L’attività seminariale del gruppo Ingegneria finanziaria si articola su diverse forme di incontro che possono avere obiettivi diversi:
- sviluppare la diffusione della ricerca su tematiche di finanza quantitativa
- diffondere studi/risultati di tipo quantiativo all’interno della comunità finanziaria
- fornire agli studenti occasioni di incontro anche di natura non tecnica su tematiche attinenti il mondo della finanza.
Le attività comprendono seminari scientifici, workshop e incontri su temi specifici, corsi di formazione.
Jun 14 2021Summer School – From Networks to Neural Networks in Finance
Lake Como School of Advanced Studies - 14-18 June 2021
The School aims to present the state of the art on methodologies and applications of Neural Networks and Nets to finance. The expected audience of the school is provided by PhD student and young researchers interested in applications of Neural Networks and Nets to finance.
The school is organized through three different initiatives:
- Four minicourses
- Workshops with students and participants to the school on developing research ideas.
- Albert Diaz Guilera, Universitat de Barcelona (12 hours):
- Tomaso Aste UCL, London (6 hours): Information filtering networks for socio-economic systems
- Matteo Matteucci, Politecnico di Mialno (12 hours): Introduction to neural networks: from theory to practice
- Josef Teichmann, ETH Zurich (6 hours) (TBC)
- Christoffer Kok, European Central Bank, Contagion modelling at the ECB: analytical frameworks and policy usage
- Paolo Giudici, Università di Pavia, Network based credit risk models for peer to peer lending.
- Andrea Prampolini, Intesa Sanpaolo, Limit order book simulation with interactive agents
Detailed program: https://nnnf.lakecomoschool.org/program/
Dipartimento di Matematica
Politecnico di Milano
Emilio Barucci, Roberto Baviera, Daniele Marazzina.
Michele Azzone, Emilio Barucci, Roberto Baviera, Matteo Brachetta, Giancarlo Giuffra, Francesca Grassetti, Daniele Marazzina.
Jun 10 2021Conference Big Data and Machine Learning in Finance
Politecnico di Milano, June 10-11, 2021
Big Data and Machine Learning are driving a significant transformation in the financial industry. Amazing examples include: robo-advisory; predicting frauds in payment systems; development of sophisticated algorithmic trading strategies; systemic risk assessment; rating of companies/financial products using a huge amount of information; development of chatbots for customers; nowcasting of financial time series; digital marketing; instant pricing of insurance products.
The transformation concerns the academia and the financial industry. The goal of the conference is to bring together academicians with different backgrounds (economists, finance experts, data scientists, econometricians) and representatives of the financial industry (banks, asset management, insurance companies) working in this field.
Papers on all areas dealing with Machine Learning and Big Data in finance (including Natural Language Processing and Artificial Intelligence techniques) are welcomed. The conference targets papers with different angles (methodological and applications to finance).
For the time being, the conference is planned to be in presence. Depending on the COVID emergency, we may consider to switch to an on-line (or a blended) conference by the 20th of April. In any case the conference will be organized (either in presence, blended or on-line). The conference fees (including the social dinner) are
- 200 Euro (industry) - Early bird 150
- 150 Euro (academic) - Early bird 100
- 50 Euro (phD student)
The early bird payments are for people registering to the conference before March 30th. However, the payments will be possible only after April 20th - in case of online conference, there will be no fees to be paid.
- Tomaso Aste (University College London)
- Emanuele Borgonovo (Università Bocconi)
- Tucker Balch (JP Morgan AI research)
- Juri Marcucci (Bank of Italy)
- Georgios Sermpinis (Adam Smith Business School, University of Glasgow)
Submission of the papers deadline: March 30th, 2021
Notification deadline: April 20th, 2021
Registration deadline: June 1st, 2021
Scientific Committee: Emilio Barucci (Politecnico di Milano, chair), Filippo Della Casa (UNIPOL), Paolo Giudici (Università di Pavia), Daniele Marazzina (Politecnico di Milano), Valerio Poti (University College Dublino), Andrea Prampolini (Banca IMI), Marcello Restelli (Politecnico di Milano).
Organizing Commitee: Michele Azzone, Emilio Barucci (chair), Francesca Grassetti, Daniele Marazzina, Marcello Restelli.
Contact us: firstname.lastname@example.org
With the support of
Apr 20 2021Polimi Fintech Series – Sandra Paterlini – April 20, 2021
April 20th, 2021 - 17.30 (CET)
Sandra Paterlini (Trento University)
Details about the seminar will be added soon
Mar 22 2021Polimi Fintech Series – Valerio Potì – March 22, 2021
March 22nd, 2021 - 17.30 (CET)
Valerio Potì (University College Dublin)
COVID Narrative Risk: A Computational Linguistic Approach to the Econometric Identification of Narrative Risk During the COVID-19 Pandemic
Details about the seminar will be added soon
Feb 22 2021Polimi Fintech Series – Charalampos Stasinakis – February 22, 2021
February 22nd, 2021 - 17.30 (CET)
Charalampos Stasinakis - University of Glasgow
(with G. Sermpinis)
Big Data, Artificial Intelligence and Machine Learning: A Transformative Symbiosis in Favour of Financial Technology
The financial technology revolution is a reality, as the financial world is gradually transforming into a digital domain of high-volume information and high-speed data transformation and processing. The more this transformation takes place, the more consumer and investor behaviour shifts towards a pro-technology attitude of financial services offered by market participants, financial institutions and financial technology companies. This new norm is confirming that information technology is driving innovation for financial technology. In this framework, the value of big data, artificial intelligence and machine learning techniques becomes apparent. The aim of this chapter is multi-fold. Firstly, a multidimensional descriptive analysis is shown to familiarise the reader with the extent of penetration of the above in the financial technology road-map. A short non-technical overview of the methods is then presented. Next, the impact of data analytics and relevant techniques on the evolution of financial technology is explained and discussed along with their applications’ landscape. The chapter also presents a glimpse of the shifting paradigm these techniques bring forward for several fintech related professions, while artificial intelligence and machine learning techniques are tied with the future challenges of AI ethics, regulation technology and the smart data utilisation.