Department of
Economics

Programme and courses

Educational programme

Learning activities

Activities are divided into four terms:

  • First term: October-December (for students who are required to follow Maths and Statistics Pre-Courses, lessons will begin in September)
  • Second term: January-March
  • Third term: April-May
  • Fourth term: May-June

Lessons take place from October to June: Monday to Friday (usually Monday, Tuesday and Wednesday are devoted to frontal lessons; Thursday and Friday may be used for recovery lessons and/or exams). Training activities involve classroom lectures, interactive classes, exercises, seminars, practical training sessions and the preparation of a final paper.

250 hour of internship are also scheduled from June: for the modality and activation visit the dedicated web page: Stage [ITA] / Internships [ENG].

Final diploma is normally expected in December.

Attendance

IMEF is a full-time Master’s Programme: attendance is mandatory. Absences cannot exceed 30% of the entire programme. Only in exceptional cases, absences will be justified if properly supported by documentary evidence.

Language

The course is entirely taught in English.

Where

The programme of the International Master in Economics, Finance and Data Science will be held at the San Giobbe Economics Campus (Cannaregio 873, 30121 Venice) of the Ca' Foscari University of Venice. The Campus hosts also the Department of Economics and the Economics Library [ITA].

IMEF courses

Instructor

  • Elisa Cavezzali

Syllabus

  1. Introduction to Corporate Finance
  2. Financial Statement Analysis & Financial Planning
  3. Single Period Valuation, Multi-Period Discounting
  4. Net Present Value, Payback Period Method, Discounted Payback Period, Average Accounting Method
  5. Internal Rate of Return, Profitability Index, Capital Budgeting
  6. Weighted Average Cost of Capital (WACC)

Instructors

  • Giorgio Calzolari
  • Domenico Sartore

Syllabus

  1. Linear Regression Model
  2. Multiple Equation Models
  3. Dynamic Modelling: Univariate Stochastic Processes
  4. Dynamic Modelling Univariate Linear Model
  5. Applied Econometrics and Empirical Finance

Reading List

  • Greene W. H. (2006), Econometric Analysis, fourth edition, Prentice Hall, Upper Saddle River
  • Chatfield C. (1996), The Analysis of the Time Series: Theory and Practice, Chapman and Hall
  • Gourieroux C. and Monfort A. (1997), Time Series and Dynamic Models, Cambridge University Press
  • Banerjee A., Dolado J. J, Galbraith J. W., Hendry D. F. (1993), Co-integration, Error Correction and the Econometric Analysis of Non-Stationary Data, Oxford University Press, Oxford
  • Hendry D.F. (1995), Dynamic Econometrics, Oxford University Press, Oxford

Instructor

  • Lucia Trevisan

Syllabus

The course aims to provide the required instruments to interpret international macroeconomic and finance scenarios and related changes. A focus on monetary aspects highlights the evolution of Central Banks’ communication language. Based on an operating approach, a qualitative analysis of the data allows learning how to select the scenario’s current key-variables and to interpret the market expectations. The course also considers the macroeconomic interdependence of national economies by analysing the effects of transmission’s mechanism of monetary and fiscal policies between countries.

  1. The Communication Language of the Authorities

    1. The instruments of monetary policy
    2. The market expectations
    3. Central Banks’ opportunities to communicate their monetary policy
    4. Fed and ECB: different behaviour

  2. Macroeconomic Analysis of a Country

    1. Annual data
    2. Quarterly data
    3. Monthly data

  3. Analysis of Current International Scenario

    1. The key variables
    2. The United States
    3. The Euro Area

  4. Macreconomic Interdependence of National Economies

    1. The effect of tight monetary policy
    2. The effect of tight fiscal policy
    3. The effect on the current international scenario

