series, with an emphasis on model building, accurate prediction and evaluation. Completion of this course will equip students with insights and modeling tools to analyze real world financial and business time dependent data.

Learning Outcomes of the Course Unit

1   To able to approach and analyze financial time series, including high frequency data, 2   To able to differentiate between various time series models, 3   To able to forecast future observations of the time series, 4   To be able to explain concepts of ARCH and GARCH models, 5   To be able to introduce different types of ARCH/GARCH models, 6   To be able to explain concepts of Causality and Cointegration, 7   To able to gain knowledge of using R program.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 Introduction to time series, and the characteristics of financial time series 2 The concepts of stationary and unit root tests 3 ARIMA Models 4 Seasonal ARIMA Models and Regression with ARMA errors 5 ARCH model and its features 6 GARCH model and its features 7 Midterm 8 Midterm 9 Vector Autoregressive Models (VAR) 10 Granger causality test 11 Vector Error Correction Model 12 Cointegrated VAR model 13 ARDL approach to cointegration 14 Real world applications by using R program

Recomended or Required Reading

Analysis of Financial Time Series, by Ruey S. Tsay (John Wiley, 2010), 3rd Edition. Forecasting: Principles and Practice, by Rob J Hyndman and George Athanasopoulos

Planned Learning Activities and Teaching Methods

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA 1 MTE MIDTERM EXAM 2 MTEG MIDTERM GRADE MTEG * 1 3 FIN FINAL EXAM 4 FCGR FINAL COURSE GRADE MTEG * 0.40 + FIN * 0.60 5 RST RESIT 6 FCGR FINAL COURSE GRADE (RESIT) MTEG * 0.40 + RST * 0.60

Further Notes About Assessment Methods

None

Assessment Criteria

To be announced.

Language of Instruction

Turkish

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

Associate Prof. Dr. Emrah Gulay, emrah.gulay@deu.edu.tr Assistant Prof. Dr. Mehmet Ozan Ozdemir, ozan.ozdemir@deu.edu.tr

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours) Lectures 12 3 36 Preparations before/after weekly lectures 12 1 12 Preparation for midterm exam 1 20 20 Preparation for final exam 1 25 25 Independant Study 1 20 20 Final 1 1 1 Midterm 1 1 1 TOTAL WORKLOAD (hours) 115

Contribution of Learning Outcomes to Programme Outcomes

PO/LO PO.1 PO.2 PO.3 PO.4 PO.5 PO.6 PO.7 PO.8 PO.9 PO.10 LO.1 1 LO.2 1 LO.3 1 LO.4 1 LO.5 1 LO.6 1 LO.7 1