Language of Instruction
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English
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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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BA Program in Economics
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Mode of Delivery
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Face to Face
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Type of Course Unit
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Elective
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Objectives of the Course
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Course description This course will introduce students to some widely-used models used to study and forecast financial markets and familiarize them with the properties of financial data. The models to be covered include autoregressive and ARMA models, GARCH models for volatility forecasting, Value- at-Risk models, and models using high frequency (intra-day) asset prices
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Course Content
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Assumed/required prior knowledge Students will be expected to learn and apply the statistical software package EVIEWS to implement the models covered in class on real data. Previous knowledge of EVIEWS is not required.
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Course Methods and Techniques
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Prerequisites and co-requisities
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None
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Course Coordinator
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None
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Name of Lecturers
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Prof.Dr. Muhittin Kaplan
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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
Resources
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Bodie, Z., A. Kane and A.J. Marcus, 2010, Investments, 9th Ed., McGraw-Hill, USA Brooks, C., 2008, Introductory Econometrics for Finance, 2nd Ed., Cambridge University Press, Cambridge. Campbell, J. Y., A.W. Lo, and A.C. MacKinlay, 1997, fhe Econometrics of Financial Mar- kets, Princeton University Press, Princeton, New Jersey.
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John E. Hanke Dean Wichern (2014), Business Forecasting, Pearson Education Limited. Sypros Makridakis, Steven C. Wheelwright and Rob J. Hyndman (1998) Forecasting: Methods and Applications, John Wiley and Sons, Inc. Walter Enders (2015), Applied Econometrics Time Series, Wiley, USA. I. Gusti Ngurah Agung, (2019) Advanced time series data analysis: Forecasting using EViews, John Wiley & Sons.
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Course Category
Mathematics and Basic Sciences
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Engineering
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Engineering Design
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Social Sciences
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Education
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Science
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Health
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