The course aims to deepen and extend the concepts and techniques acquired by students during the previous level of their studies to understand and manage complexity and risk in different contexts. We aim at providing students with skills for solving complex problems deriving from real applications, providing decision-making techniques through the application of quantitative approaches, giving an understanding of the interaction between computer science and the optimization of processes at an advanced level, offering tools for the management of large datasets in economics, finance and business.
The goal is to equip students with skills and encourage critical thinking from a quantitative point of view, to avoid a mere application of routines and algorithms.
The focus will be on the study and in-depth understanding of complex networks and different types of risk in financial, macroeconomic, energy, cyber and insurance fields, to list but a few.
The goal is to equip students with skills and encourage critical thinking from a quantitative point of view, to avoid a mere application of routines and algorithms.
The focus will be on the study and in-depth understanding of complex networks and different types of risk in financial, macroeconomic, energy, cyber and insurance fields, to list but a few.
Curriculum
teacher profile teaching materials
Financial Risk
Derivatives Markets
Risk in the Energy Sector
Option Pricing: The Cox–Ross–Rubinstein Binomial Model
Deterministic Differential Equations in Financial Modelling
Differential Calculus and the Black–Scholes Option Pricing Model
The Greeks and Sensitivity Analysis
Value at Risk (VaR)
Volatility: Measurement and Role in Risk Management
Quantitative Methods for Systemic Risk and Complexity
Entropy, Uncertainty, and Complexity in Financial Systems
Programme
Introduction to RiskFinancial Risk
Derivatives Markets
Risk in the Energy Sector
Option Pricing: The Cox–Ross–Rubinstein Binomial Model
Deterministic Differential Equations in Financial Modelling
Differential Calculus and the Black–Scholes Option Pricing Model
The Greeks and Sensitivity Analysis
Value at Risk (VaR)
Volatility: Measurement and Role in Risk Management
Quantitative Methods for Systemic Risk and Complexity
Entropy, Uncertainty, and Complexity in Financial Systems
Core Documentation
Teaching materials provided by the lecturerAttendance
Strongly recommendedType of evaluation
Learning outcomes are assessed through a final examination aimed at verifying knowledge of the theoretical content and the ability to apply the quantitative tools presented in the course. The assessment considers the correctness of the solutions, clarity of exposition, and the ability to interpret results from an economic perspective. Activities carried out during the course may contribute to the final grade, according to criteria communicated at the beginning of the course. teacher profile teaching materials
Financial Risk
Derivatives Markets
Risk in the Energy Sector
Option Pricing: The Cox–Ross–Rubinstein Binomial Model
Deterministic Differential Equations in Financial Modelling
Differential Calculus and the Black–Scholes Option Pricing Model
The Greeks and Sensitivity Analysis
Value at Risk (VaR)
Volatility: Measurement and Role in Risk Management
Quantitative Methods for Systemic Risk and Complexity
Entropy, Uncertainty, and Complexity in Financial Systems
Mutuazione: 21210495 Metodi quantitativi per il rischio e la complessità in Economia e Gestione della Trasformazione Digitale LM-56 R MASTROENI LORETTA CLARA LETIZIA
Programme
Introduction to RiskFinancial Risk
Derivatives Markets
Risk in the Energy Sector
Option Pricing: The Cox–Ross–Rubinstein Binomial Model
Deterministic Differential Equations in Financial Modelling
Differential Calculus and the Black–Scholes Option Pricing Model
The Greeks and Sensitivity Analysis
Value at Risk (VaR)
Volatility: Measurement and Role in Risk Management
Quantitative Methods for Systemic Risk and Complexity
Entropy, Uncertainty, and Complexity in Financial Systems
Core Documentation
Teaching materials provided by the lecturerAttendance
Strongly recommendedType of evaluation
Learning outcomes are assessed through a final examination aimed at verifying knowledge of the theoretical content and the ability to apply the quantitative tools presented in the course. The assessment considers the correctness of the solutions, clarity of exposition, and the ability to interpret results from an economic perspective. Activities carried out during the course may contribute to the final grade, according to criteria communicated at the beginning of the course.