• Course title: 3.SFT1. Principles of Sustainable Finance
• Number of ECTS: 5
• Course code: MSFE_2_SUSTFIN-1
• Module(s): Module 3.SFT: Specialisation -Sustainable Finance Track
• Language: EN
• Mandatory: Yes

On completion of the course unit successful students will be able to: •Explain and apply the concepts of negative externalities, incentive problems and the contractual solutions to these problems.•Apply the main models used to assess the costs and benefits of climate mitigation policies and discuss the key financial parameters in these models.•Discuss how the investments required for the transition to a sustainable economy are likely to affect financial markets.•Evaluate the implications of climate change for the financial decisions of households.

The objective of the course is to provide students with the theoretical and empirical foundations of sustainable finance. The course is divided into three parts. The first part revisits the main models of corporate valuation and financing to account for ESG performance. We first introduce the energy and carbon statements of the firm. We then cover recent models of firm valuation with externalities. Key topics include corporate emissions accounting, emissions trading and asset prices, and the insurance value of abatement. Additionally, the segment delves into sustainable investing in equilibrium and explores the evidence on the green premium, ensuring a robust understanding of how carbon pricing influences stock prices and the broader market.The second part of the course focuses on climate change economics, exploring the welfare impacts, externalities, and policy interventions. It covers basic climate change economic theories, the role of discount rates, and integrated assessment models like the DICE models. This section also addresses the design of climate policies, comparing the efficiency of price-based versus quantity-based regulations. The third part shifts to climate finance, emphasizing empirical research design, physical risks, and the role of ESG ratings in mutual funds and banking. Topics such as the pricing of climate risk insurance, the impact of sea level rise on real estate prices, and the divergence of ESG ratings provide practical insights into how financial markets respond to environmental risks and regulatory measures.

60% written exam30% presentation10% In-class participation

BIBLIOGRAPHY:Bernstein, A., Gustafson, M. T., & Lewis, R. (2019). Disaster on the horizon: The price effect of sea level rise. Journal of Financial Economics, 134(2), 253–272. https://doi.org/https://doi.org/10.1016/j.jfineco.2019.03.013Bolton, P., & Dewatripont, M. (2005). Contract Theory. The MIT Press.Coase, R. H. (1937). The Nature of the Firm. Economica, 4(16), 386–405. https://doi.org/https://doi.org/10.1111/j.1468-0335.1937.tb00002.xCoase, R. H. (1960). The problem of social cost. Journal of Law and Economics, 87–137.Giglio, S., Maggiori, M., Stroebel, J., & Weber, A. (2020). Climate change and long-run discount rates: Evidence from real estate. National Bureau of Economic Research.Giglio, S., Maggiori, M., & Stroebel, J. (2014). Very Long-Run Discount Rates. The Quarterly Journal of Economics, 130(1), 1–53. https://doi.org/10.1093/qje/qju036Goldsmith-Pinkham, P. S., Gustafson, M., Lewis, R., & Schwert, M. (2019). Sea Level Rise and Municipal Bond Yields. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3478364Gopinath, G., Kalemli-Özcan, Ş., Karabarbounis, L., & Villegas-Sanchez, C. (2017). Capital Allocation and Productivity in South Europe*. The Quarterly Journal of Economics, 132(4), 1915–1967. https://doi.org/10.1093/qje/qjx024Hsieh, C.-T., & Klenow, P. J. (2009). Misallocation and Manufacturing TFP in China and India. The Quarterly Journal of Economics, 124(4), 1403–1448. https://doi.org/10.1162/qjec.2009.124.4.1403Issler, P., Stanton, R., Vergara-Alert, C., & Wallace, N. (2019). Mortgage markets with climate-change risk: Evidence from wildfires in california. Available at SSRN 3511843.Stern, N. (2007). The economics of climate change: the Stern review. Cambridge University press.

• Course title: 3.SFT2.Frameworks and Tools
• Number of ECTS: 7
• Course code: MSFE_2_SUSTFIN-2
• Module(s): Module 3.SFT: Specialisation -Sustainable Finance Track
• Language: EN
• Mandatory: Yes

On completion of the course unit successful students will be able to: Understand the main challenges in sustainable finance, in particular socially responsible investing, both from a sustainability as well as a finance perspectiveUse common techniques to incorporate sustainability in investment decisionsUnderstand specific financial instruments that focus on socially responsible investing and that allow investors to manage ESG-related risksMaster important theories that explain how sustainability and finance interact and how they affect financial market pricing and asset pricing theoriesAssess whether specific tools in socially responsible investing are likely to support the transition to a more sustainable economy or not

