# INDIVIDUAL COURSES

The courses for the full-time programme

Preparatory Courses (September - October)

Mathematics
The aim of the course is to provide students with the necessary mathematical tools employed in the teaching of main courses of the program and used in the related literature, as well as to familiarize them with the application of mathematics in addressing economic problems.The topics covered by the course are: functions and equations; the time value of money (the present and the future value of money); matrices (matrix operations, transposes and inverses, determinants, Cramer’s Rule); differential calculus (derivatives, rules of differentiation; Taylor Series expansion, maxima and minima of functions of one and of more than one variables, optimization with and without constraints); integral calculus (rules of integration, definite and indefinite integrals, improper integrals).

Statistics

The main objective of the course is to remind student the basic notions in statistics so that they would be able to follow a course in Quantitative Analysis or Finance.Course contents: Random Variables and their Probability Distributions: Discrete and Continuous Random Variables. Joint Distributions, Conditional Distributions, and Independence. Features of Probability Distributions: Expected Value, Median, Variance, Standardizing a Random Variable. Features of Joint and Conditional Distributions, Covariance, Correlation, Variance of Sum of Random Variables, Conditional Expectation. The Normal and Related Distributions. Population, Parameters, and Random Sampling. Finite Sample Properties of Estimators. Interval Estimation and Confidence Intervals: Confidence Intervals for the Mean from a Normally Distributed Population.

1st Semester (Οctober - February)

Economics of Financial Markets
The main goal of the course is for students to understand the relationship between the banking system and the financial markets. It focuses on how the liquidity in an economy is shaped, and what is the role of the commercial banking system in this process. The determinants of money supply are presented, whereas the various monetary policy tools as well as the role of a Central Bank are discussed. The money demand process is analyzed as well as the transmission mechanisms of monetary policy. Special attention is given to the presentation of the ECB and the Eurosystem.
Financial Reporting and Anlaysis

The aim of the course is to guide students in the area of Financial Reporting. The students taking this course should be able to evaluate alternatives and base their decisions by having a good understanding about the concepts and techniques of IFRS reporting practices. The key accounting issues will be explained considering rapid changes in the economic environment and global markets.

Key components of financial reporting are discussed:

Financial Reporting and Accounting Standards, Conceptual Framework for Financial Reporting, Statement of Financial Position and Statement of Cash Flows Cash and Receivables, Valuation of Inventories Depreciation, Impairment and Depletion, Intangible Assets, Investments, Revenue Recognition, Accounting for Leases, Statement of Cash Flows

Quantitative Methods
The lectures target to familiarize the class participants with the basic theoretical principles and the understanding of financial models. The objective of the applications is to familiarize the students with the various estimation techniques, applied on real data, on the areas of Economics and Finance. Random Variables. Covariance-Correlation dependence of random variables. Hypothesis Testing. Linear Regression and hypothesis testing. Economic Applications, with emphasis on CAPM. Transformations of random variables and introduction of dummy variables. Misspecification (autocorrelation, heteroskedasticity). Economic significance of heteroskedasticity with emphasis on portfolios and fund formation. GMM and Maximum Likelihood. Binary dependent variables (Logit, Probit). Introduction to time series with emphasis on GARCH and VAR models
Capital Markets and Portfolio Management

The aim of this course is to introduce students to the modern tools of investment analysis and appraisal, including investment decision under certainty and under uncertainty, pricing of risk, portfolio management, and asset pricing. It also covers topics on pricing fixed income securities, the term structure of interest rates and bond portfolio management. The course includes demonstrations/applications of the above techniques using computer software to see how they can be used, in practice. At the end of the course, the students would have learned the tools of the modern investment analysis and become familiar with their application, in practice.

Course contents: Investment decisions under certainty, Investment decisions under uncertainty, Mean-variance portfolio analysis, The Capital Asset Pricing Model, Factor models and the Arbitrage Pricing Theory, Bond Markets, The term structure of interest rates: theory and practice, Bond portfolio management and International capital markets and portfolio management.