Reading List

  • Material supplied by the Instructor

Instructors 

  • Michele Costola
  • Lorenzo Frattarolo

Syllabus

  1. Introduction to Matlab
  2. Introduction to VBA
  3. Interface with Bloomberg and Datastream

Reading List

  • to be defined

Instructors

  • Diana Barro
  • Martina Nardon
  • Lorenzo Frattarolo
  • Silvia Bozza

Syllabus
Part I - Mathematics

  1. Matrices and linear algebra: vectors, matrices, linear systems, eigenvalues, positive definiteness
  2. Optimization problems with many variables: examples from economics
  3. Unconstrained optima: first and second order conditions
  4. Constrained optima: the Lagrange conditions
  5. Differential equations
  6. Calculus of variations and Eulero equation
  7. Dynamic programming

Reading List

  • Sundaram (1996), A first course in optimization theory, Cambridge University Press
  • Simon C., Blume L. (1994), Mathematics for economists, Norton and Company
  • Seierstad A., Sydsæter K. (1987), Optimal control theory with economic applications, North-Holland
  • Luenberger D. (1987),Investment Science, Oxford University Press.

Part II – Statistics

  1. Probability and distribution theory
  2. Properties of a random sample
  3. Point estimation and interval estimation
  4. Hypothesis testing

Reading List

  • Lecture notes

Instructor

  • Pietro Dindo

Syllabus

  1. Choice among risky prospects. The expected utility hypothesis
  2. Measures of risk aversion. “Paradoxes” in actual decision making
  3. Portfolio selection. Liquidity preference. Demand for insurance
  4. Prices of marketed assets and state prices
  5. Absence of arbitrage opportunity and pricing of derivative securities
  6. Efficiency of complete markets for contingent commodities
  7. Complete financial markets under rational expectations
  8. Pricing in complete financial markets: the consumption based capital asset pricing model (CCAPM)
  9. Allocation of risks
  10. Linear risk tolerance, quadratic utilities in complete markets
  11. Introduction to the capital asset pricing model (CAPM)
  12. Two funds separation theorem

Reading List

  • Hirshleifer, J. and Riley, J. G., The Analytics of Uncertainty and Information, Cambridge Surveys of Economic Literature, CUP, 1992, Part I, pp. 1 – 164.

Instructor

  • Roberto Casarin

Syllabus

  1. Monte Carlo methods
  2. Quasi-Monte Carlo methods
  3. Importance sampling
  4. Accept/Reject methods
  5. Metropolis-Hastings and Gibbs sampling
  6. Stochastic process simulation
  7. Stochastic Differential Equation

Reading List

  • Ripley B.D. (2008), Stochastic Simulation, Wiley
  • Kloden P. E.,  Platen E. (1992) Numerical Solution of Stochastic Differential Equations, Springer
  • Fishman G. (2013), Monte Carlo: concepts, algorithms, and applications, Springer
  • Robert C. and Casella G. (1999), Monte Carlo statistical methods, Springer

Instructor

  • Micheal Donadelli

Syllabus

  1. Consumption-Saving Choices

    • Two-Period Model: Optimization under Certainty
    • Intertemporal Optimization
    • Sequential and Intertemporal Budget Constraint

  2. Risk, Insurance, Market Completeness

    • Insurance and Consumption Smoothing
    • State-Contingent Securities
    • Arrow-Debreu Pricing and Equilibria
    • Full Risk Sharing

  3. Intertemporal Choices under Uncertainty

    • Expected Utility and the EE
    • The C-CAPM
    • CRRA Preference
    • Consumption Dynamics

  4. Asset Pricing Anomalies

    • The Equity Premium Puzzle
    • The Riskfree Rate Puzzle

  5. The Impact of Uncertainty Shocks

    • Vol-Shocks vs. Economic Policy Uncertainty Shock
    • Risk Aversion vs. Ambiguity Aversion?

Reading List

  • Slides and Lecture Notes provided by the instructor at the beginning of the course.

