COURSE UNIT TITLE

: FINANCIAL ECONOMETRIC APPLICATIONS

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
FIB 5104 FINANCIAL ECONOMETRIC APPLICATIONS ELECTIVE 3 0 0 5

Offered By

Financial Economics and Banking

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

PROFESSOR DOCTOR HAKAN KAHYAOĞLU

Offered to

Financial Economics and Banking

Course Objective

The aim of this course is to teach student the theoretical structure of the basic econometric methods and techniques who plan to research in finance and financial econometrics and Macroeconomics.

Learning Outcomes of the Course Unit

1   To be able to understand the structure and properties of high-frequency time series.
2   To be able to learn the basic information for the prediction of the volatility parameters.
3   To be able to interpret the obtained results.
4   To be able to create prediction methods in terms of the economics and finance theory.
5   To be able to learn how to follow developments in literature and how to use relevant software packages.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Programs for the analysis of the volatility and Class-utilized software: Eviews 7.2, Oxmetrics, Stata 12.
2 High-frequency time series and characteristics of financial time series. Price movements in the financial markets.
3 Financial Econometrics: Volatility Modeling Introduction, Univariate Time Series and Forecasting (Basic Concepts, moving averages approach, Distributed Lag Models).
4 Financial and Statistical Distributions, ARMA Modeling Process, Box-Jenkins Approach, ARMA structure. Correctional Exponential Models and Application
5 Volatility Prediction Approaches (different approaches to estimate the volatility of prices of financial instruments, Delayed volatility models: GARCH
6 Volatility Measurement approaches: EGARCH, GJR, APARCH, IGARCH, Risk Metrics, FIGARCH, FIEGARCH, FIAPARCH, HYGARCH.
7 Volatility Measurement approaches: EGARCH, GJR, APARCH, IGARCH, Risk Metrics, FIGARCH, FIEGARCH, FIAPARCH, HYGARCH.
8 MIDTERM EXAM
9 Variance tests with breaks
10 Nonlinearity in time series and New Approaches: Threshold and Transition artificial neural network approaches(non-linear time series tools for testing).
11 Markov Regime Switching Model
12 Modeling Approaches according to time variable parameter.
13 Applications for Nonlinear Time Series: Threshold and Transition prediction methods and artificial network
14 Applications for Nonlinear Time Series, Chaotic Time Series and Chaos Applications.
15 Applications using R

Recomended or Required Reading

Main Reference:
Tsay, Ruey, Analysis Of Financial Time Series, John Wiley & Sons, 2010.
Brooks, Chris, Introductory Econometrics for Finance, Cambridge, 2008.
Econometric Programmes:
Eviews 7.2, Oxmetrics, Stata, R
Books:
Alexander, Carol. (2008) Market Risk Analysis, Volume I: Quantitative Methods in Finance. Wiley
Alexander, Carol. (2008) Market Risk Analysis, Volume II: Practical Financial Econometrics. Wiley
Alexander, Carol. (2008) Market Risk Analysis, Volume III: Pricing, Hedging and Trading Financial Instruments. Wiley
Alexander, Carol. (2008) Market Risk Analysis, Volume IV: Value at Risk Models. Wiley
Alexander, Carol and E. Sheedy Eds. (2008) The Professional Risk Manager s Guide to Finance Theory and Application. (McGraw-Hill)
Alexander, Carol. and E. Sheedy Eds. (2008) The Professional Risk Manager s Guide to Financial Markets. (McGraw-Hill)

Planned Learning Activities and Teaching Methods

Course content is mainly prepared financial econometrics for this program. Method of course aims to generate theoretical infrastructure in order to provide making applications and using relevant literature in financial economics or finance. Therefore, the course will be based on applications by using different types of econometric programmes.

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 * 0.20 + STT * 0.30 + FIN* 0.50
5 RST RESIT
6 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.20 + STT * 0.30 + RST* 0.50


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)

hakan.kahyaoglu@deu.edu.tr

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 14 1 14
Preparation for midterm exam 1 15 15
Preparation for final exam 1 20 20
Preparing homework 1 25 25
Reading 1 15 15
Final 1 3 3
Midterm 1 3 3
TOTAL WORKLOAD (hours) 137

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9
LO.111111
LO.21111
LO.3111111
LO.411111
LO.5111

CONTACT INFORMATION
Dokuz Eylül Üniversitesi Cumhuriyet Bulvarı No: 144 35210 Alsancak / İZMİR
Phone: +90(232) 412 12 12 - Fax: +90 (232) 464 81 35

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