Teaching
Philosophy
I teach valuation and financial statement analysis the way it is actually practised — as the disciplined, case-by-case translation of accounting numbers into economic claims about a business. Lecture material is built around real firms, real filings, and real questions an investor, lender, or acquirer must answer with the data on hand. Each session asks students to (i) reformulate the financial statements, (ii) make a defensible forecast, (iii) translate that forecast into a value, and (iv) confront their value with the price the market is quoting. The discipline lies in showing how each step is sensitive to specific accounting choices and disclosure quality — the connective tissue between financial statement analysis, auditing, and management accounting.
Experience
Financial Statement Analysis for Company Valuation
Sole lecturer. Integrated AI-augmented research workflows into the syllabus, teaching students to use large language models as a fast but fallible research assistant whose output must be critically audited.
Bocconi University · 2023–present
Ran case discussions, designed problem sets, and held weekly office hours for students of mixed quantitative background. Contributed materials to the Penman–Pope textbook on Financial Statement Analysis for Value Investing.
AI in the classroom
In the 2026 course I introduced AI as a fast — but fallible — research assistant whose output students must critically interrogate, through three workflows: (i) using LLMs to pull material from 10-K filings and conference calls, then independently auditing the extraction; (ii) prompting an LLM to draft a valuation thesis, then identifying its specific accounting mistakes; and (iii) using AI to stress-test forecasts under alternative assumptions. The goal is to graduate students who can use AI productively and know exactly where it breaks.