Ateneo - UPO

The course addresses the application of quantitative methods and Artificial Intelligence tools in finance and Fintech and examines the main financing channels available to innovative start-ups and SMEs. Particular attention is devoted to investment decisions, risk management, financial markets, and the role of Venture Capital, Business Angels, and Crowdfunding, including in the context of Fintech, AI, and platform-based firms.

For the first module, the compulsory material for exam preparation is provided on the course DIR page; any books, articles, or other sources suggested during the lectures are optional and intended for further study.

For the second module, the main reference books are:

Alberto Dell’Acqua, John Shehata, Startup Finance, 2nd ed., Egea.
Ine Paeleman, Tom Vanacker, Silvio Vismara, Supradeep Dutta (eds.), Field Guide to Entrepreneurial Finance, Elgar Field Guides, 2026.

Scientific articles, working papers, slides, and case studies will also be provided.

The course aims to provide the conceptual, quantitative, and applied tools required to understand and analyze the main financial decisions in Fintech and entrepreneurial finance. In particular, the course aims to develop the ability to assess investment and financing problems under risk and uncertainty, understand the functioning of the main financial instruments and markets, and analyze the financing choices of start-ups and SMEs, with particular reference to Venture Capital, Business Angels, and Crowdfunding.
The course also aims to develop applied skills, critical judgement, and the use of appropriate technical language through case studies, quantitative applications, and Python activities.

FIRST MODULE
Basic knowledge of mathematics, probability, and statistics is required, sufficient to understand random variables, probability distributions, expected value, variance, covariance, and correlation.
Introductory knowledge of Python programming is also required, particularly the use of variables, data structures, functions, and libraries for numerical computing and data visualization.
A preliminary understanding of the main concepts of finance, such as return, risk, portfolios, financial instruments, and the general functioning of financial markets, is useful but not essential.

SECOND MODULE
None

The course combines lectures, quantitative examples, exercises, computational activities in Python, and case study analysis. Teaching activities are designed both to support the acquisition of the main concepts and tools and to promote their application to financial and entrepreneurial finance problems.
The course also includes guided discussions and group work, in written and/or oral form, aimed at developing critical judgement, applied skills, and the appropriate use of technical language.

For the first module, the information provided in the Syllabus concerning course content, teaching materials, teaching methods, and assessment applies to both attending and non-attending students.

For the second module, attending students may follow a specific learning pathway including the preparation and in-class presentation of a case study in small groups. The assessment of this activity contributes to the final grade. Further details will be provided during the course.

DISABILITY AND SPECIFIC LEARNING DISORDERS
Students with disabilities, Specific Learning Disorders (SLD), or Special Educational Needs (SEN) may request dedicated services and specific support by contacting the University Staff for Student Careers and Services and consulting the dedicated University webpage: https://uniupo.it/it/servizi/servizi-studenti-disabili-e-dsa
After contacting the relevant University Staff, students may also contact the lecturers responsible for the modules regarding teaching-related aspects and the adaptation of examination arrangements.

Assessment is based on different examinations for the two modules.

For the first module, the examination consists of an oral test aimed at assessing knowledge and understanding of the course contents, as well as the ability to apply concepts and models to simple financial problems. The oral examination may include theoretical questions, applications, numerical examples, interpretation of results, and discussion of computational procedures.

For the second module, a compulsory written examination is required, consisting of both open-ended and multiple-choice questions. Attending students will also complete group assignments related to guest lectures and case studies discussed during the course, and their assessment contributes to the final grade.

To pass the integrated course, students are required to demonstrate an adequate knowledge of the contents of both modules and the ability to correctly apply the main concepts. Higher grades will be awarded for greater mastery of the topics, ability to establish connections between different subjects, independent judgement, and clarity of presentation.

The integrated course covers the main topics of Fintech, quantitative finance, and entrepreneurial finance.

The first module focuses on the use of quantitative methods and Artificial Intelligence tools in financial decision-making. Main topics include risk and uncertainty modelling, Monte Carlo simulation, portfolio optimization, utility theory, dynamic asset allocation, derivatives pricing and hedging, market microstructure, algorithmic trading, optimal execution, market making, and the design of AI-based financial systems. Quantitative and computational applications are developed in Python.

The second module examines the main financing channels available to start-ups and SMEs and the role of the key actors in the entrepreneurial finance ecosystem. Topics include the funding gap and financing over the firm life cycle, debt and equity financing, Venture Capital across the different stages of the investment process, Business Angels, and Crowdfunding. The module also addresses the impact of Fintech on the financial sector, new business models, emerging risks and challenges, through case studies including target firm valuation and the design of crowdfunding campaigns. The gender dimension is also considered, with particular reference to female entrepreneurship and the gender gap in access to capital.

By the end of the course, students will be able to understand the main concepts and tools of Fintech, quantitative finance, and entrepreneurial finance, with particular reference to investment and financing decisions, risk management, financial markets, and the financing of start-ups and SMEs.
Students will also be able to apply the main tools covered in the course to simple financial problems, interpret quantitative results, critically assess models and financing alternatives, and discuss the decisions of the different actors in the financial ecosystem using appropriate technical language.