Instructor

  • Martina Nardon

Syllabus

  1. Stochastic processes and Brownian motion
  2. Martingales
  3. Stochastic integrals, stochastic differential equations and Itô Lemma
  4. Financial applications of Itô Lemma

Reading List

  • Mikosch T. (1998), Elementary stochastic calculus

Instructors

  • Stephen Schaefer
  • Teresa Grava

Syllabus

  1. Introduction to derivatives and Arbitrage
  2. Forwards, Swaps and Futures
  3. Fixed income derivatives
  4. Introduction to Options
  5. Trading Strategies Involving Options and Introduction to the Binomial Model
  6. The Black-Scholes Model
  7. Options on Currencies and Futures
  8. The management of Market Risk
  9. Numerical Methods

Reading List

  • Hull J., Options, Futures and Other Derivative Securities, Prentice-Hall
  • Stephen M Schaefer, Asset pricing: derivative assets, International Encyclopaedia of Social and Behavioral Sciences, Economics Section (O. Ashenfelter, Ed.), Princeton University Press.

Instructors

  • Maurizio Murgia
  • Alberto Plazzi

Syllabus

  1. Dividends, taxes and Firm Value
  2. Capital structure and debt policy: Modigliani – Miller theory
  3. Capital structure and debt policy
  4. Corporate risk management

Reading List

  • Copeland, Weston, Shastri (2005), Financial Theory and Corporate Policy, Addison Wesley

Instructors

  • Monica Billio
  • Massimiliano Caporin

Syllabus

  1. Efficient frontier: empirical aspects 
  2. The Capital Asset Pricing Model
  3. The Arbitrage Pricing Theory 
  4. Risk measurement
  5. Tutorial on EViews

Reading List

  • Campbell J., Lo A., and MacKinlay A.C. (1997), Econometrics of Financial Markets, Princeton University Press
  • Franses P.H. and D. van Dijk (2000), Nonlinear Time Series Models in Empirical Finance, Cambridge University Press,
  • Gouriéroux, C. and J. Jasiak (2000), Financial Econometrics, Princeton University Press, Princeton
  • Taylor S.J. (2001), Asset Price Dynamics, Volatility and Prediction, Princeton University Press

Instructor

  • Alina Preger

Syllabus

  1. ALM introduction: repricing gap, NII and EV sensitivities;
  2. Behavioural models (NMD and prepayment);
  3. IRRBB regulation
  4. Liquidity risk management introduction: maturity ladder, CBC, liquidity gaps
  5. Liquidity risk regulation: LCR and NSFR
  6. Liquidity risk regulation: ALMM

Reading List

  • Material supplied by the Instructor

Instructor

  • Michele Trova

Syllabus

  1. Multifactor Asset Pricing Models for Portfolio and Risk Management
  2. The Black-Litterman Model
  3. Market Timing Ability
  4. Robust Asset Allocation
  5. Resampled Efficient Frontier
  6. Portable Alpha Strategies 

Reading List

  • Slides and papers supplied by the Instructor

Instructor

  • Marco Corazza

Syllabus

  1. Introduction to Artificial Intelligence and Machine Learning in finance
  2. Intelligent metaheuristics for complex optimization and applications
  3. Supervised learning and applications
  4. Group Method of Data Handling and applications
  5. Reinforcement Learning and applications
  6. Implementations in Matlab

Reading List

  • O’ Hara M. (1997), Market Microstructure Theory, Blackwell Business
  • Campbell J. Y., Lo A. W., Craig MacKinlay A. (1997), The Econometrics of Financial Markets, Princeton University Press
  • Fantazzini D. (2004), Financial Markets Microstructure and High Frequency Data, Dupress
  • Cherubini U.,  Luciano E., Vecchiato W. (2004), Copula Methods in Finance, Wiley

Instructor

  • Walter Torous

Syllabus

Concepts and techniques for analyzing financial decisions in property development and investment.
Topics:

  • property income streams
  • pro forma analysis
  • equity valuation
  • tax analysis
  • risk
  • financial structuring of real property ownership.