Sustainable finance or, more broadly speaking, the role of financial markets and investors in the transition towards a more sustainable economic framework has become a central tenet in finance. It affects all areas of finance including corporate finance, asset management and financial markets. On the demand side are companies as well as governments, municipalities and agencies in need of financing investment projects. Banks and financial markets are major supplier of the means of financing. Institutional investors, asset managers and insurance companies play an important role as they manage large portfolios of equities and bonds. Other involved parties are service providers (such as rating agencies, data providers, etc.), regulators as well as the legal system. In this course, we will focus on the roles and the incentives of these parties involved. We look at the theoretical frameworks from a micro as well as from a macro perspective, the incorporation of the sustainability aspect in investment frameworks and into the tools which are used by participants in financial markets. Importantly, we also need to understand how and why these tools and frameworks actually support a successful implementation of sustainable finance goals, if at all. A central principle in investments is the risk-return tradeoff. An important part of this course will provide a comprehensive assessment of how ESG-dimensions fit into this way of thinking. This includes a careful discussion of ESG-related risks and their impact on investment strategies. It will also feature an honest and economically well-founded discussion of realistic return expectations in the area of SRI.Finally, we need to develop comprehensive, accurate and implementable definitions of how success of socially responsible investment strategies is measured, beyond the standard measurement of financial success, and what the shortcomings of these measures are and how they could be remedied.

70% Written exam20% Presentation10% In-class participation

The literature will be focusing on recent, academic papers.

• Course title: 3.SFT3.Investment Strategy, Implementation and Risk Management
• Number of ECTS: 5
• Course code: MSFE_2_SUSTFIN-3
• Module(s): Module 3.SFT: Specialisation -Sustainable Finance Track
• Language: EN
• Mandatory: Yes

On completion of the course unit successful students will be able to :Understand the different responsible investing strategies from a practical point of viewUnderstand how an asset manager develops a sustainable investment strategy and policy and how the manager may build a portfolio of investments aligned with a particular responsible investing strategy.Understand the types of sustainable financial instruments issued by financial market participants and in which situations such instruments are used, as well as the practical challenges linked to such instruments.Understand how an ESG due diligence questionnaire can be built up and completed based upon data received from an investee companyRecognise and understand the key risk management issues related to ESG elements

In the last couple of years there has been an explosion of financial institutions, asset managers, insurance companies exploring and creating “sustainable” financial solutions, whether these be responsible investment funds, green corporate loans, social bonds or other innovative financial products. Almost every financial market participant is looking into the development of new products to ensure they capture relevant opportunities.  This also means that the challenge of measuring and managing ESG performance (both opportunities and risks) have hit the headlines of specialist financial press and sustainable press alike.  This course:will focus on a combination of industry frameworks used by the financial sector, for example the European sustainable finance regulation package, as well as the more practical elements of sustainable finance, looking at how a sustainable finance strategy is developed, refined, implemented and monitored.  will look at the different strategies adopted when managing assets in accordance with ESG principles (using the spectrum of capital as a basis), as well as how asset managers are conducting their day-to-day operations.  will also cover how ESG due diligence is carried out by investors, analysing questionnaires and templates for ESG assessments.will also look at other market participants including the banking, insurance sectors as well as stock exchanges and how products are developed within those organisations.Students:will look at portfolio construction in line with a chosen responsible investment policy and consider performance of ESG portfolios compared to non-ESG portfolios.  will consider the particular case of the bonds market (green, social, sustainability, SDG bonds) and how this market has developed and how the bond market experience can translate into best practice for other areas of sustainable finance, as well as looking at other sustainable financial instruments. will also look at risk management principles related to ESG including assessing ESG risks, the governance for risk management systems, assessing climate risks (physical, transition, financial), and more generally how the consideration of ESG risks is embedded into risk management.  

50% seminar paper20% presentation10% class participation

BIBLIOGRAPHY:Watch TED Talk: https://www.ted.com/talks/bronwyn_king_you_may_be_accidentally_investing_in_cigarette_companies, delivered by Dr Bronwyn King, June 2017, TedX Sydney, entitled “You may be accidentally investing in cigarette companies”Business Insider Video: “How ESG Metrics Work And Why All Investors Should Care” 7 May 2018, Nuveen https://www.youtube.com/watch?v=4LPRQaG83Ls“Sustainable finance – it’s decision time – From niche product to new business model”, KPMG Luxembourg,https://assets.kpmg/content/dam/kpmg/lu/pdf/sustainable-finance-it-is-decision-time.pdfDirk Schoenmaker and Willem Schramade, Principles of Sustainable Finance, 2018, Oxford University Press, 1st Edition, Oxford, UK (ISBN: 9780198826606) (Textbook) – suggestion only for the momentMatthew W. Sherwood and Julia Pollard, Responsible Investing: An Introduction to Environmental, Social, and Governance Investments, 2019, Routledge, 1st Edition, London, UK (ISBN: 9781138560079) (Textbook) suggestion only for the moment

• Course title: 3.SFT4.Sustainable Corporate Strategy, Creating out-Performance
• Number of ECTS: 6
• Course code: MSFE_2_SUSTFIN-4
• Module(s): Module 3.SFT: Specialisation -Sustainable Finance Track
• Language: EN
• Mandatory: Yes

The course provides participants with knowledge, insights, and experience necessary to be at the cutting edge of sustainable corporate finance and strategy.  It shares the state-of-art in integrating sustainability into corporate decision making, creating a competitive advantage.The course introduces the term sustainability, with a special focus on environmental sustainability, while covering the entire spectrum of ESG (Environment, Social and Governance) considerations. It describes international norms and standards, measurement methods, and looks into their translation in today’s business world.  The aim is to bring participants up to speed about current best practice in terms of sustainable corporate finance and strategy and anticipate tomorrow’s challenges.The course is structured along two main axes.  In the first one, concepts and practices of integrating sustainability into decision making will be elaborated.  Case studies and real-world examples will be presented and studied. Along the second axis, students will present their assignments, which will be decided upon together, on the basis of the material presented and studied in class. The assignments can be prepared, both, in groups or individually.  Class discussion will allow deeper elaboration of, and feedback about the assignment.  

