• Course title: 1.F1.Financial Markets and Institutions – The Luxembourg Financial Centre
• Number of ECTS: 3
• Course code: MScFE-25
• Module(s): Module 1.F.Fundamentals of Financial Markets, Investments and Microeconomic theory
• Language: EN
• Mandatory: Yes

–       The goal is to provide students with practical knowledge of the industry and enhance their comprehension of the functioning of the value chain within the industry. It enhances the fundamental finance education that they receive with actual statistics and developments as well as future developments of the industry. It should make the students more knowledgeable and provide them with the capability to show their future employers their knowledge of the current state of the industry and help them adapt more quickly to their future work environment.

 

 
v
 

Understand the financial markets in particular the role of its main actors, their services, their instruments
Acquire a big picture of the main processes that support the functioning of the markets
Understand the interactions of the main actors that act in the financial markets in a global and local approach
Have a sufficient culture of the processes handle by the actors of the Asset Management industry
Understand the function of all the participants in the Market and fund industry sector
Distinguish the global and the Luxembourg market
Distinguish main sectors of the industry
Understand impacts of the regulation
Distinguish the fields of applications
Have a global overview of the global legal context
Grasp the meaning of fintech
Discover the impact and opportunities brought by fintech
Know what is a pitch and learn more about the life of a fintech

Financial Markets and Institutions – The Luxembourg Financial Centre

I. Financial Markets and Institutions (14 units)
I.1. Financial Markets, Intermediaries, Primary and Secondary Markets – Bernard SIMON (8 TU)
This course presents in the details the Financial Markets, firstly in describing the actors and the assets that make part of the markets through their interactions between the actors and the function of the assets. Secondly, this course develops the processes, the rules, the risk management, and the legal limits of the primary and the secondary markets.

I.2. Financial Instruments, Asset management and Fund industry – Laura UBBENHORST (6 TU)
The course aims at giving the students an understanding of the operations of the financial market. It provides an overview of the most commonly used financial instruments and their respective functionality and practical use. The course also looks at the operations, dependencies, and collaborations of the individual players on the financial market of the Fund industry and helps to gain an understanding of the respective responsibilities and interactions with each other. The main focus thereby lies on the practical examples from the Luxembourgish market and aims to give an insight on the practical implications and the day-to-day management as existing in Luxembourg.
II. Luxembourg Financial Centre (14 units)
II.1. Introduction to the Financial Services industry in Luxembourg, Value chain of the Financial Services industry, Overview of main regulations governing Financial Services industry – Nicolas DELDIME (8 TU)
Introduction to the Financial Services industry in Luxembourg, collaboration fields with the global market In and OUT and understanding of the value chain of the Financial Services Industry.
II.2. Introduction to the Financial Services industry in Luxembourg, Statistics & academic approach Global market figures, trends Luxembourg‘s facts and figures Products, Key trends and future of the industry – Dariush YAZDANI (6 TU)
The course will give an in depth and practical view of the Global, European and Luxembourg financial services industry mainly: Asset and Wealth Management, Banking and Insurance. The goal is to give students a clear and practical understanding of the data, statistics, products and value chain of each of the sub-industries.
Seminary: Startup & Fintech in the Financial Market – Emilie ALLAERT (2 TU)
The first part of the course will guide the student through the origin of Fintech and determine whether it is a new or existing trend. What qualifies as Fintech and what are the sub-categories of Fintech. The course will then discuss the trends in Fintech, what is their impact on the various actors from the Financial Sector (Banks, Insurance, Asset Management …) and how we need to be prepared to work with them. It will also cover briefly the various technologies used.

Assessment Modality
End-of-course assessment
Assessment Tasks
Type of Assessment
Grading Scheme
Weight for final Grade
Task 1
Written exam
 
0-20
100 %
Specific Assessment Rules
3h
 

 

Compulsory literature:
The Fourth Industrial Revolution by Klaus Schwab
Complementary literature (to deepen the subject, this literature is not compulsory):
Foundations of Financial Markets and Institutions: Pearson New International Edition by Frank J. Fabozzi (Autor), Franco P. Modigliani (Autor), Frank J. Jones (Autor)
The New Lombard Street: How the Fed Became the Dealer of Last Resort Hardcover by Perry Mehrling (Autor)   

• Course title: 1.F2.Financial Accounting & Reporting
• Number of ECTS: 3
• Course code: MScFE-26
• Module(s): Module 1.F.Fundamentals of Financial Markets, Investments and Microeconomic theory
• Language: EN
• Mandatory: Yes

Prepare and understand basic accounting entries
Prepare and understand the content of the financial statements of a company
Apply basic financial ratios to the F/S of a company
Understand the specific investor reporting requirements of an alternative investment fund in Luxembourg

Financial accounting architecture, mechanisms and conventions
Structure and content of the key statements (Balance sheet, profit and less accounts, annex, cash flow)
Key financial ratios
Investor reporting requirements (case of an alternative investment fund)

Assessment Modality
End-of-course assessment
Assessment Tasks
Type of Assessment
Grading Scheme
Weight for final Grade
Task 1
Written exam
 
0-20
100 %
Specific Assessment Rules
2h
 

Literature:

N/A

• Course title: 1.F3.Fixed Income Analysis
• Number of ECTS: 4
• Course code: MScFE-27
• Module(s): Module 1.F.Fundamentals of Financial Markets, Investments and Microeconomic theory
• Language: EN
• Mandatory: Yes

Understand and use analytical techniques in the field of fixed-income securities (present value, forward rates, yield-to-maturity, term structure theories, duration calculation and management of interest rate risk)
Acquire the key fundamentals for investing in fixed income securities issued by sovereigns, banks and corporates

Introduction to Fixed Income Instruments: Features of Debt Securities
Bond Sectors and Instruments:
o   Sovereign, Agency, Corporate Bonds, Asset Backed
o   Primary and Secondary Markets
Risks Associated with Investing in Bonds
Introduction to the Valuation of Debt Securities
Yield Measures, Spot and Forward Rates
Measurement of Interest Rate Risk
Term Structure and Volatility of Interest Rates
Interest Rate Derivatives and Valuation of Interest Rate Derivatives
Credit Analysis and Credit Risk
Introduction to Bond Portfolio Management
Managing Funds against a Bond Market Index
Portfolio Immunization and Cash Flow Matching

Assessment Modality
End-of-course assessment
Assessment Tasks
Type of Assessment
Grading Scheme
Weight for final Grade
Task 1
Written exam
 
0-20
100 %
Specific Assessment Rules
1.5h
 

Literature:

