Prof. Umberto Cherubini

Argomenti del programma: Since the aim of the course is to provide both theoretical background and knowledge of the markets, each three hour lesson will be partitioned in at least two parts. Very often, depending on current topics suggested by the Financial Times and other specialized sources, a third part will be carved out in the lesson, in which active participation of the students is expected.

Argomenti del programma: General principles a) A brief history of regulation from Basel I to FRTB b) Trading book and banking book c) Risk factors and risk events d) FRTB: SA and IMA e) P&L (profit and loss) attribution Fixed income: General Interest Rate Risk (GIRR) a) Cash flow analysis: fixed and floating rate notes b) Cash flow mapping and bucket hedging c) Sensitivity analysis: DV01, vega, curvature Sensitivities a) Sensitivities for…

Argomenti del programma: General principles a) A brief history of regulation from Basel I to FRTB b) Trading book and banking book c) Risk factors and risk events d) FRTB: SA and IMA e) P&L (profit and loss) attribution Fixed income: General Interest Rate Risk (GIRR) a) Cash flow analysis: fixed and floating rate notes b) Cash flow mapping and bucket hedging c) Sensitivity analysis: DV01, vega, curvature Sensitivities a) Sensitivities for…

Argomenti del programma: Lesson 1: Introduction to Machine Learning and Financial Data 1. Overview of Machine Learning and its Relevance to Finance 2. Types of Financial Data 3. Basic Statistics and Data Preprocessing Techniques Practical Session: Data Collection and Cleaning Using Python 1. Introduction to Python Libraries for Financial Data Analysis 2. Data Collection 3. Data Cleaning 4. Data Transformation 5. Data Integration 6.

Argomenti del programma: Parte I. Rischio di mercato 1. Rischio di mercato: definizione, concetti di mark-to-market, sensitività ai fattori di rischio e portafogli di replica 2. Tecniche di gestione del rischio di mercato: contratti swap e di opzione 3. Tecniche di mapping e reporting del rischio di mercato di portafogli 4. Tecniche di calcolo del Value-at-Risk: approccio parametrico, Monte Carlo e simulazione storica 5.