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