Fixed Income Analysis (Third edition) by Barbara S. Petitt, Jerald Pinto, Wendy Pirie, CFA Institute Investment Series, Wiley.
Fixed Income Analytics by Kenneth D. Garbade, MIT Press
Credit Risk Measurement by A. Saunders, Wiley Frontiers in Finance

• Course title: 1.F4.Modern Portfolio Theory
• Number of ECTS: 5
• Course code: MScFE-28
• Module(s): Module 1.F.Fundamentals of Financial Markets, Investments and Microeconomic theory
• Language: EN, FR
• Mandatory: Yes

Understand how investor preferences can be represented
Have a good grasp of the distributional and preference assumptions underlying mean-variance analysis
Understand the principle of diversification in portfolio management
Analyse the relationship between risk and return in the context of MPT
Construct mean-variance optimal portfolios for a single investment horizon to achieve investment objectives
Understand the role of the risk-free asset and its integration into portfolios
Have a good understanding of asset pricing in the mean-variance framework and of the Capital Asset Pricing Model (CAPM)
Have a deep understanding of its underlying assumptions
Critically assess the strengths and weaknesses of the CAPM
Learn mathematical techniques for optimizing portfolios
Understand the impact of constraints in portfolio optimization
Implement portfolio optimisation using software tools and real-world data
Critically assess MPT, including its underlying assumptions about the distribution of stock returns and investor behaviour
Gain proficiency in French (for students who choose to follow the course in French)

choice under uncertainty – i.e. investment decisions when returns are uncertain. It introduces the students to the concepts of risk and return and the role of diversification in reducing portfolio risk. The course further focuses on the investors’ objectives in terms of their preferences for risk and return. It proceeds by delineating the optimum investment possibilities that can be constructed from the available set of investment opportunities. In that framework, students will learn how to construct optimal portfolios, maximizing the expected return given a certain amount of risk, which provides the basis for investment strategies widely applied by portfolio managers. 
The course is structured as follows:

1. Introduction
a. Choice Theory under Uncertainty
b. Modern Portfolio Theory: The Basic Portfolio Problem
c. The Portfolio Management Process

2. Investor Preferences
a. Risk Aversion
b. Mean-Variance Utility Functions
c. Indifference Curves
d. The Optimal Portfolio Selection Problem

3. Mean, Variance and Covariance of Asset Returns
a. Random Returns
b. Mean and Variance of Returns
c. Covariance and Correlation of Returns
d. Using Historic Data: Time Series vs. Scenario Analysis; Sample vs. Population

4. Mean and Variance of Portfolio Returns
a. Portfolio Return
b. Mean Return of a Portfolio
c. Variance of a Portfolio Return
d. Variance-Covariance Matrices and Covariance between Two Portfolios

5. Portfolio Diversification
a. Systematic vs. Unsystematic Risks
b. The Concept of Diversification
c. The Power of Diversification and its Limits

6. Portfolio Analysis with Two Risky Assets
a. The Investment Opportunity Set
b. The Minimum-Variance Portfolio
c. The Efficient Frontier
d. The Optimal Portfolio for the Investor
e. Introducing a Risk-Free Asset

7. The Markowitz Portfolio Optimization Model
a. The Efficient Frontier of Risky Assets
b. The Optimal Risky Portfolio
c. The Optimal Complete Portfolio
d. Capital Allocation and the Separation Theorem

8. Portfolio Analysis with N Risky Assets: Analytic Solutions
a. Efficient Portfolios Without a Risk-Free Asset
b. Black’s Two-Fund Theorem
c. Efficient Portfolios with a Risk-Free Asset

9. The Capital Asset Pricing Model
a. Assumptions
b. The Market Portfolio and the Capital Market Line
c. Deriving the CAPM Equation
d. The Security Market Line
e. Using the CAPM

Assessment Modality
End-of-course assessment
Assessment Tasks
Type of Assessment
Grading Scheme
Weight for final Grade
Task 1
Written exam
 
0-20
100 %
Specific Assessment Rules
2h
 

 

Literature:

David G. Luenberger, Investment Science, Oxford University Press, 2nd edition
Jack Clark Francis and Dongcheol Kim, Modern Portfolio Theory, Wiley Finance
Zvi Bodie, Alex Kane, and Alan J. Marcus, Investments, Mc Graw Hill
Additional reading:
Edwin J. Elton, Martin J. Gruber, Stephen J. Brown, and William N. Goetzmann, Modern Portfolio Theory and Investment Analysis, Wiley
Barucci E. and C. Fontana, Financial Markets Theory, Springer
Simon Benninga, Financial Modeling, MIT Press
Morris DeGroot and Mark Schervish, Probability and Statistics, Pearson New International Edition, 4th edition

• Course title: 1.F5.Microeconomics, Risk and Information
• Number of ECTS: 5
• Course code: MScFE-29
• Module(s): Module 1.F.Fundamentals of Financial Markets, Investments and Microeconomic theory
• Language: EN
• Mandatory: Yes

Acquire analytical tools and theoretical foundations necessary for any specialisation at upper-level such as labour economics, industrial organisation, international trade, public finance, etc.

This course:
Presents in an accessible fashion all the essential topics in microeconomics typically required at the intermediate level for students in economics and finance
Covers the topics of consumer and producer theory moves on to that of market structure (perfect competition, monopoly, monopsony, oligopoly)
Introduces notions of risk, game theory, general equilibrium (exchange economy), externalities, asymmetric information, and public goods

Assessment Modality
Combined or continuous assessment
Assessment Tasks
Type of Assessment
Grading Scheme
Weight for final Grade
Task 1
Written exam
 
0-20
80 %
Specific Assessment Rules
2h
 
Task 2
Other, please specify
Assignments
0-20
20 %
Specific Assessment Rules
N/A
 

Literature:

Lectures and TDs are self-contained.
Recommended literature on which the course is articulated: Intermediate Microeconomics, Samiran Banerjee (purchase not obligatory).