Reading List

  • Slides and papers supplied by the instructor

Instructors

  • Stefano Bragoli
  • Andrea Giacomelli

Syllabus

  1. Definition of risk management process
  2. Sources of risk
  3. Risk measures
  4. The tasks of the risk management process

Reading List

  • Lee A. Y. (1999), CorporateMetricsTM Technical Document, RiskMetrics Group
  • Shimpi P. A. , Durbin D. , Laster D. S. (2001), Integrating Corporate Risk Management, Texere
  • Fusaro P. C. (1998), Energy Risk Management: Hedging Strategies and Instruments for the International Energy Polipovic D. (1997), Energy Risk: Valuing and Managing Energy Derivatives, McGraw-Hill
  • King J. L. (2001), Operational risk: measurement and modelling, Wiley
  • Marshall C. L. (2000), Measuring and Managing Operational Risks in Financial Institutions: Tools, Techniques, and Other Resources, Wiley
  • Doherty, N. A. (2000), Integrated Risk Management: Techniques and Strategies for Reducing Risk, McGraw-Hill
  • Artzner, P., Delbaen, F., Eber, J.-M., Heath, D. (1999) Coherent measures of risk, Math. Fin. 9(3), 203-228.
  • Acerbi C. (2002), Spectral measures of risk: a coherent representation of subjective risk aversion, Journal of Banking & Finance 26, 1505-1518
  • The Basel capital accord and its revisions 

Instructors

  • Andrea Berardi
  • Marcello Pericoli

Syllabus

  1. The basics
  2. Modern term structure theory
  3. Empirical tests of term structure models

Reading List

  • Cairns, A. (2004): Interest rate models: an introduction, Princeton University Press.
  • Rebonato, “Interest rate option models”, Wiley.
  • Hull, “Options, futures, and other derivatives”, Prentice Hall

Instructor

  • Roberto Casarin

Syllabus

  1. Utility Theory
  2. Principles of Premium Calculation
  3. The Collective Risk Model
  4. The Individual Risk Model
  5. Risk process and ruin probability
  6. Introduction to Re-insurance

Reading List

  • Dickson, D. C. M. (2005), Insurance Risk and Ruin, Cambridge University Press.

Instructor

  • Michel Dacorogna

Syllabus

  • The concept of risk, risk measure and the pricing of risk
  • Aggregation of risk and dependencies
  • Concept of capital and management of capital
  • The new Solvency Regulations and the Role of Reinsurance
  • Adding time diversification to risk diversification
  • Entreprise Risk Management (ERM) towards a holistic approach to risk management

Reading List

  • Practical Risk Theory for Actuaries by C.D: Daykin, T. Pentikäinen and M. Pesonen published by Chapman & Hall, second edition 1996 
  • Dynamic Financial Analysis, 2004, in the Encyclopaedia of Actuarial Science, vol.1 pages 505-519, edited by J. Teugels and B. Sundt published by John Wiley & Sons, with Peter Blum. 
  • Managing Bank Capital by Chris Matten, John Wiley, 2000 
  • Modelling Extremal Events for Insurance and Finance by Paul Embrechts, Claudia Klüppelberg and Thomas Mikosch, Springer, 1997 
  • Risk Management by Michel Crouhy, Dan Galai and Robert Mark Mc Graw Hill, 2001 
  • From Principle Based Risk Management to Solvency Requirements, an analytical framework for the Swiss Solvency Test, SCOR book, 20081 
  • Integrating Corporate Risk Management, by Prakash A. Shimpi, David Durbin, David S. Laster, Carolyn P. Helbling and Daniel Helbling, Swiss Re Book, 1999 
  • Reinsurance, Principles and State of the Art, 2nd Edition, contribution book edited by Andreas Schwepcke, Verlag Versicherungswirtschaft, Karlsruhe, 2004 
  • Quantitative Risk Management: Concepts, Techniques, Tools, revised edition by Paul Embrechts, Rudiger Frey and Alexander J. McNeil, Princeton University Press, Princeton, 2015 
  • Actuarial Theory for Dependent Risks: Measures, Orders and Models, by Michel Denuit, Jan Dhaene, Marc Goovaerts and Rob Kaas, John Wiley & Sons, Chichester, 2005 
  • Risk Management for Insurers, Risk Control, Economic Capital and Solvency II, by René Doff, Risk Books, London, 2007 
  • Capital Ideas Evolving, Peter L. Bernstein, John Wiley & Sons, Hoboken NJ, 2007 
  • The Value of Risk, Swiss Re and the History of Reinsurance, H. James, P. Borscheid, D. Gugerky and T. Straumann, Oxford University Press, Oxford, 2013 