Upon completion, participants should have gained insight into and be able to understand:Sustainability Challenges in Corporate StrategyIntegrating Sustainability into Corporate Financial Decision MakingInternational Principles and StandardsMeasurement FrameworksReporting FrameworksAchieving High Corporate Sustainability RatingsUnderstanding how Sustainability Creates Financial Outperformance

60% seminar paper20% presentation20% In-class participation / based on homework (essentially readings)

BIBLIOGRAPHY:”Corporation 2020, Transforming Business for Tomorrow`s World”P. Sukdev, Islandpress 2012. ISBN 9781610912389″Living Planet Report” 2019WWF,  wwf.panda.org”Corporate Sustainability: First Evidence on Materiality”M. Khan, G. Serafeim, A. YoonHarvard Business School, March 2015″The Implications of Corporate Social Responsibility for Investors”G. Clark, M. ViehsUniversity of Oxford, August 2014″Sustainability Challenges Shaping Competitive Advantages in Technology and Innovation“H. LuciusSpringer Singapore, 2017

• Course title: 3.SFT5.Economics of natural hazard
• Number of ECTS: 2
• Course code: MSFE_2_SUSTFIN-5
• Module(s): Module 3.SFT: Specialisation -Sustainable Finance Track
• Language: EN
• Mandatory: Yes

On completion of the course unit successful students will be able to :Assess the economic impact of disastersEvaluate the efficacy of ex-ante mitigation and ex-post relief policiesUnderstand future challenges that climate change will impose on disaster insuranceDemonstrate a critical awareness of practices and experiences in the field of disaster risk management

  

According to the UN, economic losses from disasters such as earthquakes, tsunamis, tropical storms and floods are estimated to average US$250 to US$300 billion annually and are on a steep increase. In the coming years, the understanding of disaster risks, and the management thereof, will have to be adapted to a world where climate change will drag further and more intensive disasters in its wake. New mechanisms of resilience and ex-ante mitigation have to be developed. This course will cover (some of) the following topics:Metrics of natural hazards and disasterClimate change and disastersMacroeconomic consequences of disastersRisk sharing: disaster risk financing and insuranceDisasters, insurance and reinsuranceModelling rare events using extreme value theoryDisaster funds and economic developmentBig Data and disaster relief and preparednessShort vs long run / direct vs indirect (economic and financial) costs of disastersVulnerability and resilience to disastersPost disaster recovery and reconstruction policies 

100% presentation

BIBLIOGRAPHY:Noy, I. (2016). Tropical storms: The socio-economics of cyclones. Nature Climate Change, 6(4), 343E. Cavallo, S. Galiani, I. Noy and J. Pantano (2013). Catastrophic Natural Disasters and Economic Growth. Review of Economics and Statistics, 95(5), 1549-1561L. Ballesteros, M. Useem. and T. Wry (2017). Masters of Disasters? An Empirical Analysis of How Societies Benefit from Corporate Disaster Aid.Academy of Management, 60(5), 1682-1708

• Course title: 3.E1.Behavioural Finance
• Number of ECTS: 5
• Course code: MScFE_BK-6
• Module(s): Module 3.E: Special Topics in Finance & Economics – Electives II
• Language: EN
• Mandatory: No

On completion of the course unit successful students will be able to :Know anomalies in finance and economics and understand theoretical explanationsKnow the foundations of behavioural finance and behavioural economicsUnderstand human behaviour

 The course: introduces to the literature on the anomalies in financial markets and the theories of behavioral economics and finance. Departing from the standard paradigm in financial economics, expected utility and the capital asset pricing model, we pinpoint anomalies that show up in the data from the real world and the laboratory.includes models of prospect theory, noise trader risks, psychological game theory, bounded rationality that help to understand the divergence between observed behavior and the standard paradigm of financial economics.

Written exam (2 hours)

Literature: Barberis and Thaler 2003. “A survey of behavioral finance.” Handbook of the Economics of Finance, 1, 1053-1128Dhami, Sanjit, 2016, Foundations of behavioral economic analysis. Oxford University PressGigerenzer and Selten (Eds.) 2002. Bounded rationality: The adaptive toolbox. MIT pressHens, Thorsten and Kremena Bachmann, 2009, Behavioral Finance for Private Banking, WileyKahneman and Tversky 1979 “Prospect Theory: An Analysis of Decision under Risk” EconometricaShleifer Andrei, 2001, Inefficient markets – An introduction to behavioral finance. Calderon Lectures in EconomicsThaler 1985 “Mental accounting and consumer choice”. Marketing science, 4(3), 199-214Thaler 1999 “Mental accounting matters”. Journal of Behavioral decision making, 12(3), 183-206Thaler and Johnson 1990 “Gambling with the house money and trying to break even”. Management science 36, 643-660Tversky and Kahneman 1992 “Advances in prospect theory”. Journal of Risk and uncertainty, 5(4), 297-323Further readings will be communicated during the lectures.