• Course title: 1.D1.Mathematics
• Number of ECTS: 3
• Course code: MScFE-35
• Module(s): Module 1.D.Mathematics and Data Analysis I
• Language: EN
• Mandatory: Yes

Work out first order linear and non-linear differential equations
Do first and second order conditions of optimal problem with and without constraints
Use maximum principle and dynamic programming study dynamic optimisation
Obtain some basic idea of Stochastic calculus and optimisation

This course provides students a solid foundation in mathematics, which includes the following topics:
1. Calculus Review:
Cover single-variable calculus topics, including: Derivatives (product rule, chain rule, implicit differentiation); Integrals (definite and indefinite);  use examples and real-world applications to illustrate each concept.
2. Linear Algebra Review:
Discuss fundamental linear algebra concepts: Vectors and vector spaces,  Matrices (addition, multiplication, inverse), Determinants,  Eigenvalues and eigenvectors and connect linear algebra to applications (e.g., solving systems of linear equations, transformations, leas
3. Multivariable Calculus:
Extend calculus to functions of multiple variables: Partial derivatives, Gradient, Hessian matrix, Emphasize applications in economics  and optimization.
4. Optimization:
Introduce optimization techniques: Unconstrained optimization, Constrained optimization (Lagrange multipliers) and applications (portfolio optimization, production planning).  Provide practical examples and exercises.
5. Equality and Inequality Constraints:
Explore optimization problems with constraints, Karush-Kuhn-Tucker conditions.  Show how to handle both equality and inequality constraints.

Assessment Modality
End-of-course assessment
Assessment Tasks
Type of Assessment
Grading Scheme
Weight for final Grade
Task
Written exam
 
0-20
100 %
Specific Assessment Rules
2h
 

Literature:

L. Blume and C. Simon. Mathematics for Economists.
Chiang, A.  and  K. Wainwright. Fundamental Methods of Mathematical Economics.
Chiang, A.  Elements of dynamic optimization.
Kamien M and N. Schwartz. Dynamic optimization: The calculus of variations and optimal control in Economics and Management.

• Course title: 1.D2.Statistics
• Number of ECTS: 2
• Course code: MScFE-36
• Module(s): Module 1.D.Mathematics and Data Analysis I
• Language: EN
• Mandatory: Yes

Describe the dependence among random variables using properties of the multivariate distributions and of the conditional and unconditional expectations of the random variables
Build predictors of variables given the values taken by other random variables
Test whether features of samples differ statistically across different samples

Random variables. Continuous and discrete random variables and their distributions. Expectations of random variables. Independence of random variables. Unconditional and conditional distributions, their properties. Multivariate distributions. Conditional expectation as predictor. Multivariate normal random vectors and their properties. Bayes statistics. Hypothesis testing and confidence intervals. 

Task 1
Test 1_Written exam
Grading Scheme: 0-20
Weight for final Grade: 45%
Task 2
Test 2_Written exam

Grading Scheme: 0-20
Weight for final Grade: 45%
Task 3
Take-home exam_Homework in Excel
Grading Scheme: 0-20
Weight for final Grade: 10%

Literature

Recommended reading:
Probability and Statistics, by Morris DeGroot and Mark Schervish, Pearson New International Edition, 4th edition (2012)
Introductory Econometrics: A Modern Approach, by Jeffrey Wooldridge, CENGAGE Learning Custom Publishing, 7th edition (2018), Appendices A, B, C

Miller, M. B. Mathematics and statistics for financial risk management. John Wiley Sons., 2nd edition (2014)
Békés, G., Kézdi, G. Data analysis for business, economics, and policy. Cambridge University Press., 1st edition (2021)

• Course title: 1.D3.Econometrics I ( R )
• Number of ECTS: 5
• Course code: MScFE-37
• Module(s): Module 1.D.Mathematics and Data Analysis I
• Language: EN
• Mandatory: No

Acquire the statistical foundations required to perform statistical analysis in business settings. Very often one needs an accurate and informative analysis of a sample of data. For example, the data might be financial returns, employee salaries, or advertising
Use descriptive statistics to summarise a set of data
Apply methods of statistical inference to try to draw generalisations from the sample for the broader population
Recognize the existence of sampling uncertainty before accepting or rejecting a research hypothesis
Undertake ‘multivariate’ analysis
Distinguish the relationships between several variables

Prerequisites:

Previous knowledge of statistical analysis is not a prerequisite. Although many participants will previously have studied statistics, the course will aim to accommodate those who have only had minimal exposure to the subject. Furthermore, previous experience with statistical software is not necessary. General digital literacy is however required.

–

Econometrics course using the software R for students interested in the finance tracks in the second year.
Use of R (basic datafile manipulation, descriptive statistics, test theory)
Simple OLS regression analysis
Multiple OLS regression analysis
Asymptotic properties
Univariate time series modelling and forecasting

Assessment Modality
Combined or continuous assessment
Assessment Tasks
Type of Assessment
Grading Scheme
Weight for final Grade
Task
Written exam
 
0-20
50 %
Specific Assessment Rules
1h
 
Task
Take-home exam
 
0-20
50 %
Specific Assessment Rules
 
 

Literature:

Introductory Econometrics for Finance by Chris Brooks
Introductory Econometrics: A Modern Approach by Jeffrey M. Wooldridge
Statistics: An introduction using R by Michael J. Crawley

• Course title: 1.D4.Econometrics I ( STATA )
• Number of ECTS: 5
• Course code: MScFE-38
• Module(s): Module 1.D.Mathematics and Data Analysis I
• Language: EN
• Mandatory: No

Conduct econometric analyses involving cross sectional and panel data
Understand the theoretical foundation of Econometrics
Estimate models with the Stata econometrics software
Understand the concept of hypothesis testing
Understand the consequences of deviations from key assumptions behind OLS estimation
Understand the issue of unobserved heterogeneity in panel data
Use simple panel estimators

Chapter 1 Reminders about OLS regression
Chapter 2 Multiple Regression Model. Inference, reminders
– Hypothesis testing (follow up)
Chapter 3 Additional problem in multiple regression models
– Units of Measurement
– More on Functional Form
– More on Goodness-of-Fit and Selection of Regressors
Chapter 4 Additional problem in multiple regression models (follow-up): Prediction Intervals and Residual Analysis
Chapter 5 Multiple Regression Models with Qualitative Information. Dummy Variables
– MLR with binary variables
Chapter 6 Heteroskedasticity
– Consequences of Heteroskedasticity for OLS
– Heteroskedasticity-Robust Inference
– Testing for Heteroskedasticity
Chapter 7 Panel data
– Unobserved heterogeneity
– Types of panel estimators
– Fixed effect estimator
– Random effect estimator
– First differences
– Applications

Assessment Modality
End-of-course assessment
Assessment Tasks
Type of Assessment
Grading Scheme
Weight for final Grade
Task
Written exam
 
Choose an item.
100 %
Specific Assessment Rules
3h
 

Literature:

Introductory Econometrics: A Modern Approach, 5e, South-Western, Cengage Learning by Jeffrey
M. Wooldridge, 2013, ISBN-10: 1111531048 ISBN-13: 9781111531041

