95661 - ADVANCED MACHINE LEARNING

Anno Accademico 2023/2024

  • Docente: Matteo Amabili
  • Crediti formativi: 3
  • SSD: SECS-S/06
  • Lingua di insegnamento: Inglese
  • Modalità didattica: Convenzionale - Lezioni in presenza
  • Campus: Bologna
  • Corso: Laurea Magistrale in Quantitative Finance (cod. 8854)

Conoscenze e abilità da conseguire

The Advanced ML course is geared towards state of the art application of neural network to pricing and market risk problem. The studend will acquire a sound knowledge of the principles underlying Neural Networks and will be guided in a tour of the relevant literature concerning the exploitation of machine learning for pricing of highly exotic products and applications to market risk managment. Altough the approach demands very large scale computing facilities, impossible to be provided to the students, nonetheless students will learn how to design solutions to this type of problem and will gain hands on experience of the methodology on simpler and smaller toy models.

Contenuti

The first part of the course is dedicated to the study of Neural Networ:

  1. Foundamentals of Neural Network
    1.1 What is a Neural Network
    1.2 Train a NN: backpropagation
    1.3 Handling categorical variables
    1.4 Tips & trick

The rest of the course is dedicated to application in finance, i.e. for the calibration of model from market data via NN.

  1. Definition of the calibration problem
  2. NN to approximate price and volatility surface
  3. Use NN as a noise filter for pricing
  4. Pointwise calibration
  5. Surface calibration

For this second part is higly recommended to attend to the course "computational finance" held by Prof. Pietro Rossi.

Modalità di verifica e valutazione dell'apprendimento

The final exam will consists of a project.

Strumenti a supporto della didattica

  • Slides (power point/pdf)
  • Selected literature
  • Jupyter Notebook and Python Code

Orario di ricevimento

Consulta il sito web di Matteo Amabili