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 |
BA%2B726 |
ΕΞΑΜΗΝΟ ΣΠΟΥΔΩΝ |
7 | ||
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ΤΙΤΛΟΣ ΜΑΘΗΜΑΤΟΣ |
Financial Computing I | ||||
| 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 | Speciality Course (S.C.) | ||||
| ΠΡΟΑΠΑΙΤΟΥΜΕΝΑ ΜΑΘΗΜΑΤΑ | No | ||||
| ΓΛΩΣΣΑ ΔΙΔΑΣΚΑΛΙΑΣ & ΕΞΕΤΑΣΕΩΝ | Greek | ||||
| IΤΟ ΜΑΘΗΜΑ ΠΡΟΣΦΕΡΕΤΑΙ ΣΕ ΦΟΙΤΗΤΕΣ ERASMUS | No | ||||
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ΗΛΕΚΤΡΟΝΙΚΗ ΣΕΛΙΔΑ ΜΑΘΗΜΑΤΟΣ (URL) |
https://
eclass.uowm.gr/courses/BA232/
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2. ΜΑΘΗΣΙΑΚΑ ΑΠΟΤΕΛΕΣΜΑΤΑ
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Μαθησιακά Αποτελέσματα |
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The aim of the course is to introduce the student to the basic quantitative methods of analysis of mainly financial time series, with the ultimate goal of understanding the relevant financial theory and its connection with modern computational practices. Upon successful completion of the course, the student will be able to: • Basic terms of finance with emphasis on capital markets. • Fundamental statistical measures of financial time series analysis • Univariate time series • Random walk • Correlation and Autocorrelation • -Computational environment in financial applications |
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Γενικές Ικανότητες |
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The student with the comprehensive theoretical training and acquisition of specific knowledge and skills is expected to be able to make : • Search, analyze and synthesize data and information, using and • using the necessary technologies. • Adapting to new situations. • Making decisions. • Working independently. • Working in teams. • Working in an interdisciplinary environment. • Generating new research ideas. • Exercise of criticism and self-criticism. • Promotion of free, creative and deductive thinking |
3. ΠΕΡΙΕΧΟΜΕΝΟ ΜΑΘΗΜΑΤΟΣ
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1. Capital Markets - Stock Market 2. Basic Statistical Measures of Financial Time Series 3. Introduction to univariate time series analysis 4. Stochasticity 5. Autocorrelation function 6. Random walk 7. Computing environment in financial applications 8. Applications |
4. ΔΙΔΑΚΤΙΚΕΣ και ΜΑΘΗΣΙΑΚΕΣ ΜΕΘΟΔΟΙ - ΑΞΙΟΛΟΓΗΣΗ
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ΤΡΟΠΟΣ ΠΑΡΑΔΟΣΗΣ |
Lectures and practical exercises in the Departments computer laboratory | ||||||||||||||||||||||||
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ΧΡΗΣΗ ΤΕΧΝΟΛΟΓΙΩΝ ΠΛΗΡΟΦΟΡΙΑΣ ΚΑΙ ΕΠΙΚΟΙΝΩΝΙΩΝ |
• Use of PowerPoint presentations • Sharing the presentation notes of the course via the educational online platform e class. • Use of the Departments computer lab for practical exercises. • Communication with students through e-class platform |
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| ΟΡΓΑΝΩΣΗ ΔΙΔΑΣΚΑΛΙΑΣ |
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ΑΞΙΟΛΟΓΗΣΗ ΦΟΙΤΗΤΩΝ |
STUDENT PERFORMANCE EVALUATION Description of the evaluation procedure Language of evaluation, methods of evaluation, summative or conclusive, multiple choice questionnaires, short-answer questions, open-ended questions, problem solving, written work, essay/report, oral examination, public presentation, laboratory work, clinical examination of patient, art interpretation, other Specifically-defined evaluation criteria are given, and if and where they are accessible to students. The assessment of students is carried out in the following four ways, in order to give them the opportunity to make choices: Ι. Practical exercises - Progress (40%) and Written final examination (60%). II. Assignment (40%) and Written Final Examination (60%). The preparation of the assignment is optional, but requires intensive engagement of the student with the subject. III. Practical Exercises - Progress (40 %), Work (40 %) and Written Final Examination (20 %). IV. Written final examination: 100% for students who do not participate in the practical exercises and do not prepare a paper. Language of Assessment: Greek. |
5. ΣΥΝΙΣΤΩΜΕΝΗ ΒΙΒΛΙΟΓΡΑΦΙΑ
| - Προτεινόμενη Βιβλιογραφία |
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1. Hyndman, R.J., & Athanasopoulos, G. (2021) Forecasting: principles and practice, 3rd edition (Greek translation), OTexts: Melbourne, Australia. OTexts.com/fppgr. 2. Christopoulos D. (2024) Time Series Analysis, Tziolas Publications, Athens, Greece. 3. Michalis - Gerasimos Strintzis. (2010), Time Series Analysis, Kyriakidis Bros Publications S.A., Greece. 4. Leontsinis, Alexandros (2000), Chaos Analysis and prediction of time series, Anikula. 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. |
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- Συναφή επιστημονικά περιοδικά: |