MODELS AND TECHNOLOGY FOR THE FINANCIAL INDUSTRY

Academic year

2023/2024 Syllabus of previous years

Official course title

MODELS AND TECHNOLOGY FOR THE FINANCIAL INDUSTRY

Course code

EM1414 (AF:382721 AR:208972)

Modality

On campus classes

ECTS credits

6

Degree level

Master's Degree Programme (DM270)

Educational sector code

SECS-P/02

Period

3rd Term

Course year

2

Where

VENEZIA

Moodle

Go to Moodle page

Contribution of the course to the overall degree programme goals

The teaching is one of the characterizing courses of the Master's Degree course in DATA ANALYTICS FOR BUSINESS AND SOCIETY and reviews the machine learning techniques applied to the financial industry.
The course focuses on understanding the most common algorithms and tools used by data scientists in finance.
During the course, practical cases will be discussed in order to apply the acquired knowledge. Python will be used.

Expected learning outcomes

1. Knowledge and comprehension
- study and understanding of the data available in the financial industry
- review of the common machine learning techniques applied to the financial industry

2. Application of Knowledge and comprehension
- Identify and apply the machine learning techniques to the analyzed problem
- Analysis of practical cases with the use of Python

3. Judgment skills
- Validation and testing of the model

Pre-requirements

Follow the requirements indicated by the Master's Degree course in DATA ANALYTICS FOR BUSINESS AND SOCIETY

Contents

Introduction to Machine Learning in the financial industry
Unsupervised learning
Supervised learning and regularization (Linear and Logistic regression, survival analysis, and support vector machines)
Financial Portfolio and regularization

Referral texts

Written material will be provided on the Moodle course linked with the lessons.
Suggested reading: Hull, J. (2021). Machine Learning in Business: An Introduction to the World of Data Science. Third Edition. Amazon Distribution.

Assessment methods

For attendees: The learning assessment consists of a written part (open questions) and an empirical analysis carried out in a group or individually.
For non-attendees: Written exam.

Teaching methods

Lecture. Slides, coding activities, exercises and examples available on Moodle platform.

Teaching language

English

Type of exam

written

2030 Agenda for Sustainable Development Goals

This subject deals with topics related to the macro-area "Human capital, health, education" and contributes to the achievement of one or more goals of U. N. Agenda for Sustainable Development

Definitive programme.

Last update of the programme: 20/03/2023