• Course title: 1.O1.VBA
• Number of ECTS: 2
• Course code: MScFE-34
• Module(s): Module 1.O.Extra-curriculum I (Module +)
• Language: EN
• Mandatory: No

Complete standard tasks in Excel/VBA
Develop any additional Excel/VBA skills they need on their own
Acquire an overview of the vast array of tasks that can be automated with VBA
Plot graphs in Excel
Handle dates and time in Excel
Use built-in functions in Excel
Implement sensitivity analysis in Excel
Be more productive in Excel using macros, shortcuts, named variables
Write programs in VBA
Debug programs in VBA
Call VBA functions from Excel
Write VBA subroutines
Generate VBA subroutines by recording a sequence of actions
Use Excel to prototype complex functions in VBA
Work with random variables and perform basic statistical analyses
Generate financial reports in pdf

 

 

 

Part I: Core knowledge
Topic 0 Introduction to the course
Topic 1 Excel Essentials
Presentation of Excel
Basic manipulations in Excel and some built-in functions
Sensitivity analysis in Excel
Optimization analysis in Excel
Topic 2 Introduction to programming with VBA
Writing (small) programs in VBA
Functions and control structures in VBA
VBA subroutines
Part II: Financial Modeling with VBA
Topic 3 Use of VBA routines in a realistic set up
Case study of the performance of a portfolio insurance strategy
Present how people use Excel and VBA in practice
Stimulate ideas regarding how to use Excel in your professional life
Topic 4 Topics in Excel / VBA
Working with random variables
Loops and conditional statements
Generating a financial report

Assessment Modality
Combined or continuous assessment
Assessment Tasks
Type of Assessment
Grading Scheme
Weight for final Grade
Task 1
Take-home exam
 
0-20
30 %
Specific Assessment Rules
N/A
 
Task 2
Take-home exam
 
0-20
70 %
Specific Assessment Rules
N/A
 

Literature:

Benninga, S., Mofkadi, T. (2022). Financial modeling, fifth edition. MIT Press (Recommended)
Winston, W. (2021) Microsoft Excel Data Analysis and Business Modeling (Office 2021 and Microsoft 365) (7th ed.) Microsoft Press (Recommended)

• Course title: 2.F1.Asset Pricing Theory
• Number of ECTS: 5
• Course code: MScFE-40
• Module(s): Module 2.F: Asset Pricing and Macroeconomic Theory
• Language: EN
• Mandatory: Yes

Make informed financial decisions
Price basic financial assets (e.g., Bond, European options)
Understand the motivations and incentives of financial market participants

1. Introduction to Asset Pricing Theory
On the Course and Asset Pricing
Asset Pricing without Risk
Application: Present value formula
2. Elements of Probability for Asset Pricing
Probability Space
Moments
Application: ARCH model
3. Absolute Pricing with Risk
One-Period Consumption-Based Asset Pricing
Multiperiod Consumption-Based Asset Pricing
Application: CAPM and CCAPM models
4 Relative Pricing Fundamentals
Discrete time modeling
Continuous time modeling
Application: Binomial model & Black Scholes model
4 Factor pricing*
From factor models to expected return-beta representations
Empirical factor models
Application: APT
*indicates topics that are less likely to be covered due to time constraint

Assessment Modality
Combined or continuous assessment
Assessment Tasks
Type of Assessment
Grading Scheme
Weight for final Grade
Task 1
Written exam
 
0-20
60 %
Specific Assessment Rules
2h
 
Task 2
Active participation
 
0-20
20 %
Specific Assessment Rules
N/A
 
Task 3
Other, please specify
 
0-20
20 %
Specific Assessment Rules
Pop quizz
 

Literature:

Emilio Barucci and Claudio Fontana, Financial Markets Theory, Springer, chap. 1-4 6, 2017 (2nd edition).
Gabrielle Demange, and Guy Laroque. Finance and the Economics of Uncertainty. Blackwell, 2005
Steven E. Shreve, Stochastic Calculus for Finance II, chap. 1-4. 2000

Further handouts and recommended readings relevant for the course and the examination will follow in due course, as discussed in class.

• Course title: 2.F2.Macroeconomics and International Finance
• Number of ECTS: 5
• Course code: MScFE-41
• Module(s): Module 2.F: Asset Pricing and Macroeconomic Theory
• Language: EN
• Mandatory: Yes

 

Use the framework developed in class to study questions such as:
o What determines output, consumption, investment?
o What causes recessions? What causes financial crises?
o How do macroeconomics and finance interact?
o What is the relationship between fiscal deficit and current account deficit?
o What determines inflation?
o What are the factors accounting for the recurrent fluctuations in employment and output called the business cycle?
o What factors account for exchange rate fluctuations?
We will not provide definitive answers to these questions. However, we will present a framework for thinking about these questions and for reviewing the various sides in the debates.

This class provides the foundations needed to understand how the macroeconomy operates, with a particular emphasis on the broad economic and financial movements in the global economy.
We will construct models to understand the determination of aggregate output, unemployment, prices, interest rates, inflation, and open economy topics, in the short-run and the medium-run, with applications to European economies and discussions of macroeconomic policy issues.

Assessment Modality
Combined or continuous assessment
Assessment Tasks
Type of Assessment
Grading Scheme
Weight for final Grade
Task 1
Written exam
 
0-20
75 %
Specific Assessment Rules
2h
 
Task 2
Other, please specify
 
0-20
25 %
Specific Assessment Rules
Problem Set
 

Literature:

Course slides. Disclaimer: the slides serve as supporting material for the lectures and are by design incomplete. You should expect to take notes, as everything that I say in class is potentially examinable. The slides may also contain errors and approximations. If what I say in class deviates from these notes, trust me over the notes. If you see any typos (or even something that just could be clearer), please email me.
The class loosely follows these two textbooks:
– Kurlat, Pablo (2020), A Course in Modern Macroeconomics,
https://sites.google.com/view/pkurlat/a-course-in-modern-macroeconomics
– Schmitt-Grohe, Stephanie, Uribe, Martin and Woodford, Michael (2020), International Macroeconomics,
http://www.columbia.edu/~mu2166/UIM/index.html
Additional references:
– Romer, D. (2011). Advanced macroeconomics, fifth edition.
– Obstfeld, M., Rogoff, K. (1996). Foundations of international macroeconomics. MIT press.
– Terra, Cristina (2015), Principles of International Finance and Open Economy Macroeco-nomics: Theories, Applications and Policies, Academic Press.
– Williamson, S. D. (2018). Macroeconomics, 6th.
As the class develops, other references may be assigned for further advanced background readings.
Complementary material, including slides to be used in class, can be downloaded from the course Moodle.

