FIRST SEMESTER
CAPITAL MARKETS AND FOREIGN EXCHANGE MARKETS
Capital and money markets and foreign exchange markets are structural components of a modern market economy. This course analyzes these markets’ structure, organization, functioning, and participants. It focuses on issues of allocation, returns, efficiency, and empirical testing, as well as the role of volatility, utilizing appropriate theoretical and empirical tools. Particular emphasis is placed on the analytical view of new data, institutional dynamics, the introduction of new products, and the ongoing internationalization of the markets under examination.
Topics covered include, among others:
- The structure, organization, and functioning of capital and money markets
- The participants in these markets
- Issues of allocation, returns, efficiency, and empirical testing
- The role of volatility
- Institutional dynamics, the introduction of new products, and the internationalization of markets
- The role of technological advancements, electronics, and telecommunications
- The study of the Greek case
Upon successful completion of the course, the student will be able to:
- Have a comprehensive understanding of modern markets.
- Understand their dynamics.
- Grasp the mechanism of their operation.
- Know how new products are introduced into these markets.
- Recognize the stakeholders and their roles.
- Highlight the role of information and communication technologies in these markets
MODERN PROGRAMMING METHODS
This course aims to introduce students to the Python programming language. It covers the fundamental principles of programming to solve a series of empirical problems and useful applications. The goal is to understand the role that programming can play in problem-solving, regardless of the student’s prior programming experience. On a technical level, the course includes the basic principles of Python programming, such as values and variables, expressions and arithmetic, conditional execution, loops, functions, and more advanced libraries, such as objects, lists, tuples, dictionaries, and sets, as well as exception handling and custom types, all delivered through simple quizzes and real-world problems. Additionally, it covers concepts such as statistical inference and analysis, basic data analysis practices, and data processing using the NumPy and Pandas libraries.
Topics covered include, among others:
- Introduction to programming
- Variables and numbers
- Control structures and loops
- Lists, tuples, and sets
- Functions and libraries (NumPy and Pandas)
- File management
- Applications in finance
- Applications to real business data
Upon successful completion of the course, the student will be able to:
- Understand the basic principles of programming through Python
- Recognize the need and usefulness of programming
- Create programs to execute tasks
- Analyze business data
ANALYSIS AND VALUATION OF INVESTMENTS
The purpose of this course is to present the topics of Finance (Management) while also studying the subjects of Investments. Finance (Management) deals with two broad and interrelated areas: the valuation of businesses and investment opportunities in companies and the financing of companies and investment activities. Investments focuses on the fundamental principles of risk and return, diversification, asset allocation, and efficient markets. It covers forms of portfolio management (passive and active) and explains when each is applied, regarding the interests of banking, insurance, and investment organizations. Finally, it highlights the role of regulatory frameworks and supervisory authorities.
Topics covered include, among others:
- Business valuation
- Investment opportunities in companies
- Financing of companies and investment activities
- Capital structure
- Issuance of debt and equity
- Corporate governance
- Security valuation
- Fundamental principles of risk and return
- Portfolio management
Upon successful completion of the course, the student will be able to:
- Understand the markets, equity and fixed-income securities, investment strategies, modern portfolio theory, the capital asset pricing model, and derivative models of valuation.
- Perform the valuation of bonds and stocks, as well as construct portfolios and evaluate them using appropriate indicators.
- Understand the forms of portfolio management (passive and active) and explain when each is applied with reference to the interests of banking, insurance, and investment organizations.
- Recognize the importance of the role of regulatory frameworks and supervisory authorities (including central banks) in regulating investments, particularly within a common framework such as that of the European Union (and the Eurozone), as well as in adverse economic environments or during periods of crisis.
ALTERNATIVE FORMS OF INVESTMENTS
This course will present the distinctive characteristics of alternative investment options brelatiout so-called traditional investments (such as stocks and bonds), focusing on the theoretical and empirical models associated with these investments. It will also analyze how traditional approaches to Finance are applied to alternative investments and the additional theoretical tools necessary for studying these investments. Finally, the course will cover the specific investment processes followed in various alternative investments, such as different types of auctions.
Topics to be analyzed include:
- Investments in Private Equity
- Investments in Venture Capital
- Investments in Real Estate
- Investments in Art and Collectibles
- Investments in Hedge Funds
- Special topics (types of auctions, etc.)
Upon successful completion of the course, the student will be able to:
- Understand the characteristics and functioning of alternative investments.
- Recognize the differences between alternative investments and traditional investments.
- Comprehend the basic theoretical and empirical models related to alternative investments.
