# Numerical Methods for Finance and Risk Management

A.Y. 2020/2021
12
Max ECTS
80
Overall hours
SSD
SECS-S/01 SECS-S/06
Language
English
Learning objectives
Module Numerical Methods for Finance
The first part of the course aims to provide a good knowledge of stochastic calculus and no arbitrage principles that constitute the foundations in the pricing of financial derivatives. We first discuss the Wiener process, then we move to the construction of stochastic integrals. We also introduce the concept of a martingale measure and its connection with the Fundamental Theorem of Asset Pricing.
The second part of the course aims to introduce students to the main numerical methods for the estimation of stochastic processes and to the numerical evaluation of contingent claims. The main topics presented are: Monte Carlo simulation, parameter estimation of stochastic processes, model selection and calibration.

Module Risk Management
At the end of the course, the student will possess an adequate mathematical terminology, learned the main quantitative and computational tools to be able to work in the risk management unit of a bank or insurance company.
Expected learning outcomes
Module Numerical Methods for Finance
At the end of the course, students should have acquired the fundamentals of stochastic calculus and the main numerical methods for the evaluation of contingent claims. Students should be able to produce scripts in the R programming language for the estimation of a stochastic process that describes the asset price dynamics and evaluate numerically contingent claims based on no arbitrage principles.

Module Risk Management
At the end of the course, the student will know the basic elements of the Basel and Solvency regulatory frameworks for banks and insurance companies; will possess an adequate mathematical terminology and learned the main quantitative tools related to the study of risk variables and measures in quantitative risk management; will be able to recognize statistically the presence of an elliptical or heavy-tailed distribution and determine its influence on a risk portfolio; will be able to code a software for the computation of the capital reserve needed by a financial institution to comply with the above regulatory frameworks; will be aware of the basic quantitative tools to perform the stochastic aggregation of various typologies of risks.
Course syllabus and organization

### Single session

Responsible
Lesson period
Second trimester
Professor(s)
Reception:
Tuesday from 2.30 p.m. to 5.30 p.m.
Microsoft office Teams (https://work.unimi.it/servizi/servizi_tec/1536.htm)