Program Structure

The total number of credits in the program is 90.

It includes seven (7) compulsory courses of which four (4) in the first semester with seven and a half (7.5) credits each and three (3) in the second semester with six (6) credits each, two ( 2) elective courses in the second semester with six (6) credits each and the writing of a dissertation in the third semester with thirty (30) credits. Two (2) non-credit preparatory courses are offered before the start of the program.

The Full Study Program of taught and examined courses is defined in detail as follows:

1st Semester

Introduction to Statistic Theory

The aim of the course is to present, develop and apply basic concepts of statistics. Descriptive statistical measures and diagrams useful for data exploration are presented, and the theory of basic continuous and discrete distributions is introduced. Methods and techniques for obtaining point estimators such as the maximum likelihood method and the least squares method are developed. The properties of the estimators and the sampling distributions that are used in statistical inference are presented. The construction of confidence intervals and the implementation of hypothesis testing are introduced and presented. Statistical techniques and methods are applied using the R package.

At the end of the course, students will be able to:

  • Compute useful descriptive measures and construct appropriate diagrams.
  • Understand the basic distributions and their usefulness in practice.
  • Calculate probabilities using basic distributions.
  • Apply parameter estimation methods such as the maximum likelihood method.
  • Understand the sampling distribution and its usefulness.
  • Construct confidence intervals and conduct hypothesis testing.
  • Apply statistical techniques and methods using the R package

Preparatory course: 0 ECTS

Introduction to Microeconomic Theory

The course examines the basic economic principles of finance. In more detail, it examines the way in which consumers decide how to allocate their income. It also analyzes the way in which companies decide what and in what quantities to produce. The properties of the various market forms are examined and compared according to their characteristics. In many markets firms interact and their analysis is done through game theory. An introduction to game theory and the concept of Nash equilibrium is given. Also, the equilibrium price and quantity are described in markets in which firms compete either by setting quantities or by setting prices.

By the end of the course students will be able to:

  • Understand the  way consumers  derive the demand curve.
  • Understand the  way the supply curve is derived in competitive market
  • Tο  analyze the characteristics of the four market structures.
  • To Understand the concept of Nash equilibrium.

Preparatory course: 0 ECTS

Industrial Organization and Policy

The course deals with Industrial Organization and antitrust and regulation policy. Examines the structure and the various ways firms are competing in imperfect markets as well as the necessary policies to improve market efficiency and productivity. Various models of optimal pricing, static and dynamic are analyzed and several case studies are studied.

After successful completion of this course the students must have understood  (a) the appropriate tools to analyze different product markets, (b) to expose students to the policy issues related to competition and regulation and (c) develop strategic thinking.

Compulsory course: 7.5 ECTS

Capital Market 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 also 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. 

Compulsory course: 7.5 ECTS

Game Theory & Strategic Decisions with applications in Economics

This 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. 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.

Compulsory course: 7.5 ECTS

Quantitative methods

The course introduces and presents the fundamental theory of statistical and econometric models, methods and techniques, which are essential in the research and analysis of economic and financial data. First, the theory of regression models, simple and multiple linear regression, is presented. Topics such as variable/model selection, use of dummy variables, and multicollinearity are examined. Emphasis is placed on the application of theory, examining residual hypotheses using diagnostic tests, and the interpretation of results is presented. The theory and practical application of time series analysis models are introduced and presented in detail. A detailed description and presentation of stochastic time series models (ARMA models) is made, and the Box-Jenkins methodology is developed. The course introduces the generalized linear models (logit/probit, log-linear models) used for the analysis of binomial data and frequency data (Poisson data). The break-point models and the basic checks for the existence of structural changes in financial data are presented and developed. Finally, panel data models are presented, as well as the techniques for estimating the parameters of these models. An analytical application of the theory, models and methods to empirical economic and financial problems is made using the R statistical package.

The aim of the course is to learn students how to use appropriate statistical and econometric methods, models and techniques required to analyze economic and financial data. Upon successful completion of the course, students will be able to:

  • To be able to apply, using the R package, econometric models to empirical economic problems and applications.
  • To be able to know and apply a wide class of econometric models to useful empirical problems.
  • To learn the principles of statistical and econometric inference, so that they are able to understand the analysis necessary for a particular data set, and how it can be properly applied.
  • To estimate the parameters of statistical and econometric models.
  • Conduct hypothesis tests and construct confidence intervals for population parameters.
  • Estimate regression models and time series models, construct forecasts and appropriately interpret the results of the analysis they conduct.
  • Estimate structural change models and panel models and apply them to empirical economic problems.

