Overview

There are four 2-weeks sessions. A session consists of two consecutive one-week courses, supplemented by one guest lecture on a topic of special interest. Each session can be chosen independently, but each two-week session must be attended in full.

Session 1: Modern risk measurement (23 February–8 March 2025)

Session 2: New challenges on long-run risks (27 July–9 August 2025)

Note: Students admitted to this session must have basic knowledge in theoretical and empirical asset pricing (e.g., see topics reported in the J Chocrane book, “Asset Pricing”); financial econometrics (multivariate linear regressions; time-series econometrics; forecasting; GMM; GARCH; estimation of APT models).

Week 1 (Mo 28/7 to Fri 1/8): MacroFinTech

Lecturer: Max Croce, U. Bocconi

Contents: Modern macrofinance models often take into account the role of news shocks. For news shocks to be priced, preferences should go beyond the expected utility framework. This course has two applied goals. First, familiarize with asset pricing models with recursive preferences in both endowment and production economies. Second, solve macrofinance DSGE models through standard perturbation methods. Becoming knowledgeable about these techniques is extremely beneficial as it increases both the quantity of research papers that can be produced in a short amount of time.

This course is mainly applied, in the sense that we will devote most of our time learning how to solve a model and get results. We will see only a minimum set of theoretical concepts that are essential to check the correctness of the solution and debug our codes. By the end of the course, solving a dynamic stochastic general equilibrium (DSGE) model should be a routine task.

We will work with dynare++.exe, a free stand-alone package that solves stochastic systems of smooth equations. We will also learn how to integrate dynare++.exe with Matlab in order to generate nice tables and figures in an efficient way. We will see recent applications related to:
– MacroFinTech for emissions regulation;
– Supply Chain Uncertainty & Growth;
– Currencies.

Depending on enrollment, some presentations will be assigned to students. We will have 1 or 2 homeworks that will require students to replicate existing papers using dynare++ and Matlab.

Some references:
– Tallarini (2000, JME);
– Bansal and Yaron (2004, JF);
– Kung and Schmit (2013, JF);
– Croce et al (2024), WP, ‘Supply Chain Uncertainty’
– Croce et al (2025), WP, ‘Green Coins’.

Fri 1/8: GUEST LECTURE on Horizon risk, what is it and how to tackle it in a dynamic way

Speaker: Giulia Di Nunno, U. Oslo

Contents: Horizon risk is the assessing the financial exposure by a risk measure that is not adequate to the actual time horizon of the position. We clarify that dynamic risk measures are subject to horizon risk, so we propose to work with fully-dynamic risk measures. We shall combine horizon risk with other uncertainties of the future market scenarios, such as interest rates uncertainty, thus we propose and justify the use of a cash non-additive version. We then construct such risk measures via backward stochastic differential equations or via shortfall-type representation. As illustration, we introduce the class of hq-entropic risk measures.

Week 2 (Mo 4/8 to Fri 8/8): Model free pricing and estimation of financial risks

Session 3: AI for Risk (14–27 September 2025)

Week 1 (Mo 15/9 to Tue 23/9): Predictive uncertainty in Machine Learning with conformal inference

Lecturer: Stefano Favaro, U. Torino and Collegio Carlo Alberto

GUEST LECTURE: Introduction to CyberRisk

Speaker: Alessandro Armando, U. Genoa and IMT Lucca

Week 2 (Mo 21/9 to Fri 25/9): Concepts of Deep Learning and applications to Finance and Risk Management

Session 4: Networks and risk propagation (18–31 January 2026)

Week 1 (Mo 19/1 to Fri 23/1, 2026): Title TBD

Lecturer: Remco Hofstad, Eindhoven U. of Technology

GUEST LECTURE: Title TBD

Speaker: Monica Billio, U. Ca’ Foscari Venezia

Week 2: (Mo 26/1 to Fri 30/1, 2026): Title TBD