• Course title: 2.D1.Econometrics II (R)
• Number of ECTS: 5
• Course code: MScFE-42
• Module(s): Module 2.D: Data Analysis II
• Language: EN
• Mandatory: No

Use adequately the data analysis techniques presented in class
Quickly learn and critically assess new data analysis techniques on their own

 

 

1. Basics of Econometrics
   The magic of econometrics
   LLN & CLT
2. Introduction to programming with R
   Data & computer basics
   Introduction to R
   Introduction to programming with R
3. Fundamentals of linear regression
   Regression model
   Justifications for the linear regression model
   Estimation
4. Parametric inference
   Estimation principles: MLE & MM
   Model selection
5. Classification
   Gaussian classifiers: QDA & LDA
   Binary response models: Linear probability model & Logistic regression
   Support vector machine
   Trees
   

Assessment Modality
Combined or continuous assessment
Assessment Tasks
Type of Assessment
Grading Scheme
Weight for final Grade
Task 1
Written exam
 
0-20
60 %
Specific Assessment Rules
2h
 
Task 2
Active participation
 
0-20
20 %
Specific Assessment Rules
N/A
 
Task 3
Other, please specify
 
0-20
20 %
Specific Assessment Rules
Pop quiz
 

 

 

 

 

Literature:

Trevor Hastie, Robert Tibshirani, Jerome Friedman (2009). The Elements of Statistical Learning. Available at https://web.stanford.edu/~hastie/ElemStatLearn/
Stéphane Tuffery, Data Mining and Statistics for Decision Making, Wiley series in computational statistics, Wiley
Larry Wasserman (2004) All of Statistics. A Concise Course in Statistical Inference

Further handouts and recommended readings relevant for the course and the examination will follow in due course, as discussed in class.

• Course title: 2.D2.Econometrics II (STATA)
• Number of ECTS: 5
• Course code: MScFE-43
• Module(s): Module 2.D: Data Analysis II
• Language: EN
• Mandatory: No

Formulate a research question and its related hypothesis to test empirically
Use statistical software (STATA) to gather, organize and process data to answer a research question
Use statistical software to produce graphs and tables to be used in scientific reporting
Discriminate between identification strategies to answer a research question
Interpret the output of empirical research in scientific journals

The objective of the course is twofold. First, it aims to familiarise students with research designs and the different tools economists use to identify causal relationships. Second, it intends to train students with data manipulation.
 
The course starts with a complete presentation of what research design and causality means. The second part of the course presents the economist toolkit to identify causal estimates (including panel data regressions, difference-in-differences, regression discontinuity designs)

Assessment Modality
Combined or continuous assessment
Assessment Tasks
Type of Assessment
Grading Scheme
Weight for final Grade
Task
Other, please specify:
mid-term exam

0-20
30 %
Specific Assessment Rules
 
 
Assessment Modality
Final exam during exam session
Assessment Tasks
Type of Assessment
Grading Scheme
Weight for final Grade
Task
Written exam  90 min

 
0-20
70 %
Specific Assessment Rules
 Closed book
 

Literature:

“Causal Inference The Mixtape”, by Scott Cunningham, Yale University Press, 2021 (main reference)
 
“Mostly Harmless Econometrics”, by Joshua Angrist and Jörn-Steffen Pischke, Princeton University Press, 2009
 
“The Effect: An Introduction to Research Design and Causality” by Nick Huttington Klein, Chapman and Hall/CRC, 2021
 
“Causal Analysis”, by Martin Huber, MIT Press, 2023
 
Selected papers.
 

• Course title: 2.E1.Financial Analysis and Valuation
• Number of ECTS: 5
• Course code: MScFE-44
• Module(s): Module 2.E: Special Topics in Finance and Economics – Electives I
• Language: EN
• Mandatory: No

    Leverage case studies for practical evaluation of Equity investments and diverse assets
    Determine if securities are overvalued, fairly valued, or undervalued using current market prices and valuation estimates
    Understand and describe different equity valuation models used in professional settings
    Comprehend and articulate various equity distribution mechanisms, including dividends, stock splits, and repurchases
    Describe the dividend payment process in detail
    Use present value models for equity valuation, focusing on dividend discount and free-cash-flow-to-equity models, with real data
    Calculate the intrinsic value of non-callable, non-convertible preferred stocks using actual financial figures
    Evaluate the intrinsic value of equity securities using both the Gordon growth and two-stage dividend discount models, with real-life examples
    Identify which companies are suitable for different dividend discount models based on real industry scenarios
    Implement price multiples in equity valuation, understand their connection to fundamental financial metrics, and apply comparable analysis
    Effectively present and explain their valuation results and analysis to investment boards, translating complex financial concepts into actionable insights for decision-makers

This course introduces students to spreadsheet modelling and various techniques essential for investment analysis, company valuation, forecasting, and more, with a particular focus on Equity Markets and Investment Portfolios. We will delve into case studies, emphasising practical applications in these areas. Valuation extends beyond mere numerical analysis. It demands judicious model selection and careful derivation of inputs. We’ll delve into the most widely used equity valuation models, including present value models, multiplier models, and asset-based valuation, each serving a crucial role in intrinsic value estimation. When it comes to valuing a company or a group of companies, selecting a suitable valuation model becomes imperative, guided by the available data. This data not only influences the choice of the model but also how it’s employed in the valuation process. While more complex models exist, potentially offering refined valuation, it’s essential to remember the “law of parsimony”: a model’s complexity should align with the inputs at hand. Simplicity often trumps complexity in terms of practicality and relevance. It is important to acknowledge the inherent fallibility of valuation. No method guarantees absolute accuracy, and forecasts will inevitably be off the mark at times. Our objective is to minimise these inaccuracies, striving for the most reliable forecasts possible within the given constraints.

Assessment Modality
Combined or continuous assessment
Assessment Tasks
Type of Assessment
Grading Scheme
Weight for final Grade
Task 1
Other, please specify
 
0-20
50 %
Specific Assessment Rules
Case Study
 
Task 2
Presentation
 
0-20
50 %
Specific Assessment Rules
case Study
 

Literature:
Core Textbooks:

• 
  Koller, T., Goedhart, M., Wessels, D. (2020).
  Valuation: Measuring and Managing the Value of Companies (7th Edition). Wiley Finance.
  


