UNIVERSITY OF PIRAEUS

DEPARTMENT OF BANKING AND FINANCIAL MANAGEMENT

Postgraduate Program (M.Sc.) in Banking and Finance

Lesson: Quantitative Methods

Instructor: Dr. Panagiotis Samartzis

Bibliography:

• Chris Brooks, “Introductory Econometrics for Finance”, Cambridge University Press , 2019.
• Ενοποιημένες ποσοτικές μέθοδοι στα Οικονομικά, Εκδόσεις Διπλογραφία, 2019.
• Teacher notes.

Other bibliography:

• Helmut Lutkepohl, Markus Kratzig, “Applied Econometrics”, Cambridge University Press, 2008.

Course Description

Introduction

• Descriptive and Inductive Statistics.
• Deterministic and stochastic phenomena.
• Modeling principles.

Probabilities, random variables and probability distributions

• The concept of random and non-random sampling.
• Probability theory, random experiments, probability space.
• The concept of random variable, the cumulative probability distribution function, the probability density function and independence.
• Conditional Probability & Bayes Theorem.

Inductive Statistics

• Estimator, finite sample properties, asymptotic properties.
• Valuation methodology. Method of moments, method of maximum probability.
• Hypothesis testing and confidence intervals, the size and power of a statistical testing.
• ​​Properties of estimators, Gauss-Markov Theory, ​​Distributions of estimators.
• Applications using the Eviews program.

Regression

• The data generating process and regression models.
• Linear regression models, simple regression models, the classical multiple regression model, auto regressive models.

Simple Linear Regression Model

• Main assumptions.
• Heteroscedasticity, autocorrelation, multicolinearity.
• Statistical significance, confidence intervals, F-test, R-squared.
• Forecasts using regression models.