Compulsory course: 7.5 ECTS

2nd Semester 

Corporate Finance

Session 1. A primer on money creation in a modern economy

  • Quantitative Easing (QE) and asset valuations.
  • Quantitative Tightening (QT) and capital market turbulence. A view to the future.
  • Long-term refinancing operations, targeted operations, credit easing, outright monetary operations (OMT) and the Covid-19 pandemic emergency programs.

Session 2. Capital Structure: Optimal debt-equity choice.

  • Empirical patterns of corporate financing and possible explanations.
  • Types of financial instruments and markets.
  • Modigliani-Miller irrelevance proposition. An options-based approach to debt and equity valuations. The weighted average cost of capital (WACC) and WACC fallacies.
  • Capital structure under financial frictions. Taxes, financial distress costs and the static trade off (STO) in practice.
  • Debt-overhang: The underinvestment problem and the role of financial restructuring.
  • Equity capital raising and the mechanics of rights issues.
  •  Incentives, asymmetric information and the pecking-order of financing choices.

Session 3. Capital Budgeting: Risk, return, and free cas flow analysis

  • CAPM, asset betas, WACC, and the internal rate of return (IRR) in practice.
  • Data sources: Equity risk premium (ERP), marginal tax rates, sectoral betas and growth rates on operating income (EBIT).
  • Free cash flow analysis: Working capital, sunk costs, tax shields (amortization-depreciation and interest costs). 

Compulsory course: 6 ECTS

Business Finance & Strategic Business Decisions

The course contents:

  • Experimental design of alternative products/services
  • Empirical models of decision making Revealed preference discrete choice data analysis
  • Stated preference data analysis
  • Simulation of options/demand/market shares based on scenarios
  • Market segmentation, design of preference data collection tools

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 

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 
  • design data collection tools for the estimation of behavioral models

Compulsory course: 6 ECTS.

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.   

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

  1. To develop your capacity to understand  characteristics of time series such as stationarity, cointegration, causality, time dependence 
  2. To provide you with a stronger understanding in important topics in economics and finance such as risk and expected return.
  3. To enlighten your insights on the benefits that modern econometrics offer on optimal decision making in economics and finance 
  4. To give you hands-on experience in applying econometric techniques on economics and financial series, with the use of computational software. 
  5. To develop your powers in forecasting economics series with large datasets 

Compulsory course: 6 ECTS.

Indicative List of Elective Courses

*You are required to attend 2 (two) elective courses

Behavioral Economics

This course examines the role of systematic bias in the financial decisions of businesses and individuals, such as pricing and consumption decisions. The analysis is done first on a theoretical level through the construction of models and then through the construction of experiments and econometric analyzes. More specifically, the course focuses on biases such as overconfidence, naivety, aversion to loss, aversion to uncertainty, the Placebo phenomenon, reciprocity, the architecture of choices, the attachment to reference points, reputation mechanisms, the pursuit of social status and the cultural dimensions of human behaviour. Finally, we will develop analytical and quantitative behavioural tools to explain the behaviour of microeconomic and macroeconomic variables and we will extend the analysis to different subfields such as behavioral industrial organization, marketing, economic policy, finance and business.

Elective course: 6 ECTS

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

Banking Administration and Risk Management

The financial crisis that broke out in 2007 demonstrated the importance of recognizing and managing the multiple risks faced by financial institutions (FI). The course provides a comprehensive approach to managing the risks faced by FI: identifying, measuring and mitigating them. Emphasis is placed on the role of derivative products in reducing risk. Both internal systems and external prudential rules are covered, seeking solutions to the deficiencies that have led to failures in both self-regulation and supervision of FI.

Elective Course: 6 ECTS

Financial Derivative Products

The course covers the main derivative financial products: Forwards and futures on various underlying values. Options on stocks, indices, forex and futures. Interest rate and currency swaps. At the heart of the analysis are models of pricing as well as hedging of risks with derivatives or from derivative positions on behalf of financial organizations. Special topics covered include, among others, the Black-Scholes model, binomial trees, delta hedging as well as various applications such as real rights in finance.

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.

Elective Course: 6 ECTS

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.

After successful completion of this course the students must have understood:   

  • The problems that may arise from the distinction between business ownership and management.
  • The role of the board of directors
  • The ways of monitoring the decisions of business executives.
  • The corporate governance systems in different countries.

Elective Course: 6 ECTS

3rd Semester

Elaboration of Dissertation 

During the period of the 3rd semester, the students of the Master's Specialization Program undertake the writing of their dissertation. Completion of the Diploma is mandatory for full-time program students. The dissertation is supported before the examination committee and its evaluation is based on strict scientific criteria based on originality, depth and analysis, composition and quality.

Compulsory: 30 ECTS