• 
  Damodaran, A. (2018). The Dark Side of Valuation: Valuing Young, Distressed, and Complex Businesses (3rd Edition). Pearson FT Press.
  


• 
  Berk, J., DeMarzo, P. (2020). Corporate Finance (5th Global Edition). Pearson.
  

 

Additional Recommended Reading:

• 
  Bodie, Z., Kane, A., Marcus, A. (2022).
  Investments (12th Edition). McGraw-Hill.
  


• 
  Lundholm, R., Sloan, R. (2019). Equity Valuation and Analysis (4th Edition). McGraw-Hill/Irwin.
  


• 
  Pinto, J. E., Henry, E., Robinson, T. R., Stowe, J. D. (2015). Equity Asset Valuation (CFA Institute Investment Series, 3rd Edition). Wiley.
  


• 
  CFA Institute (Annual). CFA Program Curriculum (Equity Investments Corporate Finance volumes) – for the latest approaches and case studies in valuation.
  

 

Online Resources and Data:

• 
  Aswath Damodaran’s website (NYU Stern): Regularly updated datasets, valuation spreadsheets, and lecture notes on intrinsic and relative valuation.
  


• 
  CFA Institute’s online articles and research briefs on equity valuation and corporate finance.
  


• 
  Financial data and analytics platforms such as Bloomberg, FactSet, PitchBook, and SP Capital IQ for real-time valuation metrics, comparables, and market data.
  

• Course title: 2.E2.Corporate Finance
• Number of ECTS: 5
• Course code: MScFE-45
• Module(s): Module 2.E: Special Topics in Finance and Economics – Electives I
• Language: EN
• Mandatory: No

Study the theoretical concepts of capital budgeting and valuation
Learn how to solve problems and to apply the theoretical concepts to real world data
Learn to value the equity and debt investments in existing corporations

Return and risk
Capital asset pricing model
Cost of equity and cost of capital
Efficient market hypothesis, behavioral finance & beauty contest
Financial structure of the corporate firm
Limits to the use of debt, financial distress
Leverage and valuation – flow to equity – flow to the firm – adjusted present value
Introduction to financial options and pricing of real options
Topics: M&A, Corporate governance, short-term finance, etc.
The course introduces students to corporate finance. It builds on the capital asset pricing model. Systematic and unsystematic risks of assets are discussed in the contexts of the capital market line and the security market line. Making use of the Modigliani and Miller theorem of optimal capital structure with and without taxes, students learn how to value bonds, stocks and projects applying three different discounted cash-flow approaches.
We discuss the flow-to-equity approach, the APV approach, and the WACC approach. Furthermore, the course introduces to relative valuation and option valuation. Financial issues will be discussed that impact the business organisation including financing, capital budgeting, dividend payouts, capital structure, agency issues, financial and business risk. Throughout the course, the theoretical concepts are illustrated through textbook problems and real-world applications. We set-up and apply financial spreadsheets to data gathered in real-time from internet sources.

Assessment Modality
End-of-course assessment
Assessment Tasks
Type of Assessment
Grading Scheme
Weight for final Grade
Task
Written exam
 
0-20
100 %
Specific Assessment Rules
2h
 

Literature:

The course will be based on the following tex books:
Corporate Finance by Ross / Westerfield / Jaffe / Jordan
Corporate Finance by Berk / DeMarzo
Corportate Finance – A Focused Approach Erhardt / Brigham
Investment Valuation by Damodaran
Additional reading will be provided during the course.

• Course title: 2.E3.Derivatives
• Number of ECTS: 5
• Course code: MScFE-46
• Module(s): Module 2.E: Special Topics in Finance and Economics – Electives I
• Language: EN
• Mandatory: No

Demonstrate a working knowledge of the principles of financial derivatives
Understand how derivative markets work
Interpret the particular role of over-the-counter markets
Apply concepts of no-arbitrage and risk neutral valuation
Determine prices of derivatives like futures and options
Understand how particular risk exposures can be hedged
Deal with the ‘greeks’ of an option portfolio
Understand option strategies
Define the risk profile of a commodity-based strategy, recommend on risk-mitigation tactics (hedging) using various paper hedging techniques

Over the last decades, firms have been increasingly challenged by financial price risks due to unpredictable movements in stock prices, exchange rates, interest rates and commodity prices. The financial markets have responded by continuously developing a range of financial instruments, called derivatives.
By the end of the course, you will have a good knowledge of how these contracts work, how they are used for hedging using real-life experience, and how they are priced.

Assessment Modality
End-of-course assessment
Assessment Tasks
Type of Assessment
Grading Scheme
 
Task
Written exam
 
0-20
 
Specific Assessment Rules
2h
The final written examination will constitute the final grade of the course. Students are allowed to use a non-programmable calculator as well as one-page A4 with formulas.
 

Literature:

For example:
Hull, John: Fundamentals of Futures and Options Markets, Pearson/Prentice-Hall or similar introductory derivatives textbook

• Course title: 2.E4.Financial Stability : Theory & Practice
• Number of ECTS: 5
• Course code: MScFE-47
• Module(s): Module 2.E: Special Topics in Finance and Economics – Electives I
• Language: EN
• Mandatory: No

 

This course will empower students with a strong foundation in financial stability, emphasizing its pivotal role within the economy. The topics explored in this course hold significant relevance for various career paths in finance, including wealth management, banking, corporate finance, and consulting. Furthermore, this knowledge is valuable even for students not pursuing finance careers, as it equips them to develop informed perspectives on the intricacies of the financial system.

This course gives an analysis of the financial system, its sources of instability, and the common approaches for reducing this instability.
The first part of the course provides an overview of the financial system. It highlights its key functions and explains why it has a complex structure (e.g., heavy regulation, complex contracts).
The second part of the course describes the traditional banking and shadow banking sectors and explain why both sectors are subject to financial instability. It then explains why financial instability can lead to crises with severe consequences on economic activity. Finally, it provides an overview of the role played by regulation and central bank in limiting the consequences of financial instability.
The third part of the course focuses on the recent advances for improving financial stability. It begins with an analysis of the 2008 crisis—an event that triggered a deep thinking about financial stability. It then discusses how to improve financial stability by managing systemic risk and sharpening financial regulation.
Outline of the Course
Part I: Financial System and Systemic Risk
A. Functions of the Financial System
B. Structure of the Financial System
C. Systemic Risk
Part II: Banking Sector
A. Commercial Banks
B. Universal Banks
C. Shadow BanksPart III: Stabilization of the Financial System
A. Government Intervention
B. Central Bank InterventionPart IV: Post 2008 Evolution and Current Issues
A. Regulatory Response
B. Pros and Cons of the Regulatory Response
C. Measuring and Taxing Systemic Risk

Assessment Modality
Choose an item.
Assessment Tasks
Type of Assessment
Grading Scheme
Weight for final Grade
Task 1
Written exam
 
0-20
70%
Specific Assessment Rules
 
 
Task 2
Active participation
 
0-20
10%
Specific Assessment Rules
 
 
Task 3
Presentation
 
0-20
20%
Specific Assessment Rules
 
 
Specific Retake Modality (if applicable)
Click or tap here to enter text.

