Game Theory

Mechanism Design. Revelation principle, Dominance and Nash Implementation. Strategic and Axiomatic Bargaining. Asymmetric Information and Optimal Contracts. Moral Hazard and Adverse Selection models. Signaling and Screening Models. Applications. Static games of complete information: definition of a game; normal form representation; strongly and weakly dominated strategies; Nash Equilibrium (NE); mixed strategy equilibrium. Applications of NE and introduction to market competition; Cournot competition; Bertrand competition; externalities; public goods.

Funding and Management of Research and Intellectual Property (long seminar without exam)

This long seminar aims at providing an overview on the management of intellectual property rights (copyright transfer agreements; open access; patents, etc.). Funding opportunities for PhD students, post-docs, and researchers are also presented (scholarships by the Alexander von Humboldt Foundation; initiatives by the Deutscher Akademischer Austausch Dienst; scholarships offered by the Royal Society in UK; bilateral Italy-France exchange programmes; Fulbright scholarships; Marie Curie actions; grants for researchers provided by the European Research Council).

Foundations of Probability Theory and Statistical Inference

This course aims at introducing the fundamental concepts of probability theory and statistical
Some proofs are sketched or omitted in order to have more time for examples, applications and
In particular, the course deals with the following topics:

? probability space, random variable, expectation, variance, cumulative distribution function, discrete and absolutely continuous distributions, random vector, joint and marginal distributions, joint cumulative distribution function, covariance,


The course covers important topics in modern quantitative finance and risk management: efficient market hypothesis and violations, financial markets micro-structure and types of arbitrage, general principles of modelling the price dynamics of financial assets, market risk and other types of financial risks, Value-at-Risk (VaR) approach and applications, modelling of extreme events and crisis, VaR analysis for financial derivatives, copula methods,modelling of trends in time series in connection with technical analysis, and the foundations of high-frequency arbitrage trading.

Empirical Studies in Economics and Management

The course aims at providing students with hands-on empirical tools to test the behaviour of economic agents that are heterogeneous in nature. How productive is a firm, an industry or a country?

Economic Growth and Development

The main goal of the course is to introduce students to the Neoclassical growth model, the overlapping-generations model and endogenous technological change. The course will provide the basic tools required to study long run growth and provide some answers to the fundamental question of why economies grow and why some countries are much richer than others. The main topics will be the following. Stylized facts of economic growth and development. Introduction to the Solow growth model. Neoclassical growth. Overlapping generations and dynamic efficiency.

Econometrics I

This course presents a comprehensive treatment of econometric methods for linear models and assumes working knowledge of undergraduate econometrics basic linear algebra, basic probability theory, and statistics that are covered in the pre-courses.

Data Science with Complex Networks

Complex Systems are everywhere and in the era of massive production of electronic data coming from all sort of devices it is of crucial importance to have the right tools to manage and extract from them all the valuable information. To this aim during this course we will develop both the basic theoretical tools and the practical coding technics to tackle all sort of complex systems, ranging from Trade and Financial Networks, to the World Wide Web and the Social Networks.