1. Γενικά
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ΣΧΟΛΗ |
Σχολή Οικονομικών Επιστημών |
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ΤΜΗΜΑ |
Τμήμα Οργάνωσης και Διοίκησης Επιχειρήσεων |
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ΕΠΙΠΕΔΟ ΣΠΟΥΔΩΝ |
Προπτυχιακό |
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ΚΩΔΙΚΟΣ ΜΑΘΗΜΑΤΟΣ |
BA832 |
ΕΞΑΜΗΝΟ ΣΠΟΥΔΩΝ |
8 | ||
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ΤΙΤΛΟΣ ΜΑΘΗΜΑΤΟΣ |
Financial Computing II | ||||
| ΑΥΤΟΤΕΛΕΙΣ ΔΙΔΑΚΤΙΚΕΣ ΔΡΑΣΤΗΡΙΟΤΗΤΕΣ |
ΕΒΔΟΜΑΔΙΑΙΕΣ ΩΡΕΣ
ΔΙΔΑΣΚΑΛΙΑΣ |
ΠΙΣΤΩΤΙΚΕΣ ΜΟΝΑΔΕΣ | |||
| Διαλέξεις | 3 | ||||
| Εργαστήριο / Εργ. Ασκήσεις | 0 | ||||
| Ασκήσεις (Πράξης κ.λ.π.) | 0 | ||||
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ΣΥΝΟΛΟ ΩΡΩΝ |
3 | ||||
| ΤΥΠΟΣ ΜΑΘΗΜΑΤΟΣ | Special Backround (S.B.) | ||||
| ΠΡΟΑΠΑΙΤΟΥΜΕΝΑ ΜΑΘΗΜΑΤΑ | |||||
| ΓΛΩΣΣΑ ΔΙΔΑΣΚΑΛΙΑΣ & ΕΞΕΤΑΣΕΩΝ | Greek | ||||
| IΤΟ ΜΑΘΗΜΑ ΠΡΟΣΦΕΡΕΤΑΙ ΣΕ ΦΟΙΤΗΤΕΣ ERASMUS | |||||
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ΗΛΕΚΤΡΟΝΙΚΗ ΣΕΛΙΔΑ ΜΑΘΗΜΑΤΟΣ (URL) |
https://
eclass.uowm.gr
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2. ΜΑΘΗΣΙΑΚΑ ΑΠΟΤΕΛΕΣΜΑΤΑ
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Μαθησιακά Αποτελέσματα |
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The aim of the course is to apply modern computational methods to basic knowledge of creating models for the analysis and forecasting of mainly economic time series. Upon successful completion of the course, the student will acquire knowledge and skills that will enable him/her to: • Understand the particular characteristics of an economic time series and the types of patterns it may follow. • Make forecasts using simple time series methods. • Solve problems of the above categories using computational methods (gretl , eviews etc.). • Know elements of decision making in simple problems with forecasting techniques. |
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Γενικές Ικανότητες |
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• Promoting free, creative and inductive thinking • Working in an interdisciplinary environment. • Generating new research ideas. • Autonomous work • Group work |
3. ΠΕΡΙΕΧΟΜΕΝΟ ΜΑΘΗΜΑΤΟΣ
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The basic material that students need to know for the course is contained in the following sections: • Time series • Data types and data sources • Types of data types and data sources • Methods of smoothing • Smoothing methods: double exponential smoothing, exponential smoothing with trend adjustment, Exponential smoothing with trend adjustment • Time series decomposition into individual components (trend, seasonality, cyclicality, etc.) • Model selection criteria • Programming |
4. ΔΙΔΑΚΤΙΚΕΣ και ΜΑΘΗΣΙΑΚΕΣ ΜΕΘΟΔΟΙ - ΑΞΙΟΛΟΓΗΣΗ
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ΤΡΟΠΟΣ ΠΑΡΑΔΟΣΗΣ |
Face to face | ||||||||||||||||||||||||
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ΧΡΗΣΗ ΤΕΧΝΟΛΟΓΙΩΝ ΠΛΗΡΟΦΟΡΙΑΣ ΚΑΙ ΕΠΙΚΟΙΝΩΝΙΩΝ |
Use of Microsoft Office 365 software for the theoretical part of the course, and use of specialised software for the laboratory part. | ||||||||||||||||||||||||
| ΟΡΓΑΝΩΣΗ ΔΙΔΑΣΚΑΛΙΑΣ |
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ΑΞΙΟΛΟΓΗΣΗ ΦΟΙΤΗΤΩΝ |
The assessment of students is carried out in the following two ways, in order to give them the opportunity to make choices: Ι. Work Progress (60%) and Thesis (40%). Participation is optional; students are tested in each discrete section of the course. Thesis writing is optional, but requires intensive student engagement with the subject. Instructions for the assignment as well as the due date for the assignment can be found in the educational platform e - class. II. Written final examination 100% for students who do not participate and do not prepare a paper. Language of Assessment: Greek. |
5. ΣΥΝΙΣΤΩΜΕΝΗ ΒΙΒΛΙΟΓΡΑΦΙΑ
| - Προτεινόμενη Βιβλιογραφία |
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1. M. A. H. Dempster, Juho Kanniainen, John Keane and Erik Vynckier (2018), High-Performance Computing in Finance: Problems, Methods, and Solutions, Chapman and Hall/CRC Financial Mathematics Series, 1st Edition. 2. Christopoulos D. (2024) Time Series Analysis, Tziolas Publications, Athens, Greece. 3. Veneti A. Ioannis, (2021) Introduction to Econometrics, Gotsis Publications. 4. R.H.Shumway, and D.S. Stoffer (2011) Time Series Analysis and Its Applications. with R Examples. 5. Jarrett, J. (1993) Forecasting Methods for Economic and Business Decisions, Gutenberg , Athens. 6. Ayiakloglu, H.N., Economou, G.S. (2002) Methods of Forecasting and Decision Analysis, Benou Publications, Athens. 7. Kondylis, E.K. (1999) Statistical Techniques of Business Administration, Interbooks Publications , Athens. |
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- Συναφή επιστημονικά περιοδικά: |