2nd Semester (February - June)

Corporate Finance

Corporate Finance is one of the seven core courses of the program. Students taking this course should be able to:

Identify issues of first-order importance that are relevant to corporate financing, combine them to make informed decisions and negotiate funding terms with financiers. Identify turning points in economic policy that could have a material impact on funding conditions and corporate decisions to access external financing. Navigate in the new era of extraordinary policy interventions by central banks that have a profound impact on asset valuations and the cost of corporate financing. Value investment projects, conduct capital budgeting exercises, and identify factors that affect corporate decisions to access different forms of financing. Assess alternative ways of accessing capital markets.

Financial Derivatives

The aim of this course is to introduce students to the theoretical and practical aspects of financial derivatives.

Specifically, the course examines the pricing and use of financial derivatives including options, forward contracts, futures contracts, swaps and credit derivatives. The course will extensively focus on the theory and applications of derivatives in speculation and risk management. Moreover, the course includes a computational demonstration of the pricing models with excel.

Banking and Risk Management

By the course end, the students should be able to understand in depth:

The role and the types of financial institutions (FI)

The risks that face the FI,  Interest Rate Risk, Credit Risk, Liquidity Risk, Foreign Exchange Risk, Market Risk,Sovereign Risk, Off-Balance Sheet Risk,  Technology and other Operational Risks,  Fintech

Basel I, ΙΙ & ΙΙΙ and Capital Adequacy

Definition and Measurement of the Exposure to Risk using several methods such as Value-at-Risk (VaR) and Expected Shortfall.

Elective Course 1

Students select one elective course from the below indicative list course.

Elective Course 2

Students select one elective course from the below indicative list course.

3rd Semester (September - January)

Master's Dissertation

The Master’s dissertation is mandatory for students in the full-time programme.

* Elective Courses (indicative list)

Companies’ and Banks’ Valuations and Mergers

The objective of the course are the valuations and the mergers & acquisitions of companies and Banks. Issues such as: corporate finance, capital and alternative investments, financial reporting systems, business groups, capital structure and operations decisions, acquisition methods and strategies, corporate restructuring, stock valuations, terms of m&a’s transactions and shareholders’ agreements.

The desired learning outcomes are a full understanding of the concepts, tools, and methods of valuing companies as well as technical mergers & acquisitions, they will also be able to apply the above knowledge, tools, and methods in practice.

Credit Risk Management
The first section presents standard interest rates models. These are then used in practice to price option or futures on Treasury Bills and Bonds, as well as interest caps and floors. They can also be used to hedge against risky debt. Having introduced the above tools, the second section the course makes an introduction to the credit risk, credit ratings, estimation of default probabilities, calculates the credit risk on debt instruments, presents credit risky bonds, credit default swaps, futures and options on credit default swap spreads, options on swaps, and finally introduces the mortgage-backed securities. The latter can be found very useful for practitioners in the markets for their every day activities, while students will learn all the necessary tools for credit risk management.
Game Theory & Strategic Decisions: with applications in Economics

The chief purpose of this course is to enable the student to set up, study and solve games, especially games that arise in business and economics. To acquire a taste of the type of situations we would be interested in as well as the type of questions we would be asking, think of the following “real-life” situation.Τhis course is designed for people in business, for managers. It is as theoretical as necessary for providing an introduction to the science of game theory; and practical in that it offers many applications and case studies to make it attractive to managers in both the commercial and non-profit sectors, as well as to students in business.

Information Technologies, Trading & Investment Strategies

Dealing room operations focus, mainly, on trading financial securities and executing financial transactions, and are directly dictated from risk, liquidity and cash management constrains. The aim of this course is to make the student familiar with the functions, operations and trading strategies in the modern dealing room. It offers an opportunity to learn more about the Reuters Eikon application; the financial information service for professionals.The course attempts to develop an operational knowledge in trading financial securities with a focus on risk management and return enhancement. It deals comprehensively with the increased importance played by risk and uncertainty in today’s financial markets. Students are introduced to theoretical and empirical issues of different financial instruments, their valuation methodology, and their institutional uses in risk management.

Investments with statistical and computational methods and market microstructure

In this course we will use statistical and computational tools to study several aspects of trading in modern financial markets; What statistical facts about financial markets are useful for investors.  How quantitative trading models are constructed, implemented and evaluated. How markets are organised and how organisation affects trading costs. We will discuss several major asset classes including cryptos. The syllabus covers both theoretical work and empirical work.