Instructors

  • Alain Monfort
  • Yacine Ait-Sahalia
  • Massimiliano Caporin

Syllabus
Part I – Volatility modeling

  1. Stylized facts
  2. Stochastic processes
  3. Statistical modelling of a stochastic process
  4. Univariate ARCH models
  5. Generalisations of univariate ARCH models
  6. Inference in ARCH-GARCH models
  7. Multivariate GARCH models
  8. Hidden Markov Chain models
  9. Discrete factor models
  10. Pricing and dynamic models

Reading List

  • Hamilton J. (1994), Time Series Analysis, Princeton University Press
  • Gouriéroux C. (1997), ARCH Models and Financial Applications”, Springer-Verlag
  • Bertholon H.,  Monfort A. and Pegoraro F. (2008), Econometric Asset Pricing Modelling, Journal of Financial Econometrics, 4, 407-458

Part II – Continuous time econometrics

  1. Continuous‐time calculus
  2. Arbitrage and risk‐neutral pricing
  3. Classical interest‐rate models
  4. Multifactor interest‐rate models
  5. Credit risk and default
  6. Nonparametric density estimation for interest rates
  7. Nonparametric estimation of volatility
  8. Nonparametric pricing of interest‐rate derivatives
  9. Practical model building

Reading List

  • Material supplied by the instructors

Instructors

  • Stefano Bragoli
  • Andrea Giacomelli

Syllabus

  1. Definition of credit risk
  2. The estimate of the different credit risk components
  3. Pricing of instruments subject to credit risk
  4. Portfolio models
  5. Definitions of operational risk
  6. Bayesian Networks
  7. Other measurement tecniques

Reading List

  • Duffie D. and Singleton K. J. (2003), Credit Risk: Pricing, Management, and Measurement, Princeton University Press
  • Gupton G., Finger C.C. and Bhatia M. (1997), CreditMetrics, Technical Document. J.P. Morgan & Co.
  • Credit Suisse Financial Products (1997), CreditRisk+. A Credit Risk Management Framework, Technical Document, CSFP.
  • Daykin C.D., Pentikäinen T., Pesonen M. (1994), Practical Risk Theory for Actuaries, Chapman & Hall
  • Wilson, T. (1997), Portfolio Credit Risk (I), Risk, vol. 10 n. 9, 111-117
  • Wilson, T. (1997), Portfolio Credit Risk (II), Risk, vol. 10 n. 10, 56-61
  • Cruz M. G. (2002), Modeling, Measuring and Hedging Operational Risk; John Wiley & Sons
  • Embrechts P., Klüppelberg C. and Mikosch T. (1997), Modelling Extremal Events for Insurance and Finance, Springer-Verlag
  • Pearl J. (2000), Causality: Models, reasoning, and inference, Cambridge University Press

Instructors

  • Andrea Berardi
  • Marcello Pericoli

Syllabus

  1. The basics
  2. Modern term structure theory
  3. Empirical tests of term structure models

Reading List

  • Cairns, A. (2004): Interest rate models: an introduction, Princeton University Press.
  • Rebonato, “Interest rate option models”, Wiley.
  • Hull, “Options, futures, and other derivatives”, Prentice Hall

The ARPM Certificate establishes broad and deep proficiency in modern quantitative finance, across the financial industry: asset management, banking and insurance.

Attainment of the ARPM Certificate requires the candidate to successfully complete three tests: the Level I Exam, the Level II Exam, and the Practical Project.

250 hours

For the modality and activation visit the dedicated web page: Stage [ITA] / Internships [ENG].

Last update: 26/05/2023