QFinLab e HuffPost Italia raccontano Fintech

Il gruppo QFinLab è lieto di annunciare la collaborazione con HuffPost Italia per la nuova sezione Fintech del giornale di informazione.

La nuova sezione è stata inaugurata il 13 ottobre con l’articolo di presentazione del Direttore Mattia Feltri.

Tutti i dettagli su HuffPost Fintech


Seminario “Consigli di Amministrazione e assetti proprietari delle società quotate”

Giovedì 7 Ottobre 2021, alle ore 10, il Prof. Emilio Barucci presenterà i risultati della ricerca Assetti proprietari e corporate governance nel nuovo millennio durante il convegno “Consigli di amministrazione e assetti proprietari delle società quotate” organizzato dal Consiglio Nazionale dell’Economia e del Lavoro (CNEL).

Il seminario potrà essere seguito in diretta al link https://youtu.be/DXsdcRbtFSk .


Big Data and Machine Learning in Finance Conference

Politecnico di Milano

June 10, 2021 – June 11, 2021

Session 109:00Stefano Polo, Roberto Daluiso, Emanuele Nastasi and Andrea PallaviciniReinforcement Learning for Options on Target Volatility Funds
 09:25Edoardo Vittori, Michele Trapletti and Marcello RestelliOption Hedging with Risk Averse Reinforcement Learning
 09:50Carlo Sala, Tristan Cazenave and Timothee Sohm-QueronNeural Network for Volatility Surfaces under Convex Constraint
    
Break10:15  
    
Invited10:30TOMASO ASTEDeep learning the limit order book:  what machines can learn and what can we learn from them?
    
Session 211:30Riccardo Aiolfi, Nicola Moreni, Marco Bianchetti, Marco Scaringi and Filippo FoglianiLearning Bermudans
 11:55Pietro Rossi, Marco Bianchetti, Giovanni Amici, Alessio Peroni, Federico Brina and Matteo MezzettiLearning Derivatives Without Calibration
 12:20Roberto Daluiso, Emanuele Nastasi, Andrea Pallavicini and Giulio SartorelliPricing Swing Options by Reinforcement Learning
    
Lunch12:45  
    
Invited14:00GEORGIOS SERMPINISFunctional False Discovery Rate in Mutual Fund Performance
    
Session 315:00Fabio Verona and Gonçalo FariaFrequency-domain information for active portfolio management
 15:25Edoardo Vittori, Amarildo Likmeta and Marcello RestelliMonte Carlo Tree Search for Trading and Hedging
 15:50Karoline Bax, Özge Sahin, Claudia Czado and Sandra PaterliniESG, Risk and dependence: an empirical investigation
    
Break16:15  
    
Session 416:45Paul Hager, Christian Bayer, Sebastian Riedel and John SchoenmakersOptimal Stopping with Signatures
 17:10Niklas Bussmann, Roman Enzmann, Paolo Giudici and Emanuela RaffinettiAn extension of the Shapley-Lorenz decomposition to risk management
 17:35Angela De Martiis, Thomas Heil and Franziska PeterAre you a Zombie? A Supervised Learning Method to Classify Unviable Firms and Identify the Determinants
 18:00Martino Bernasconi de Luca, Edoardo Vittori, Francesco Trovò and Marcello RestelliDealer Markets: a Reinforcement Learning Mean Field Approach
Session 509:00Francesco Colasanto, Luca Grilli, Domenico Santoro and Giovanni VillaniFine-tuned AlBERTo for Stock Price Prediction: a Gibbs Sampling Approach
 09:25Luca Barbaglia, Sergio Consoli and Sebastiano ManzanNowcasting the economy with news during the pandemic
 09:50Lucia Alessi, Eric Ghysels, Marco Petracco and Zhe WangBitcoin and News Around the World in Twenty-Six Languages
    
Break10:15  
    
Invited10:30EMANUELE BORGONOVOInterpretability and Explainability Methods: Can They Help Financial Machine Learning?
    
Session 611:30Damiano Brigo, Xiaoshan Huang, Andrea Pallavicini and Haitz Saez de Ocariz BordeInterpretability in deep learning for finance: a case study for the Heston model
 11:55Leandro Sánchez-Betancourt, Álvaro Cartea and Imanol Perez AribasOptimal Execution of Foreign Securities: A Double-Execution Problem with Signatures and Machine Learning
 12:20Giovanni Rabitti, Emanuele Borgonovo and Elmar PlischkeHigher order Shapley effects for global sensitivity analysis of extremes
    
Lunch12:45  
    
Invited14:00JURI MARCUCCIUsing Twitter for Macroeconomic Indicators
    
Session 715:00Piotr Wójcik and Bedil KarimovIdentification of scams in Initial Coin Offerings with machine learning
 15:25Alessandro Bitetto, Paola Cerchiello, Stefano Filomeni, Alessandra Tanda and Barbara TarantinoMachine Learning and Credit Risk: Empirical Evidence from SMEs
 15:50Ajit Desai and James ChapmanMacroeconomic Predictions using Payments Data and Machine Learning
    
Break16:15  
    
Session 816:45Emilio Barucci, Michele Bonollo, Federico Poli and Edit RrojiA machine learning algorithm for stock picking built on information based outliers
 17:10Luca Sitzia, Roberto Baccaglini, Vittorio Malacchia and Federico CozziA Neural Network Approach for the Estimation of Mortgage Prepayment Rates
 17:35Michele Azzone, Roberto Baviera and Pietro ManzoniNeural Network Middle-Term Probabilistic Forecasting of Daily and hourly Power Consumption
 18:00Michele Azzone, Emilio Barucci, Giancarlo Giuffra and Daniele MarazzinaA Machine Learning Model for Lapse Prediction in Life Insurance Contracts

EMFI


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.
 

Minicourses:
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.


Lectures:
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.