- Appreciate the significance of alternative investment options in the financial system and in the economy as a whole.
APPLICATIONS OF ECONOMETRIC MODELS
This course will emphasise the applications of econometric models for analyzing panel and cross-sectional data, that is, data at the level of individuals, businesses, and transactions. The need for microeconomic analyses arises from the increasing availability of relevant data, primarily through digitising transactions and modern data mining tools. Analyzing cross-sectional data helps to understand the economic behavior of individuals and businesses. The course will thoroughly address issues within these specific fields, allowing students to grasp the theoretical background of these methods and, importantly, specialize in their practical application.
Topics to be analyzed include:
- Linear and non-linear regression models
- Functional forms of models and interpretation of coefficients
- Models with auxiliary variables
- Analysis of discrete variable models
- Asymptotic properties of the OLS estimator and statistical tests
- Qualitative information: binary (or dummy) variables
- Policy evaluation methods
- Empirical applications using real data
Upon successful completion of the course, the student will be able to:
- Combine analytical thinking with practical applications.
- Understand the necessity of applying econometric methods.
- Select the appropriate model based on the data of the hypothesis under examination.
- Develop skills for conducting independent empirical research.
SECOND SEMESTER
BIG DATA ANALYSIS TOOLS
The development of information technology over the past decade has led to the availability of large volumes of structured (numerical) and unstructured data, which contribute to forecasting future risks/returns, assessing the outcomes of strategies, and providing high-quality personalized services. The purpose of this course is to overview the main methodologies used in the labor market and to provide the relevant technical skills through case studies, enabling students to perform all the necessary actions.
Topics covered include, among others:
- Databases, preprocessing, mining, managing, and presenting data (Hadoop, Tableau)
- Supervised analysis methods (Decision Trees and Random Forests, Linear & Logistic Regression)
- Unsupervised and semi-supervised analysis methods (Naive Bayes, k-Means, Gaussian Mixture Models)
- Modern applications in Finance
Upon successful completion of the course, the student will be able to:
- Understand recent developments in the field of big data analysis.
- Manage large databases and apply the key analysis methodologies using appropriate software.
- Extract necessary information from databases and conduct analyses to identify patterns for use in financial forecasting and risk management.
- Graphically represent and statistically describe the extracted information.
- Draw conclusions on investment strategies and policy recommendations based on the findings of inductive analysis.
BLOCKCHAIN TECHNOLOGY: INTRODUCTION AND APPLICATIONS
This course aims to introduce students to the principles of blockchain technology and the details of cryptocurrencies. It aims to ensure that fundamental and advanced blockchain technology concepts are understood. Specifically, it studies the characteristics that make blockchain technology unique and its applications, the most well-known of which are cryptocurrencies (especially Bitcoin), which will be explored in depth. The course covers the history, definitions, conceptual background, recognition, and criticism of cryptocurrencies. It explains how cryptocurrencies operate from when a transaction is created until it is considered part of the blockchain.
Topics covered include, but are not limited to:
- Properties of blockchain technology
- Functioning of blockchain
- History of money and early attempts to introduce cryptocurrencies
- Characteristics of cryptocurrencies: money, speculative assets, store of value
- Decentralized vs. centralized digital asset management/cryptocurrency management
- Stablecoins (backed by some asset or currency) vs. volatile cryptocurrencies
- Examples of cryptocurrencies such as Bitcoin, Ethereum, and projects like Libra/Diem
- Issues related to cryptocurrencies, such as financial regulation, anonymity, tax issues, criminalization, deflationary risks, etc.
- Uses of cryptocurrencies
- Future developments regarding cryptocurrencies
Upon successful completion of the course, the student will be able to:
- Analyze how blockchain technology can contribute to the development of sectors such as the financial industry, etc.
- Understand the characteristics of cryptocurrencies.
- Explain the issues related to cryptocurrencies.
- Distinguish between different types of cryptocurrencies.
- Recognize the various potential uses of cryptocurrencies.
BEHAVIORAL ECONOMICS AND PERSONAL FINANCE
This course aims to cover the behavioral aspects of economic decision-making and personal financial planning. Students will be introduced to the theoretical, conceptual, and empirical foundations of the errors and biases that investors encounter in financial markets. Students will become familiar with the terminology, techniques, and approaches used in modern financial advisory services through theoretical models and experimental exercises. The course will evaluate how households in Greece, the EU, and globally behave regarding their personal finances and assess how modern financial services are shaped. Finally, it will understand how personal finance issues are interconnected and how individual decisions relate to the macroeconomic environment and vice versa.