Part 1: quant trading models, design and implementation

- Relevant statistical facts
- Building a quant trading model: return forecasts, risk forecasts and trading cost estimates

-  Porfolio construction and portfolio evaluation

Part 2: modern market structure and related concepts
- Core concepts (e.g. liquidity, transparency) and basic market design issues (i.e. auctions versus dealerships)
- How modern markets actually work and examples of recent innovations (e.g. dark trading regulation)

Part 3: current market issues and opportunities

-  Cryptos, bitcoin and blockchain

Large Data and Statistical Learning

This course is designed to introduce students to the concepts of large data handling and analysis with machine learning techniques. We start with computational analysis and inference and discuss the Monte Carlo, Bootstrap, k-fold cross-validation and recursive and rolling estimation methodologies. We provide a solid basis for time-series forecasting based on predictive linear regressions as well as using the Kalman Smoother. Next, we discuss large data handling techniques and discuss its features (seasonalities, nonstationarities). We discuss how unsupervised machine learning methodologies (k-means clustering, principal component analysis and dynamic factor analysis) could be applied in economics and finance forecasting applications (including the construction of Financial Conditions Indexes and Uncertainty Indicators). Next, we introduce the penalised regression methodologies of ridge, lasso and elastic net. We extend our discussion to unbalanced datasets and use bridge equations, MIDAS and U-MIDAS models as suggested remedies. Finally, our special topics include adaptive learning and modelling and applications of machine learning in portfolio selection.On top of our theory discussions, the course has a “hands-on” approach where all these methods applied in real data using the R Project for Statistical Analysis as the main scientific software.

Special Topics in Finance and Investments

The aim of this course is to present a number of risk management and investment applications to the students, which are used in practice. It covers topics in international portfolio risk management and currency risk, matual funds and portfolio performance evaluation, Investments strategies and value at risk (VaR) applications.

At the end of the course, the students will have become familiar with techniques and concepts on international investing risk management procedures and diversification, performance evaluation procedures and security selection, investment strategies accounting for taxes and inflation, investor constrains, investment policies and VaR procedures. VaR procedures for asset portfolios and loans management will be demonstrated through a an econometric package.

Applied Econometrics in Economics and Finance

This course is an applied, time series econometrics course, that focuses on estimation, modelling, forecasting and simulation of time series econometrics models. It will cover core of the theory concepts such as stationarity, parameter estimation, hypothesis testing, projections, volatility models (arch, garch, egarch), and the analysis of non stationary time series models, with applications in financial and economic series.  The objectives of the course is to develop your capacity to understand  characteristics of time series such as stationarity, cointegration, causality, time dependence To provide you with a stronger understanding in important topics in economics and finance such as risk and expected return. To enlighten your insights on the benefits that modern econometrics offer on optimal decision making in economics and finance To give you hands-on experience in applying econometric techniques on economics and financial series, with the use of computational software. To develop your powers in forecasting economics series with large datasets

After successful completion of this course the students must have a good understanding of:

experimental design theory and applications basic preference/choice model building theory and econometric estimation of basic and advanced choice/preference models

design data collection tools for the estimation of behavioral models

Furthermore, students are expected to obtain the necessary skills to :

use scientific software and develop codes independently, collect, handle and organize panels of choice data, visualize data and extract features, decompose and quantify the effect of attributes/characteristics on consumers’ choices/preferences simulate and predict choices, demand and market shares.

Corporate Governance

In the course we analyze the principles of corporate governance that guarantee the operation of firms in the best interests of their shareholders. This can be done by the alignment of incentives of executives with those of the shareholders. We examine the structure and the role of the board of directors, the compensation schemes of the business executives, and the internal and external control mechanisms of firms.  We also examine the  alternative corporate governance schemes in different countries. Finally, we examine issues of corporate social responsibility and sustainability.

The courses offered each year are decided upon by the Programme’s Special Interdepartmental Committee following a recommendation by the Programme’s Coordinating Committee.

It is possible for students to choose courses from other Master’s Programmes in the School or in the University following a decision by Programme’s Special Interdepartmental Committee, and the General Assembly or Special Interdepartmental Committee of the other Department/Programme.

Modification of the curriculum and redistribution of courses between semesters can be made following decisions of the governing bodies, in accordance with the Postgraduate Studies Regulations.