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Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS EKO 6105 FINANCIAL ECONOMETRICS ELECTIVE 3 0 0 7

Offered By

Econometrics

Level of Course Unit

Third Cycle Programmes (Doctorate Degree)

Course Coordinator

ASSOCIATE PROFESSOR EMRAH GÜLAY

Offered to

Econometrics

Course Objective

The main objective of the course is to tell how to study applied financial econometrics workout by synthesizing all subjects which has been learnt in the class

Learning Outcomes of the Course Unit

1   To be able to explain main concepts used in financial econometrics 2   To be able to explain concept of volatility 3   To be able to explain concepts of ARCH and GARCH model 4   To be able to introduce different types of ARCH/GARCH models 5   To be able to use financial data in family of iARCH/GARCH implementation 6   To be able to explain how to apply multivariate time series methods to financial data

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 Characteristics of volatility, structure of model 2 ARCH model and its features 3 GARCH model and its features 4 Integrated GARCH model(IGARCH), GARCH-M model, Exponential GARCH model(EGARCH) 5 Long memory stochastic models, estimation of exponential-weighted 6 Some of GARCH models with multivariate variable, GARCH models for dual returns 7 High frequency GARCH models 8 The applications of using R 9 Midterm 10 Weak stationary, cross-correlation matrices 11 Vector Autoregressive Models(VAR) 12 Granger Causality Test 13 Error Correction form 14 Cointegrated VAR model 15 ARDL approach to cointegration

Recomended or Required Reading

Brooks, Chris, Econometrics for Finance, Cambridge, 2008. Verbeek, Marno, Modern Econometrics, wiley, 2008. Hill, R.Carter, William E.Griffiths, Guay .C.Lim, Principles of Econometrics, Wiley, 2008.

Planned Learning Activities and Teaching Methods

This course will be presented using softwares to set up econometrics models, Windows, Word, Excel

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

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)

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 13 5 65 Preparation for midterm exam 1 27 27 Preparation for final exam 1 30 30 Reading 1 10 10 Midterm 1 3 3 Final 1 3 3 TOTAL WORKLOAD (hours) 180

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