• Course title: 3.E2.Household Finance and Real Estate
• Number of ECTS: 5
• Course code: MScFE_BK-7
• Module(s): Module 3.E: Special Topics in Finance & Economics – Electives II
• Language: EN
• Mandatory: No

On completion of the course unit successful students will be able to :Carry out their original empirical work, do the critical reading of pertinent articles related to the question and know how to handle complex survey data.Carry out their original empirical work, do the critical reading of pertinent articles related to the question and know how to handle complex survey data.Critically assess the individual and social benefits of important financial products accessible to consumers.Approach consumer financial markets with more empathy towards potential customers and design better functioning products and markets.Orient themselves in the real world of household financial savings, debt and investments, up to current developments.

The objective of the course is to understand how households use financial instruments to attain their objectives. We first review the empirical facts on household wealth and inequality as well as the underlying rational and behavioral aspects of consumer financial decision making. We study current household financial products and the competitive landscape in credit, investment, and advising markets. We also cover consumer financial product innovations and the regulation of household finance, and provides an overview of recent research on real estate markets. The course includes a group project, where students will apply the concepts seen in class and make a presentation. We introduce various data sources on household finance, their advantages and disadvantages. We guide students in how to prepare their dataset for their own project in several dimensions (e.g. weighting and imputation) and in how to apply basic estimation techniques on household surveys with a complex sample design.

Oral exam (40%)Presentation (40%)Seminar paper (20%)

A comprehensive reading list of recent academic publications and working papers is available from the instructors.

• Course title: 3.E3.Financial Engineering
• Number of ECTS: 5
• Course code: MScFE_BK-8
• Module(s): Module 3.E: Special Topics in Finance & Economics – Electives II
• Language: EN
• Mandatory: No

On completion of the course unit successful students will be able to :Show proficiency in probability and statistics, calculus, programming and use these tools to model markets and drive decision makingUnderstand risk and analyze financial dataDesign and implement complex financial models that allow financial firms to price and trade securitiesUnderstand the current academic and practitioner literature on financial engineeringGet exposed to some of the most applicable machine learning techniques in finance considering that machine learning and Artificial Intelligence (AI) play a significant role in the creation of models

Understanding risk and analysing data to drive policy and decision making is the name of the game in institutions like i.e. banks, insurance companies, hedge funds, and governments.Financial Engineering is the study of applying math, statistics, computer science, economic theory, and other quantitative methods to analysing and modelling financial markets. Financial engineers work at the intersection between data science and finance. The first financial engineers were Fischer Black, Robert Merton, and Myron Scholes, infamous for their options pricing model known as the Black-Scholes Model. This model won the Nobel prize in economics and is the foundation for the explosion in derivative markets. 

The final grade of the course will be derived from the grade for participation (25%), the presentation (25%) and the grade for the research paper (50%).

Literature: “Statistics and Data Analysis for Financial Engineering”, 2nd edition by David Ruppert and David S. Matteson, Springer, ISBN 978-1-4939-2614-5 (eBook) Research papers

• Course title: 3.E4.Professional seminars
• Number of ECTS: 5
• Course code: MScFE_BK-9
• Module(s): Module 3.E: Special Topics in Finance & Economics – Electives II
• Language: EN
• Mandatory: No

Fund Channel SA (professor: Olivier MARCY): In full autonomy, be able to select the reliable information sources, to analyze the information accuracy. Get the right information at the right moment, it is key and critical in finance.Alternative liquid investments (professor: Edoardo ANCORA): At the end of the course the students will have a complete overview of the valuation techniques applied in Luxembourg for private equity, real estate and private debt. The students will be able to become familiar with the practical aspects to perform and assess a valuation of an alternative and illiquid investment.Let’s set up an asset management business (professor: Nicolas DELDIME): Understand the strategic concerns of entrepreneurs who move to Luxembourg to do asset management. Have a holistic understanding of a regulated organizational model.

