Courses a.y. 2022/2023
12139 COMPUTATIONAL METHODS AND MACHINE LEARNING
20191 FINANCIAL ECONOMETRICS AND EMPIRICAL FINANCE - MODULE 1
40406 ADVANCED ECONOMETRICS 4
I have taught many courses: Statistics, Econometrics, Quantitative Methods for Trading, Econometrics for Finance, and Machine Learning. In all of these courses, in full agreement with Bocconi University teaching philosophy, my first objective is to offer students a simple but rigorous treatment of the topic of the course. I strongly believe that a little of simple, correct, and deep knowledge is very useful.
Imprecise concepts and vague “stories” and “anecdotes,” are, maybe, at first sight fascinating and alluring, but in practice useless and potentially lead to errors. As opposed to this: practical examples are of fundamental importance if accompanied by the required basic knowledge required for a real understanding of “what is happening.”
Learning with detail and precision requires detail and completeness in teaching materials. I always try to help my students in this, by providing detailed and complete study materials and I am always available to answer their questions.
I graduated in Economics from Bocconi University in 1983. I was an Assistant Professor of Mathematical Statistics from 1989 to 1998 and an Associate Professor of Mathematical Statistics from 1998 to 2010. Since 2010, I have been an Associate Professor of Mathematics for Finance, Economics, and Insurance.
My main research interest has always been concentrated on the consequences of the use of “false” models in statistics and in finance. This is a classic topic, usually considered under two points of view:
- Robustness: where conclusions of a model resist misspecification
- Embedding and extension of the model
I did research in both directions, in particular in fields where models use the language of partial differential equations. In the first direction, I applied energy inequalities to check robustness of misspecified models for diffusions. In the second direction, I contributed to papers applying the parametrix series method to the approximation of non-solvable models.
More recently, I am trying to apply canonical correlation (in a suitably extended version) to the study of the “correlation” between the semantics of message exchanges scraped from the Internet and the evolution of certain characteristics of financial prices.
On analytic perturbations of the B&S PDE
Approximation tools for PDE solutions and applications in finance
The saga of the regression Beta: the cautionary tale of the most misunderstood statistical concept
Puzzling out what matters most in ESG ratings
Project Finance Collateralised Debt Obligations: an Empirical Analysis of Spread Determinants
European Financial Management, 2012
Risk Shifting Through Nonfinancial Contracts. Effects on Loan Spreads and Capital Structure of Project Finance Deals
Journal of Money, Credit, and banking, vol. 42, 2010
Parametrix approximation of diffusion transition densities
Siam Journal on Financial Mathematics, 2010
Hedging with Energy
Mathematical Finance, 2006
Factor based index tracking
Journal of Banking & Finance, 2006
Model error analysis methods
Statistica Applicata, vol. 4/2006, 2006
Risk management implications of time inconsistency: model updating and recalibration of no-arbitrage models
Journal of Banking & Finance, vol. 29, 2005
“Pitfalls in linear models for style analysis”
Statistical Methods & Applications, 2004
"LAWS OF LARGE NUMBERS"IN CONTINUUM ECONOMIES
Decisions, Games and Markets, 1997
A note on the decidability of de Finetti's coherence
Theory and Decision, 1995