• HOME
• ABOUT US
  • Name Address
  • General Description
  • Governance
  • Academic Calendar
  • Degree Programmes
  • List of Programmes in English
  • General Admission and Registration Procedures
  • Credit Mobility and Recognition of Prior Learning
  • ECTS Credit Allocation
  • Academic Guidance
  • Contacts
• Degree Programmes
  • Third Cycle Programmes (Doctorate Degree)
  • Second Cycle Programmes (Master's Degree)
  • First Cycle Programmes (Bachelor's Degree)
  • Short Cycle Programmes (Associate's Degree)
• GENERAL INFORMATION FOR STUDENTS
  • Cost of Living
  • Accommodation
  • Meals
  • Medical Facilities
  • Facilities for Disabled Students
  • Insurance
  • Financial Supports
  • Student Affairs Office
  • Practical Information for International Students
  • Language Courses
  • Work Placement Possibilities
  • Sports, Social and Cultural Facilities
  • Student Associations and Clubs
  • About İzmir - Turkey
• INTERNATIONAL RELATIONS
  • International Relations Office
  • Registration Procedures
  • Agreements
  • Coordinators
  • Documents
  • List of Programmes in English
  • ECTS / DS Labels

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS IKT 6617 APPLIED NONLINEAR TIME SERIES ELECTIVE 3 0 0 6

Offered By

Economics

Level of Course Unit

Third Cycle Programmes (Doctorate Degree)

Course Coordinator

PROFESSOR DOCTOR HAKAN KAHYAOĞLU

Offered to

Economics

Course Objective

Dersin amacı, doğrusal olmayan ekonometrik yaklaşımları özellikle, değişen varyans, leptokurtik, asimetrik yapılar üzerinden analiz etmektir.

Learning Outcomes of the Course Unit

1   To be able to use the technics for estimating time varying parametries in high time series 2   To be able to apply nonlinear technics for Financial, commadity and ve energy markets 3   To be able to learn software 4   To be able to analyze financial volatility and to use financial modelling to be able to simulate and inference statistics in stochastic data 5   To be able to model advance financial modelling and to understand econometric approaches

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 Structural break in time series (1) 2 Structural break in time series (2) 3 Wavelets tests 4 Düşük ve Yüksek frankasa sahip zaman serilerinde uygulamalar (1) 5 Düşük ve Yüksek frankasa sahip zaman serilerinde uygulamalar (2) 6 Treshold Autoregresive (TAR) Approachs 7 Treshold Cointegration (VAR/Cointegration) (1) 8 Treshold Cointegration (VAR/Cointegration) (2) (Midterm exam will also be held this week after course hour) 9 Smooth Transition autoregresive Approaches (STAR) 10 Mixture Models (1) 11 Mixture Models (2) 12 Univariate and Multivariate Markov Switching 13 Chaos teorem and Analyze 14 Probility Distrubitions in Finance

Recomended or Required Reading

Fan, J. ve Yao, Q. Nonlinear Time Series: Nonparametric and Parametric Methods, Springer, New York, 2003. Franses, P.H. ve van Dijk, D. Nonlinear Time Series Models in Empirical Finance, Cambridge University Press, New York, 2003. Granger, C.W.J. ve Terasvirta, T. 1993. Modelling Nonlinear Economic Relationships, Oxford University Press, Oxford, 1993. Tong, H. Non-Linear Time Series: A Dynamical Systems Approach, Oxford University Press, Oxford, 1990.

Planned Learning Activities and Teaching Methods

Face-to-face

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 *** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

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 14 3 42 Reading 2 15 30 Preparation for midterm exam 1 20 20 Preparation for final exam 1 20 20 Midterm 1 3 3 Final 1 3 3 TOTAL WORKLOAD (hours) 160

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