BCEE (professors: Yves BODSON, Philippe HENNES, Yves DOMINICY)Risk Management: The first part of the lecture is an introduction to risk management answering the questions what risk is and what is risk management. The different types of risk in a bank will be introduced, as well as the Banking Union and the three lines of defense. In the second part of the lecture, we will concentrate on the credit risk, and we will be talking about credit scoring models.Asset Classes and securitization: Presentation of the primary financial asset classes (key legal and economical definitions, interaction between economic and financial cycles, valuation criteria applicable to fixed income instruments and to equities, risk categories and key measurement tools) and of the securitization market (key concepts with references to the primary financial asset classes and evolving legal and economic landscape)Corporate Banking: The presentation will address the management of the bank’s commercial relationship with corporate/professional clients, with the main theme of business financing.Fund Channel SA (professor: Olivier MARCY)Information Hierarchy (Duality between, media objectives and public targeted, versus, financial resources)Part I:Brief history of the messages and the information channels and approach of the Media theoriesNews-papers – Information hierarchyPart II:Impact of the digitalizationWeb platforms and social media – information hierarchySocial Media information hierarchy – (student presentations – 2/4 per groups) Alternative liquid investments (professor: Edoardo ANCORA)In a time of low-interest, low inflation and high turbulence in Stock Exchanges, investment managers are engaged in the hunt of higher yields like never before, starting to explore the alternative and illiquid investment space. In this context, a key skill required is the capability to properly value alternative and illiquid assets. During the course we will explore the main alternative investments (private equity, real estate, and private debt) and the typical valuation techniques applied by investment managers in Luxembourg. Let’s set up an asset management business (professor: Nicolas DELDIME)1. Asset management is a regulated profession. What does it mean to practice a regulated profession?2. Build an organizational model (governance, staffing, insourcing / outsourcing, different stakeholders)3. Build a business plan4. Review of a practical case

BCEE (professors: Yves BODSON, Philippe HENNES, Yves DOMINICY): 3 hours written examFund Channel SA (professor: Olivier MARCY): 20mn presentation during course periodAlternative liquid investments (professor: Edoardo ANCORA) :1 hour written examLet’s set up an asset management business (professor: Nicolas DELDIME): 1 hour written examThe final grade is the aggregation of the 4 exams’ grade (weighted / Teaching Units)

LiteratureInformation Hierarchy – Fund Channel SA (professor: Olivier MARCY):Digital Platforms :Fundchannel.comBloomberg.comMorningstar.comFundinfo.comFundsquare.netSwissFundData.chsix-group.comBooks :Media et Société (Francis Balle – Montchrestien – 7ème Edition – 2019)Culture Numérique (Dominque Cardon – Les presses de Sciences Po, Coll. « Les petites humanités » 2019)Histoire des Médias (Jacques Attali Fayard – 2021)Deux Mille Mots pour dire le Monde ( Henriette Walter – Bouquins – 2021)Histoire politique de la roue (Raphaël Meltz – Librairie Vuibert – 2020)Histoire de la Rue de l’Antiquité à nos Jours ( Danielle Tartakowsky – Tallandier 2022)Les Algorithmes font la loi (Aurélie Jean – Livre de poche – 2023)Histoire Mondiale des Impôts de l’Antiquité à nos jours (Eric Anceau, Jean-Luc Bordon Passés / Composés – 2023)No Crypto ( Nastasia Hadjadji – 2023)Technopolitique (Asma Mhalla – Seuil – 2024)Newspapers & MultiMedia Platforms :Financial Times (UK & World Wide)The New YorkerBBCThe EconomistSouth China Morning PostJeune AfriqueLes Echos (FR)L’Echo & De Tijd (BE)Handelsblatt  (DE)Beaux Arts Magazine (FR)Le courrier InternationalLet’s set up an asset management business (professor: Nicolas DELDIME):Circular Commission de Surveillance du Secteur Financier 18/698

• Course title: 3.E5 Financial Econometrics
• Number of ECTS: 5
• Course code: MScFE_BK-22
• Module(s): Module 3.E: Special Topics in Finance & Economics – Electives II
• Language: EN
• Mandatory: No

Upon successful completion of this course students will be able to:Model the time varying conditional variance of time series dataApply state-of-the-art risk measurement and risk management techniquesAssess the performance of the econometric models in describing the time varying VaRCritically appraise risk management systems

 

Part 1 – BackgroundRisk Management and Financial ReturnsHistorical Simulations, Value-at-Risk and Expected ShortfallA Primer on Financial Time Series Analysis Part 2 – Univariate Risk ModelsVolatility Modeling Using Daily DataVolatility Modeling Using Intraday DataNonnormal Distributions Part 3 – Multivariate Risk ModelsCovariance and Correlation ModelsSimulating the Term Structure of RiskDistributions and Copulas for Integrated Risk Management Part 4 – Backtesting and Stress Testing

100% written exam

The reference books for this course are:Elements of Financial Risk Management, Elsevier, ed. 2, Peter F. Christoffersen, 2012Risk Management and Financial Institutions, Wiley, ed. 3, John Hull, 2012 (optional)Financial Risk Manager Handbook, Wiley, ed. 5, Philippe Jorion, 2009 (optional)

• Course title: 4.E1.Design Execution and Evaluation of Research in Finance and Economics
• Number of ECTS: 5
• Course code: MScFE_BK-12
• Module(s): Module 4.E Special Topics in Finance and Economics – Electives III
• Language: EN
• Mandatory: No

On completion of the course unit successful students will be able to:Execute an academic research project: identify a research question, position it in the context of current literature, formulate hypotheses and apply appropriate methodology to test them, present results and discuss the implications of the analyses that have been carried out; critically assess academic research and the work of peers.The course is intended to equip students with the necessary knowledge and tools to carry out independent research and prepare them for the master thesis – either academic or the research section of the applied thesis.