 

Literature:

The course is based on class lectures and problem sets.
There is no mandatory book to read for this course.
 

• Course title: 2.E5.Economie monétaire internationale (Fr)
• Number of ECTS: 5
• Course code: MScFE-48
• Module(s): Module 2.E: Special Topics in Finance and Economics – Electives I
• Language: FR
• Mandatory: No

Mobiliser les principaux outils macroéconomiques permettant d’analyser les interdépendances financières internationales
Expliquer les principaux déterminants de l’évolution des taux de change
Analyser les contraintes de différents régimes de change
Comprendre les principaux mécanismes des crises de change

Le cours traite des thèmes suivants : 1. Analyse économique des régimes de change 2. Détermination du taux de change réel par les échanges de biens et services (règle de parité de pouvoir d’achat ; Effet Balassa–Samuelson ; taux de change réel dans un modèle d’économie dépendante à trois biens ; taux de change d’équilibre)  3. Interdépendances financières internationales (Règle de parité de taux d’intérêt et mesure de l’intégration financière internationale ; modèle de change fondé sur le choix de portefeuille ; Overshooting) 4. Modélisations et enseignements des crises de change

Modalité d’évaluation
Sélectionnez un élément.
Tâches d’évaluation
Type d’évaluation
Système de notation
Pondération de la note finale
Tâche 1
Autre, veuillez préciser
0-20
70%
Règles particulières d’évaluation
Travail écrit
 
Tâche 2
Présentation
0-20
30%
Règles particulières d’évaluation
Présentation des cas
 

Literature:

Bénassy-Quéré Agnès, Economie monétaire internationale, 2e éd 2015
Copeland Laurence, Exchange Rates and International Finance, Pearson, 2014
Bénassy-Quéré A., Coeuré B., Jacquet P., Pisani-Ferry J., Economic Policy: Theory and Practice, Chap 5

• Course title: 2.E6.Monetary Policy
• Number of ECTS: 5
• Course code: MScFE-49
• Module(s): Module 2.E: Special Topics in Finance and Economics – Electives I
• Language: EN
• Mandatory: No

Get a clear understanding of the before and after crisis monetary policy stance of notably the ECB and the FED and of the theoretical underpinnings of the latter

Students are introduced to key theoretical and empirical considerations concerning monetary theory and monetary policy.

Assessment Modality
End-of-course assessment
Assessment Tasks
Type of Assessment
Grading Scheme
Weight for final Grade
Task
Oral exam
 
0-20
100 %
Specific Assessment Rules
N/A
 
 
 

Literature:

Allen Blinder, After the Music Stopped, The Financial Crisis, the Response and the Work Ahead, Penguin Books, 2013.
Papadia and Valimaki central banking in turbulent times ecb and fed public documents

• Course title: 2.E7.Contemporary Issues in Public Finance
• Number of ECTS: 5
• Course code: MScFE-50
• Module(s): Module 2.E: Special Topics in Finance and Economics – Electives I
• Language: EN
• Mandatory: No

Understand the nature of public finance and the role of public sector
Understand the decision making process of public officials
Understand organization, decentralization and competition of public funding and institutions
Evaluate tax incidence, evasion and tax structure
Understand public pension funding issues
Understand public role in correcting global externalities (carbon emissions)
Get knowledge of academic literature in Public Finance and Public Economics
Develop an independent research
Acquire writing skills
Present research results orally
 

This course covers economic studies of contemporary issues in public finance issues. The economic understanding of public finance issues is essential in modern economies where at least a third of economic activities relate to government and public institutions. In many circumstances, experts in Economics and Finance are asked to advise federal and local government officials on the public finance of health, education, justice, infrastructure, scientific research, justice, economic development, etc. Experts also counsel about the economic and financial impact of government intervention in private markets like agriculture, housing, space, etc.  
The focus of the course is on application of analytical tools to key policy issues relating to the spending, taxing and financing activities of government. The course gives students an appreciation of the analytical methods in economics for the study of the public sector and the role of the state in principle and in practice. It provides a thorough grounding in the principles underlying the role of the state, the design of social insurance and the welfare state, the design of the tax system, the scope of the government, etc. The objective is to enable students to understand the practical problems involved in implementing the principles of public finance.
The course aims at covering topics like public sector statistics, theories of public finance, tax evasion, tax incidence, tax competition, government decentralization, financing social security and pension, carbon emission and externality management, privatisation and outsourcing, etc.
The course also aims at training students to formulate questions and solutions for specific issues in public finance and public intervention. Students are asked to develop their skills to organise and develop a short policy research on a specific public finance question. Students shall acquire or improve their writing and presentation skills.

 

Assessment Modality
Combined or continuous assessment
Assessment Tasks
Type of Assessment
Grading Scheme
Weight for final Grade
Task 1
Other, please specify
 
0-20
50 %
Specific Assessment Rules
Seminar Paper
 
Task 2
Presentation
 
0-20
30 %
Specific Assessment Rules
N/A
 
Task 3
Other, please specify
 
0-20
20 %
Specific Assessment Rules
Class and tutorial participation
 

Literature:

Main readings:
Intermediate Public Economics (2013), Hindrickx J. and Myles G.D., Cambridge press
Public Finance and Public Policy (2019), Jonathan Gruber, MacMillan
Economics of the Public Sector (2015), Stiglitz and Rosengard, W. W. Norton Company
Journals: International Tax and Public Finance, Journal of Public Economics, etc.

• Course title: 2.E8.Economics of Innovation
• Number of ECTS: 5
• Course code: MScFE-57
• Module(s): Module 2.E: Special Topics in Finance and Economics – Electives I
• Language: EN
• Mandatory: No

Understand and analyse general and topical issues related to innovation and its implications for firms and the economy
Have acquired the terminology for a sophisticated discussion of innovation topics
Gain a theoretical and empirical toolbox to independently analyse topics in innovation
Make sense of recent developments such as artificial intelligence as an innovation
Analyse the implications for firms
Analyse topical innovation issues empirically

Ideas, innovation and technical inventions have become the most important resource in today’s developed economies. Innovation is an important driver of growth and wealth of nations. From the firms’ perspective, innovation has become widely recognised as a key source of competitive advantage for businesses of all sizes. Innovation is, however, uncertain, costly and the returns are difficult to appropriate. This course provides students with a comprehensive understanding of the main theoretical and empirical concepts of the economic analysis of innovation.

