Deadline extended – Polimi Summer School

We are glad to inform you that the summer school 
organized by the QFinLab research group at Politecnico di Milano, jointly with the Lake Como School of Advanced Studies and Fondazione Alessandro Volta, 
has extended the application deadline to  May 24th 2021
Because of Covid-19 restrictions, the School will be held online
Registration fees: 150 EUR, VAT 22% included
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 students and young researchers interested in applications of ML techniques to finance.People from industry are also welcome.
The school is organized through mini-courses, lectures and workshops and aims at introducing complex networks, neural networks, information filtering networks and their applications to socio-economic systems.

Albert Diaz Guilera, Universitat de Barcelona (10 hours): Complex networks foundations
Tomaso Aste UCL, London (6 hours): Information filtering networks for socio-economic systems
Matteo Matteucci, Politecnico di Milano (10 hours): Introduction to neural networks: from theory to practice
Josef Teichmann, ETH Zurich (6 hours) Provable Machine Learning Techniques in Finance.

Christoffer Kok, European Central Bank, Contagion modelling at the ECB: analytical frameworks and policy usage
Paolo Giudici, Università di Pavia, Explanable AI credit risk models for peer to peer lending.
Andrea Prampolini, Intesa Sanpaolo, Limit order book simulation with interactive agents
Giuseppe Bruno, Banca d’Italia, Anomaly Detection in RTGS Systems: Performance Comparisons Between Shallow and Deep Neural Networks
Michele Tumminello, Università di Palermo, Insurance fraud detection: a statistically validated network approach
Daniele Marazzina, Politecnico di Milano, A machine learning model for lapse prediction in the life insurance contracts
Marcello Restelli, Politecnico di Milano, Reinforcement Learning for Automated Trading

For detailed information visit the Summer School website.

OCF in collaborazione con QFinLab lancia InformarsiConviene

OCF, l’Organismo di vigilanza e tenuta dell’albo unico dei Consulenti Finanziari, in collaborazione con QFinLab – Politecnico di Milano, lancia il progetto di informazione “Informarsi Conviene”, mirato a diffondere nozioni basilari, considerazioni generali e qualche consiglio pratico, per agevolare un avvicinamento ampio ai servizi di investimento da parte dei risparmiatori.

Digital Euro Seminars

Apr 08 2021

QFinLab is pleased to announce:


Prof. Emilio Barucci

Politecnico di Milano


Toward the digital euro

technology, banks and monetary policy

Two appointments:

APRIL 8th 2021, 17.30 CET

Zoom Virtual Room:

ID: 825 3239 8177

APRIL 14th 2021, 17.30 CET 

Zoom Virtual Room:

ID: 832 5133 3953

Polimi Fintech Series – Valerio Potì – March 22, 2021

Mar 22 2021
The Polimi Fintech Series, under the and the Cost project, presents
March 22nd, 2021 – 17.30 (CET)
Virtual room: Click here to access the Zoom Virtual Room, or insert the Meeting id on your Zoom app: 885 3010 212

Valerio Potì (University College Dublin)

COVID Narrative Risk: A Computational Linguistic Approach to the Econometric Identification of Narrative Risk During the COVID-19 Pandemic


In this paper, we study the role in financial markets of narratives related to the ongoing COVID-19 pandemic. The pandemic represents a natural setting for the development of narratives that may effects or be affected by financial markets. We thus treat the pandemic as a natural experiment on the relation between prevailing narratives and financial markets. We adopt the SIR model and natural language processing on financial newspaper news and Twitter tweets that deal at the same time with financial market topics and COVID-19 to study the dynamics and determinants of coronavirus narrative epidemics. Our aim is to establish whether there an “infodemic” develops, and whether the prevailing narrative, whether resemnbling an infodemic or otherwise, drives or is driven by financial markets developments, controlling for developments regarding the COVID-19 pandemic. We find associations between narratives about the epidemic, stock market dynamics (both regarding returns and volatility) and government responses to COVID-19. We also find that the narrative spread does resemble an infodemic, since it is well described by the SIR epidemic model. Our estimates of the shape of the narrative infodemic curves in different countries depend on whether the COVID-19 outbreak occurred early and on its severity. Negative tones and tones communicating uncertainty are prevalent in the growing stage of the infodemic. We find preliminary evidence of a causality relation between the negative and uncertainty tones of coronavirus tweets and both market return and volatility change.


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Polimi Fintech Series – Charalampos Stasinakis – February 22, 2021

Feb 22 2021
The Polimi Fintech Series, under the and the Cost project, presents
February 22nd, 2021 – 17.30 (CET)
Virtual room: Click here to access the Zoom Virtual Room, or insert the Meeting id on your Zoom app: 827 9926 5984


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.


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