The course aims at developing and strengthening students’ academic skills in identifying and analyzing research questions, applying research methods in finance and economics to approach these questions, and interpreting results relative to the current state of the art.The course is centered around a set of research projects in Finance and Economics that students carry out in small research teams. Each team focuses on an individual research project and carries it out along all its stages, from identifying a research question and motivating its relevance to choosing appropriate methodology to address it, executing the analysis, and presenting and interpreting the results.The course is structured as follows:1. Introductory session on a selected set of research topics, providing guidance on identifying each respective research question, on the appropriate research methodology and empirical strategy, the respective data to use for the empirical analysis, and related literature.2. Execution stage during which research teams plan and conduct their chosen research projects.3. Student presentation sessions at each stage of the execution of the research projects:3.1.     Research idea/question, motivation behind it and current state of the art.3.2.     Research methodology, empirical setup, development of hypotheses, overview of the data needed to address the research question.Execution and analysis of results, potential further areas of inquiry, conclusion.

60% Seminar paper30% Presentation10% Discussion

Academic articles that represent the key references for the set of research projects distributed ahead of the course.

• Course title: 4.E2 Testing of Economic Model – Sports Data
• Number of ECTS: 5
• Course code: MScFE_BK-15
• Module(s): Module 4.E Special Topics in Finance and Economics – Electives III
• Language: EN
• Mandatory: No

On completion of the course unit successful students will be able to:Formulate research questions.Use regulation/rules as a source of exogenous variation to estimate (economic) models.Test economic theory using sports data.Analyze sports data using economics principles.

Nowadays, a wealth of precise data is being collected about performances in sports. While statistical methods are designed to “summarize” the information contained in performance data, these methods do not properly take into account the fact that performances in sports are the result of rational agents (athletes, teams, coaches,…etc.) taking decisions under a set of incentives (rewards, prize money, payoffs) and constraints (rules of the game).This course introduces and applies the economic approach to human behavior on performance data. The course shows how this approach can provide not only deep insights into the analysis of performance in sports but also robust tests for economic models. Indeed, since by the very nature of sports, athletes perform in a “controlled” environment, (changes in) the “rules of the game” offer unique opportunities, natural experiments, to test predictions of economic models.The course provides a set of examples that are used as an illustration of the method. These examples relate to the following questions:Why do goalkeepers not always choose to jump to the same side at penalty kicks? Why did performance inequality increase so much in the last 5 decades in the peloton of the Tour de France?Why did the gender performance gap in triple jump, pole vault and marathon followed a S-shape evolution over a period of 25 years plateauing thereafter? Why do some tennis players and sumo wrestlers cheat?

2 hours written exam during the course period

PALACIOS-HUERTE, (2014), BEAUTIFUL GAME THEORY: HOW SOCCER CAN HELP ECONOMICS, PRINCETON UNIVERSITY PRESS.CANDELON, B. AND DUPUY, A. (2015): HIERARCHICAL ORGANIZATION AND PERFORMANCE INEQUALITY: EVIDENCE FROM PROFESSIONAL CYCLING, THEINTERNATIONAL ECONOMIC REVIEW, VOL. 56 (4), PP. 1207-1236.DUPUY, A. (2012): AN ECONOMIC MODEL OF THE EVOLUTION OF THE GENDER PERFORMANCE RATIO IN INDIVIDUAL SPORTS. THE INTERNATIONAL JOURNAL OF PERFORMANCE ANALYSIS IN SPORT, VOL. 12 (1), PP. 224-245.JETTER, M. AND WALKER, J. (2017): GOOD GIRL, BAD BOY: CORRUPT BEHAVIOR IN PROFESSIONAL TENNIS, SOUTHERN ECONOMIC JOURNAL, 2017, 84(1): 155-180DUGGAN, MARK, AND STEVEN D. LEVITT. (2002). “WINNING ISN’T EVERYTHING: CORRUPTION IN SUMO WRESTLING .” AMERICAN ECONOMIC REVIEW, 92 (5): 1594-1605.

• Course title: 4.E3 Statistics in risk management using R – French
• Number of ECTS: 5
• Course code: MScFE_BK-16
• Module(s): Module 4.E Special Topics in Finance and Economics – Electives III
• Language: FR
• Mandatory: No

Objectifs:Savoir manipuler le logiciel R pour des analyses de donnéesComprendre la notion de risque financier et son estimation en utilisant les fonctionnalités du logiciel RSavoir faire une analyse économétrique de séries temporelles en utilisant le logiciel R