Assessment Modality
Combined or continuous assessment
Assessment Tasks
Type of Assessment
Grading Scheme
Weight for final Grade
Task 1
Written exam
 
0-20
70 %
Specific Assessment Rules
2h
 
Task 2
Take-home exam
 
0-20
30 %
Specific Assessment Rules
Empirical
 

Literature:

Hall and Helmers (2023), Innovation and Intellectual Property, selected chapters; Greenhalgh and Rogers (2010), Innovation, Intellectual Property and Growth, selected chapters; selected articles

• Course title: 2.E9.Public Policy Analysis
• Number of ECTS: 5
• Course code: MScFE-55
• Module(s): Module 2.E: Special Topics in Finance and Economics – Electives I
• Language: EN
• Mandatory: No

–        Apply practical skills and strategies to policy-related projects
Think critically about the policy process using analytical frameworks and develop a firm understanding of the challenges and politics of public policy
Analyse evidence-based impact evaluations and effective policy communications skills

The course is designed to provide hands-on insights into evidence-based policy advice.
Using selected topics from the field of public policy, students will receive an introduction to assessing the available policy-relevant evidence in the academic literature.
Each topic is complemented by a critical assessment of limitations to implementation posed by conflicting interests of constituents, policymakers, and affected interest groups.
The course is designed to enable students to reflect critically on the role of evidence-based policy advice. Examples are to be taken from active labor market policies, welfare policies, housing policies, financial education, development policies, climate policies and the like.

Assessment Modality
End-of-course assessment
Assessment Tasks
Type of Assessment
Grading Scheme
Weight for final Grade
Task
Take-home exam
 
0-20
100 %
Specific Assessment Rules
N/A
 
 
 

Literature:

Altmann, S.; Grunewald, A.; Radbruch, J. (2021): Interventions and Cognitive Spillovers. Review of Economic Studies
Card, D.; Kluve, J.; Weber A. (2010): Active Labor Market Policy Evaluations – A Meta-Analysis. The Economic Journal, 120,
F452–F477. Doi: 10.1111/j.1468-0297.2010.02387.x
Card, D.; Krueger, A. (1994): Minimum Wages and Employment – A Case Study for the Fast Food Industry in New Jersey and Pennsylvania.
American Economic Review, 84, 4, 772-793
Chang A.C.; Li, P. (2017): A Preanalysis Plan to Replicate Sixty Economics Research Papers That Worked Half of the Time.
American Economic Review, 107, 5, 60-64. DOI: https://doi.org/10.1257/aer.p20171034
Cochrane Handbook for Systematic Reviews of Interventions. (training.cochrane.org/handbook/current)
Fernandes, D.; Lynch, J.G.; Netemeyer, R.G. (2014): Financial Literacy, Financial Education, and Downstream Financial Behaviors. Management Science, 60, 8; 1861-1883. Doi: https://doi.org/10.1287/mnsc.2013.1849
Gough, D.; Thomas, J.; Oliver, S. (2012): Clarifying differences between review designs and methods. Systematic Reviews, 1, 28; https://doi.org/10.1186/2046-4053-1-28
Hamermesh D.S. (2017): Replication in Labor Economics: Evidence from Data, and What It Suggests. American Economic Review, 107(5), 37-40
Herndon T., Ash M., Pollin R. (2014): Does high public debt consistently stifle economic growth? A critique of Reinhart and Rogoff. Cambridge Journal of Economics, 38 (2), 257–279
Neumark, D.; Wascher W. (2007): Minimum Wages and Employment. Foundations and Trends in Microeconomics, 2007, 3 (1+2),
1-182
Reinhart C.M., Rogoff K.S. (2010): Growth in a time of debt. American Economic Review, 100(2), 573-578
Rosling H., Rosling O., Rosling-Rönnlund A. (2018): Factfulness. London
Schneider H. (2017): Universal Basic Income – Empty Dreams of Paradise. Intereconomics, 52(2), 83-87

• Course title: 2.O1.Bloomberg
• Number of ECTS: 1
• Course code: MScFE-52
• Module(s): Module 2.O: Data Platforms (extra curriculum)
• Language: EN
• Mandatory: No

 

Use Bloomberg for their research, investments or future jobs
Demonstrate an awareness of the functioning of financial markets and various types of risks faced by financial services firms (e.g. FX risk, credit risk)
Gain hands-on experience with the Bloomberg Terminal
Develop practical skills required in the financial industry and knowledge of the Bloomberg Terminal enhances CVs of students placing them abreast of the job market competition as graduates who are both intellectually and technically savvy
Grasp complex concepts in a straightforward way using industry-proven analytical tools
Understand financial markets and the global economy
Identify the causality in market events using a popular platform and to interpret them
Analyse financial markets

The introductory course to Bloomberg is a self-learning, interactive module that introduces the Bloomberg Terminal to students.
The course consists of concrete examples of using Bloomberg taken from the financial industry and case studies involving the use of the Bloomberg data, Bloomberg news and Bloomberg analytics.
The content of the course is focused, among other items related to the professional use of Bloomberg, on the practical use of this platform to explore:
historical data extracts for financial collateral haircut calculations and use of fund benchmarks and equity relative indices
some important issues about interest rates
topics of bond total return, various measures of bond return, and the leading factors of return change; basic idea of the meanings of interest rate swap, the swap pricing methods and the corresponding Bloomberg functions
issues concerning carry trade and interest rate parity
aspects of credit rating and using agency ratings for Probability of Default models in credit risk
important aspects of equity trading with Fundamental and Technical Analysis, as well as the use of Bloomberg news
Business Analysis of specific industries from investment and loan granting standpoint

 

Assessment Modality
Combined of continuous assessment
Assessment Tasks
Type of Assessment
Grading Scheme
Weight for final Grade
Task 1
Attendance
 
0-20
10 %
Specific Assessment Rules
N/A
 
Task 2
Take-home exam
 
0-20
90 %
Specific Assessment Rules
N/A
 

 

Literature:

ScScott, R. H. (2010). Bloomberg 101. Journal of Financial Education, 36(1/2), 80–88 http://www.jstor.org/stable/41948636