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Language of Instruction
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Turkish
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Level of Course Unit
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Bachelor's Degree
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Department / Program
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Management Information Systems
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Type of Program
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Formal Education
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Type of Course Unit
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Elective
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Course Delivery Method
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Face To Face
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Objectives of the Course
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The aim of this course is to provide students with practical skills to teach and apply analytical and statistical methods to predict future values using historical data. In this way, students will have the ability to predict future trends and events more accurately.
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Course Content
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The content of this course consists of new techniques developed for the modeling and analysis of economic time series, which continue to develop rapidly in recent years. The concept of stationarity in time series, unit root tests, unit root tests with structural breaks, co-integration analysis and error correction model are explained and applied studies are carried out using econometric package programs.
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Course Methods and Techniques
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The topics covered in the course are complemented by computer applications. In addition, students are informed about how the techniques taught are put into practice by examining various articles on the theoretical topics examined.
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Prerequisites and co-requisities
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None
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Course Coordinator
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Asist Prof. Halime Suvay Eker
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Name of Lecturers
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Asist Prof. MERVE ESRA GÜLCEMAL
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Assistants
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None
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Work Placement(s)
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No
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Recommended or Required Reading
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Resources
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Tsay, R.S., Analysis of Financial Time Series, John Wiley, 2010. Enders, W., Applied Econometric Time Series, John Wiley, 2004. Patterson, K., Introduction to Econometrics, A Time series Approach, 2001. Franses, P.H., ve Dick van Dijk, Non-linear Time Series Models in Empirical Finance, Cambridge Univ. Press, 2000. Franses, P.H., Time Series Models for Business and Economic Forecasting, Camb.Uni.Press, 1998. Hamilton, J., Time Series Analysis, Princeton Uni. Press, 2020.
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Course Notes
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Lecture notes
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Course Category
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Social Sciences
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%20
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Field
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%80
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