Le premier chapitre du cours consiste à apprendre à manipuler le logiciel R, notamment afin d’avoir accès à des données financières et de les analyser. Nous étudierons en particulier comment créer des séries temporelles, utiliser des indicateurs statistiques, faire une analyse technique et graphique à l’aide du logiciel R.  Le deuxième chapitre s’intéresse au concept de risque financier d’un actif et d’un portefeuille d’actifs au travers de la notion de rendement, de volatilité, de calcul d’indicateurs de performance ajustés au risque et d’optimisation de portefeuille. Nous développerons la notion de risque au travers d’indicateurs statistiques tenant compte des risques extrêmes. Dans tous ces chapitres, les séries temporelles sont étudiées en faisant une analyse économétrique des données financières. Les applications qui illustrent le cours sont entièrement menées à partir du logiciel R. Les étudiants doivent avoir téléchargé le logiciel R avant de venir à la première séance du cours en utilisant le lien suivant : https://cran.r-project.org/bin/windows/base/

Examen écrit de 2 heures pendant la période de cours

Bilbiographie :Analyse des séries temporelles, 5e édition, de R. Bourbonnais et V. Terraza, chez Dunod 2022Analyse Statistique pour la gestion bancaire et financière, applications avec R, de V. Terraza et C. Toque, chez De Boeck, 2013Modélisations de la Value at Risk – Une évaluation de l’approche Riskmetrics de V. Terraza Editions Universitaires Européennes – 2010 Le livre de R, apprentissage et référence, de B. Desgraupes, chez Vuibert, 2013Séries temporelles avec R, de Y. Aragon, chez Springer, 2011

• Course title: 4.E4. Incubator Course: Cases of Modern Finance
• Number of ECTS: 5
• Course code: MScFE_BK-26
• Module(s): Module 4.E Special Topics in Finance and Economics – Electives III
• Language: EN
• Mandatory: No

On completion of the module unit successful students will be able to:Have a broader understanding about how emergent financial technologies are changing the standard Financial Architecture and its implications for financial institutionsHave a better understanding of how emergent FinTech developments will change the financial products available

This incubator course aims to Educate students about the disruptive effects of advanced technologies in the financial sector, with a leading focus on asset management, instruments and advanced data analytics.Raise awareness on both the socio-economic and the performance implications of innovation diffusion.Provide both academic and industry-strength underpinning for the future of finance.The incubator course consists of two parts. Each part includes both lectures lectures and practical case work in groups. The practical case works, as well as the lectures are offered by a residing institutional / industry partner of this course. Students are asked to provide solutions to the presented case studies, based on a problem-based discovery. The first block is concentrating on the notion “Financial architecture” in the context of asset management and administration. It discusses the disruptive effects of peer2peer technologies, such as blockchains, through industry-strength case studies. Below, the skeleton of this block is provided as follows:General IntroductionIntroduction to the Financial ArchitectureBusiness Models of BanksBusiness Models of the Asset Management IndustryTrading Platforms and their Market MicrostructureIntroduction to Blockchain Peer-to-peer platformsThe Blockchain Market Microstructure Business Models of FinTech Credit PlatformsRecent developments about Financial Products on Peer-to-peer platformsWorkshop: Liquidity pools and automated market makers (instrumentalising flash swaps and loans)Conclusion: A perspective on the changing Financial Architecture in light of recent technological developments.The second block is concentrating on the notion “advanced data analytics” in the context of asset management and administration. In an ever-changing environment, Investment Banks face many challenges: regulatory compliance, business model review and increased competition. At the same time, the financial sector is witnessing a huge digital transformation, particularly with the advent of new technologies. Artificial intelligence, Distributed Ledger Technology, API and Big data, how can new tools bring solutions to financial institutions?This block would kick-off with a lecture on investment banking. Through its organizational structure and its businesses, themes common to the world of banking and investment will be discussed. Case studies are introduced and discussed in order to propose a digital solution in response to the case problem at hand. Below, the skeleton of this block is provided as follows:A practical application of Performance and Risk management measures in finance Measures of returnThe complexity of defining and measuring riskHow to find the best returns while minimizing the risk (measures of risk-adjusted return and its limitations)?Can we use new technologies and Machine Learning for predicting stock price? How to observe the factors affecting assets?Multifactor Models (Fama French, Carhart four-factor model): a linear approachAn Introduction to Decision trees (and random forest): a nonlinear approachWorkshop #1: Implementation of a basic strategy with alternative data: does ESG (Environmental, Social, and Governance) investment bring better performance?Workshop #2: Compare linear and non-linear approaches in price prediction and understand the limitationsConclusion

The final grade will be an oral presentation (100%)

Literature:Ayadi, R., Cucinelli, D. and De Groen P. (2019) « Banking Business Models Monitor : Europe »Halaburda, H., Haeringer, G., Gans, J. and Gandal, N. (2022) “The Microeconomics of Cryptocurrencies”, Journal of Economic Perspectives forthcoming.   Lehar, A. and Parlour, C. (2021) “Decentralized Exchanges”, SSRN Working Paper.Liberti, J.M. and Petersen, M.A. (2019) “Information: Hard and Soft”, The Review of Corporate Finance Studies, 8(1), 1-41.Valleee, B. and Zheng, Y. (2019) “Marketplace lending: A new banking paradigm?”, The Review of Financial Studies, 32(5), 1939-1982.Verlaine, M. (2020) “Behavioral Finance and the Architecture of the Asset Management Industry”.Stefan Jansen. (2020). Machine Learning for Algorithmic Trading: Predictive models to extract signals from market and alternative data for systematic trading strategies with Python, 2nd Edition.Chloé-Agathe Azencott. (2018). Introduction au Machine Learning.Joachim Häcker, Dietmar Ernst. (2017). Financial Modeling: An Introductory Guide to Excel and VBA Applications in Finance.Jean Dermine. (2009). Bank Valuation and Value-Based Management: Deposit and Loan Pricing, Performance Evaluation, and Risk Management.John C. Hull. (2018). Risk Management and Financial Institutions.

