| Course Unit Code | Course Unit Title | Type of Course Unit | Year of Study | Semester | Number of ECTS Credits | | İSL539 | FINANCIAL TIME SERIES ANALYSIS | Compulsory | 1 | 1 | 5 |
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| Level of Course Unit |
| Second Cycle |
| Objectives of the Course |
| Giving theoretical and applied advanced econometrics and time series analysis, which are required to be used in other courses in the program, thesis writing and academic studies. |
| Name of Lecturer(s) |
| Doç.Dr.Gönül YÜCE AKINCI |
| Learning Outcomes |
| 1 | Covering regression models, predictions, and problems in regression | | 2 | Review and understanding of econometric models | | 3 | Teaching basic financial time series models | | 4 | Processing forecasts, estimators and their properties in econometrics | | 5 | Comprehensive coverage of ARCH and GARCH models | | 6 | Giving the necessary theoretical and applied time series analysis information for thesis writing |
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| Mode of Delivery |
| Formal Education |
| Prerequisites and co-requisities |
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| Recommended Optional Programme Components |
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| Course Contents |
| Linear time series models and their applications. Volatility modeling with heteroskedastic models; Nonlinear models, neural networks and their applications; High frequency data analysis, market microstructure; continuous diffusion models and Ito Lemma; VaR, stress testing, extreme value analysis and multivariate models, factor models and applications; multivariate relative heteroskedastic models; Markov chain, Monte Carlo methods. |
| Weekly Detailed Course Contents |
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| 1 | Basic Concepts, Chart Tools, and Time Series Examples | | | | 2 | Regression, Trend and Seasonality | | | | 3 | Model Evaluation Criteria and Selection of the Appropriate Model | | | | 4 | Stationary Models | | | | 5 | Moving Average and Self Dependent Processes | | | | 6 | Spectral Theory and Filtering | | | | 7 | Non-Stationary Models | | | | 8 | Midterm | | | | 9 | Unit Root and Unlimited Time Series | | | | 10 | Seasonal Patterns | | | | 11 | Multivariate Time Series | | | | 12 | Multivariate Time Series | | | | 13 | Multivariate Time Series | | | | 14 | Transfer Function Models | | | | 15 | Nonlinear Models | | | | 16 | final examination | | |
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| Recommended or Required Reading |
| Applied Time Series Modelling and Forecasting, John Wiley & Sons, England Brockwell, P.J. & Davis, R.A. (2002). Introduction to Time Series and Forecasting, 2nd edition, Springer, USA. Kendall, M.G. & Ord, J.K. (1990). Time Series, 3rd edition, Hodder Education. |
| Planned Learning Activities and Teaching Methods |
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| Assessment Methods and Criteria | |
| SUM | 0 | |
| SUM | 0 | | Yarıyıl (Yıl) İçi Etkinlikleri | 40 | | Yarıyıl (Yıl) Sonu Etkinlikleri | 60 | | SUM | 100 |
| | Language of Instruction | | Turkish | | Work Placement(s) | |
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| Workload Calculation |
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| Midterm Examination | 1 | 1 | 1 |
| Final Examination | 1 | 1 | 1 |
| Attending Lectures | 14 | 3 | 42 |
| Writing Paper | 1 | 30 | 30 |
| Individual Study for Mid term Examination | 2 | 20 | 40 |
| Individual Study for Final Examination | 1 | 22 | 22 |
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| Contribution of Learning Outcomes to Programme Outcomes |
| LO1 | 5 | 4 | 5 | 4 | 4 | 4 | | LO2 | 5 | 4 | 4 | 4 | 4 | 4 | | LO3 | 5 | 4 | 5 | 4 | 4 | 5 | | LO4 | 5 | 4 | 5 | 4 | 4 | 5 | | LO5 | 5 | 4 | 5 | 4 | 4 | 5 | | LO6 | 5 | 4 | 4 | 5 | 4 | 5 |
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| * Contribution Level : 1 Very low 2 Low 3 Medium 4 High 5 Very High |
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Ordu University Rectorate Building ,Cumhuriyet Campus , Center / ORDU / TURKEY • Tel: +90 452 226 52 00
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