Session 5 | 09:00 | Francesco Colasanto, Luca Grilli, Domenico Santoro and Giovanni Villani | Fine-tuned AlBERTo for Stock Price Prediction: a Gibbs Sampling Approach |
| 09:25 | Luca Barbaglia, Sergio Consoli and Sebastiano Manzan | Nowcasting the economy with news during the pandemic |
| 09:50 | Lucia Alessi, Eric Ghysels, Marco Petracco and Zhe Wang | Bitcoin and News Around the World in Twenty-Six Languages |
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Break | 10:15 | | |
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Invited | 10:30 | EMANUELE BORGONOVO | Interpretability and Explainability Methods: Can They Help Financial Machine Learning? |
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Session 6 | 11:30 | Damiano Brigo, Xiaoshan Huang, Andrea Pallavicini and Haitz Saez de Ocariz Borde | Interpretability in deep learning for finance: a case study for the Heston model |
| 11:55 | Leandro Sánchez-Betancourt, Álvaro Cartea and Imanol Perez Aribas | Optimal Execution of Foreign Securities: A Double-Execution Problem with Signatures and Machine Learning |
| 12:20 | Giovanni Rabitti, Emanuele Borgonovo and Elmar Plischke | Higher order Shapley effects for global sensitivity analysis of extremes |
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Lunch | 12:45 | | |
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Invited | 14:00 | JURI MARCUCCI | Using Twitter for Macroeconomic Indicators |
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Session 7 | 15:00 | Piotr Wójcik and Bedil Karimov | Identification of scams in Initial Coin Offerings with machine learning |
| 15:25 | Alessandro Bitetto, Paola Cerchiello, Stefano Filomeni, Alessandra Tanda and Barbara Tarantino | Machine Learning and Credit Risk: Empirical Evidence from SMEs |
| 15:50 | Ajit Desai and James Chapman | Macroeconomic Predictions using Payments Data and Machine Learning |
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Break | 16:15 | | |
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Session 8 | 16:45 | Emilio Barucci, Michele Bonollo, Federico Poli and Edit Rroji | A machine learning algorithm for stock picking built on information based outliers |
| 17:10 | Luca Sitzia, Roberto Baccaglini, Vittorio Malacchia and Federico Cozzi | A Neural Network Approach for the Estimation of Mortgage Prepayment Rates |
| 17:35 | Michele Azzone, Roberto Baviera and Pietro Manzoni | Neural Network Middle-Term Probabilistic Forecasting of Daily and hourly Power Consumption |
| 18:00 | Michele Azzone, Emilio Barucci, Giancarlo Giuffra and Daniele Marazzina | A Machine Learning Model for Lapse Prediction in Life Insurance Contracts |