• Course title: 4.E5 Topics in Well-being Research
• Number of ECTS: 5
• Course code: MScFE_BK-28
• Module(s): Module 4.E Special Topics in Finance and Economics – Electives III
• Language: EN
• Mandatory: No

On completion of the course unit successful students will be able to:Analyse different datasets with the STATA softwareHave knowledge of a number of the empirical methods used to tackle theoretical questionsHave acquired advanced interdisciplinary knowledge.

 

In this course, students will learn about the different theoretical and conceptual approaches used in the social sciences to analyze well-being and its determinants. After an introduction to the various methods proposed for the measurement of well-being, we will focus on its determinants and explore the relationship with income (including the Easterlin paradox), social position and mobility, as well as the role of adaptation and expectations. We will then move on to discuss societal well-being and the recent proposals to go beyond GDP as a measure of progress. Last, we will show how measures of individual well-being can be used to shed new light on important economic concepts such as income inequality, gender disparities and policy evaluation.

Seminar Paper (95%)Active participation (5%)

Recommended literature:Balestra, C., Boarini, R. & Ruiz, N. (2018).Going beyond GDP: empirical findings, in: C. D’Ambrosio (ed.), Handbook of Research on Economic and Social Well-Being, chapter 2, pages 52-103, Edward Elgar Publishing.Blanchflower, D. G., & Oswald, A. J. (2004). Well-being over time in Britain and the USA. Journal of Public Economics, 88, 1359-1386.Blanchflower, D. G., & Oswald, A. J. (2008). Is well-being U-shaped over the life cycle? Social Science & Medicine, 66, 1733-1749.Card, D., Mas, A., Moretti, E., & Saez, E. (2012). Inequality at work: The effect of peer salaries on job satisfaction. American Economic Review, 102, 2981-3003.Clark, A. E., & Oswald, A. J. (1996). Satisfaction and comparison income. Journal of Public Economics, 61(3), 359-381.Clark, A. E., Frijters, P., & Shields, M. A. (2008). Relative income, happiness, and utility: An explanation for the Easterlin paradox and other puzzles. Journal of Economic Literature, 46, 95-144.Clark, A. E., & Lepinteur, A. (2019). The causes and consequences of early-adult unemployment: Evidence from cohort data. Journal of Economic Behavior & Organization, 166, 107-124.Clark, A. E. (2018). Four decades of the economics of happiness: Where next? Review of Income and Wealth, 64, 245-269.Di Tella, R., MacCulloch, R. J., & Oswald, A. J. (2001). Preferences over inflation and unemployment: Evidence from surveys of happiness. American Economic Review, 91, 335-341.Easterlin, R. A. (1974). Does economic growth improve the human lot? Some empirical evidence. In Nations and Households in Economic Growth. Academic Press.Flèche, S. (2021). The welfare consequences of centralization: evidence from a quasi-natural experiment in Switzerland. Review of Economics and Statistics, 103, 621-635.Giovannini, E., & Rondinella, T. (2018). Going beyond GDP: theoretical approaches, in: C. D’Ambrosio (ed.), Handbook of Research on Economic and Social Well-Being, chapter 1, pages 1-51, Edward Elgar Publishing.Guio, A.-C. (2018). Multidimensional poverty and material deprivation: empirical findings, in: C. D’Ambrosio (ed.), Handbook of Research on Economic and Social Well-Being, chapter 6, pages 171-193, Edward Elgar Publishing.Layard, R. (2006). Happiness and public policy: A challenge to the profession. Economic Journal, 116, C24-C33.Lepinteur, A. (2019). The shorter workweek and worker wellbeing: Evidence from Portugal and France. Labour Economics, 58, 204-220.Luttmer, E. F. (2005). Neighbors as negatives: Relative earnings and well-being. Quarterly Journal of Economics, 120, 963-1002.Oswald, A. J., Proto, E., & Sgroi, D. (2015). Happiness and productivity. Journal of Labor Economics, 33, 789-822.

• Course title: 4.Applied Master Thesis (including Internship)
• Number of ECTS: 20
• Course code: MScFE_BK-19
• Module(s): Module 4.SFT.Master Thesis
• Language: EN
• Mandatory: No

• Course title: 4.Academic Master Thesis
• Number of ECTS: 20
• Course code: MScFE_BK-20
• Module(s): Module 4.SFT.Master Thesis
• Language: EN
• Mandatory: No