Topics covered include, but are not limited to:
- Basic principles of economic psychology in finance
- Insurance and behavioral economics in the healthcare sector
- Behavioral public economics and the economic psychology of tax behavior
- Personal finance and financial resilience
- Decentralized finance and behavioral personal finance
- Financial technology, errors, opportunities, and challenges
- Behavioral economics and practice: optimizing user engagement
Upon successful completion of the course, the student will be able to:
- Utilize key concepts from behavioral economics to analyze decision-making and design services aimed at personal financial planning.
- Explain the shortcomings of traditional approaches to financial education and use insights from behavioral economics and economic psychology to design more effective services.
- Evaluate how the design of financial products can be improved by applying the principles of behavioral economics.
- Predict how individuals respond to specific situations or incentives and assess policies aimed at increasing their effectiveness for a broader audience.
- Identify ways to encourage responsible financial behaviors through highly personalized approaches rather than one-size-fits-all solutions.
RISK MANAGEMENT
This course aims to expose students to the principles of risk management and insurance. Specifically, it introduces the key types of risks: market risk, counterparty or credit risk, operational risk, and insurance risk. It delves into the individual risks associated with market risk, including equity, interest rate, currency, derivative, liquidity, and concentration risks. The course analyzes the basic methods and measures of risk management. It presents life and property insurance products, key actuarial functions, and the pricing of these products. Finally, it analyzes the main financial derivatives and their use as tools for risk management and portfolio insurance.
Topics covered include:
- Key types of risks (market, counterparty or credit, operational, and insurance)
- Individual market risks (equity, interest rate, currency, derivatives, liquidity, and concentration)
- Basic methods and measures of risk management (sensitivity analysis, stress tests, and scenario analysis)
- Value at Risk – VaR
- Economic Capital
- Asset Liability Matching – ALM
- Key insurance products
- Financial derivatives
Upon successful completion of the course, the student will be able to:
- Understand the forms of risk and the measures used to quantify them.
- Calculate parametric VaR, historical VaR, Monte Carlo VaR, and VaR Contribution.
- Comprehend the significance of Economic Capital as a means of maintaining the solvency or credit rating of a financial institution.
- Understand the process of Asset Liability Matching (ALM) as a way to protect banking and insurance organizations from interest rate risk.
- Recognize life and property insurance products, the key actuarial functions, and the pricing of these products.
- Understand the main financial derivatives and their use as tools for risk management and portfolio insurance.
DIGITAL MARKETING
The evolution of digital technologies is now a fundamental factor in shaping the economic, social, political, and cultural environment worldwide. At the business level, these advancements are transforming the business landscape, making it more dynamic and uncertain, yet providing fertile ground for the development of new and innovative activities. The internet and digital technologies are crucial in shaping modern markets, creating new data, opportunities, and tools for marketing.
This course aims to present these possibilities at both strategic and tactical levels, linking them to the overall marketing strategy of an organization or company. Topics covered include: marketing strategy in the digital age, consumer behavior on the internet and other digital media, value creation, content marketing, pricing issues, advertising methods and tools on the internet (own, paid, earned media), Search Engine Optimization, new intermediaries and alternative networks, online business models, forms and capabilities of social networks, web analytics, and social media metrics. Additionally, the purpose of the digital marketing course is to equip students with knowledge about the advantages of digital marketing and its significance for the success of a company’s overall marketing efforts. Through this course, students will learn to develop a digital marketing plan, conduct e-SWOT analysis, define specific target groups, explore various digital channels, and understand the benefits and methods of integrating them effectively.
Topics covered include:
- Introductory Concepts & Functions of Modern Marketing & Consumer Behaviour.
- Customer Profile Design (Personas)
- Digital Marketing Development & Promotion Techniques
- Web Presence Design & Development
- Search Engine Optimization (SEO)
- Google Ads tools
- Social Media Marketing (Social Media Marketing & Platforms – Measurable actions in social media (Social media marketing metrics & analytics)
- Mobile Marketing Applications & Location-based Marketing apps
- Digital Marketing & Internet Analytics (Metrics, Performance Indicators, Neuromarketing)
Upon successful completion of the course, the student will be able to:
- Evaluate and critically discuss concepts and theories related to digital marketing.
- Demonstrate critical analysis skills to address complex real-life problems in digital marketing.
- Critically evaluate decisions made by organizations and businesses in creating digital marketing strategies.
- Examine and discuss recent trends and research concepts in digital marketing, critically evaluating relevant studies.
- Analyze and apply research tools to design and conduct rigorous and independent research in digital marketing.