Time Series Analysis

5th or 7th Εξάμηνο

Ακαδημαϊκό Έτος 2025-26

Με Μια Ματιά

Κωδικός Μαθήματος

ΧΡΟΑΧ01

Τύπος Μαθήματος

Special background

Γλώσσα Διδασκαλίας

Greek

Το μάθημα προσφέρεται σε φοιτητές Erasmus;

Ναι

Τρόπος Παράδοσης

Face-to-face

Χρήση Τεχνολογιών Πληροφορίας και Επικοινωνιών

-The electronic platform is used for uploading the lecture materials.

-Lectures are conducted using a computer and econometric software/tool.

Αυτοτελείς Διδακτικές Δραστηριότητεσ

Τύπος

Lectures

Εβδομαδιαίες Ώρες

Μονάδες ECTS

7,5

Περιγράμματα Σπουδών

🇬🇷 Ελληνικά

🇬🇧 Αγγλικά

Συνδεσμοι

Αξιολόγηση Φοιτητών

Written final examination in the Greek language. The examination includes multiple-choice questions, comprehension questions on the material, and problem-solving exercises.
Midterm examination in the Greek language.
Assignment

Μαθησιακά Αποτελέσματα

The course aims to highlight the necessity of modern econometric tools in the analysis of financial concepts and phenomena. Specifically, the understanding, application, and analysis of financial data constitute essential skills in the toolkit of the modern economist.

Upon successful completion of the course, students will be able to:

Use a modern econometric software/tool,
Analyze the statistical and econometric properties of models,
Analyze financial data using statistical measures and graphical representations.

Γενικές Ικανότητες

Search, analysis, and synthesis of data and information using the necessary technologies
Independent work
Work in an international environment
Critical and self-critical thinking
Promotion of free, creative, and inductive thinking

Περιεχόμενο Μαθήματος

Basic concepts of statistics (distributions, descriptive statistics)
Types of data
Returns and portfolio theory
Regression analysis (ordinary least squares method, estimators, assumptions, standard error)
Hypothesis testing
Multiple linear regression (F-test, R²)
Principal Component Analysis (PCA)
Problems in econometric models (diagnostics, correction) – Heteroscedasticity, Autocorrelation, Multicollinearity, Parameter Stability
Univariate time series models
Moving average models
Autoregressive models
ARMA models
Modeling and forecasting