contact@visioscientiae.com
| Document title | Author | Years | Source |
|---|---|---|---|
| Event detection in finance using hierarchical clustering algorithms on news and tweets | Carta, S.M., Consoli S., Piras L., Podda, A.S., Reforgiato Recupero, D. | 2021 | PeerJ Computer Science (in press) |
| Explainable Machine Learning Exploiting News and Domain-Specific Lexicon for Stock Market Forecasting | Carta, S.M., Consoli S., Piras L., Podda, A.S., Reforgiato Recupero, D. | 2021 | IEEE Access |
| Ensembling and Dynamic Asset Selection for Risk-Controlled Statistical Arbitrage | Carta, S.M., Consoli, S., Podda, A. S., Reforgiato Recupero, D., Stanciu, M.M. | 2021 | IEEE Access |
| HawkEye: a Visual Framework for Agile Cross-Validation of Deep Learning Approaches in Financial Forecasting | Carta, S.M., Consoli, S., Corriga, A., Dapiaggi, R., Podda, A. S., Reforgiato Recupero, D. | 2021 | ACM ICPS (in press) |
| Multi-DQN: An ensemble of Deep Q-learning agents for stock market forecasting | Carta, S.M., Ferreira A., Podda, A.S., Recupero, D.R., Sanna, A. | 2021 | Expert Systems with Applications |
| Deep learning and time series-To-image encoding for financial forecasting | Barra. S., Carta, S.M., Corriga, A., Podda, A.S., Recupero, D.R. | 2020 | IEEE/CAA Journal of Automatica Sinica |
| Dynamic Industry- specific Lexicon Generation for Stock Market Forecast | Carta, S.M, Consoli, S., Piras, L., Podda, A.S., and Recupero, D.R. | 2020 | The Sixth International Conference on Machine Learning, Optimization, and Data Science |
| A Multi-Layer and Multi-Ensemble Stock Trader Using Deep Learning and Deep Reinforcement Learning | Carta, S.M., Corriga, A., Ferreira A., Podda, A.S. | 2020 | Applied Intelligence |
| A General Framework for Risk Controlled Trading Based on Machine Learning and Statistical Arbitrage | Carta, S.M., Recupero, D.R., Stanciu, M., Saia, R. | 2020 | The Sixth International Conference on Machine Learning, Optimization, and Data Science |
| A holistic auto-configurable ensemble machine learning strategy for financial trading | Carta, S.M., Corriga, A., Ferreira, A., Recupero, D.R., Saia, R. | 2019 | Computation |
Carta, S.M., Consoli S., Piras L., Podda, A.S., Reforgiato Recupero, D., Event detection in finance using hierarchical clustering algorithms on news and tweets (2021), PeerJ Computer Science (in press)
Carta, S.M., Consoli S., Piras L., Podda, A.S., Reforgiato Recupero, D., Explainable Machine Learning Exploiting News and Domain-Specific Lexicon for Stock Market Forecasting (2021), IEEE Access
Carta, S.M., Consoli, S., Podda, A. S., Reforgiato Recupero, D., Stanciu, M.M., Ensembling and Dynamic Asset Selection for Risk-Controlled Statistical Arbitrage (2021), IEEE Access
Carta, S.M., Consoli, S., Corriga, A., Dapiaggi, R., Podda, A. S., Reforgiato Recupero, D., HawkEye: a Visual Framework for Agile Cross-Validation of Deep Learning Approaches in Financial Forecasting (2021), ACM ICPS (in press)
Carta, S.M., Ferreira A., Podda, A.S., Recupero, D.R., Sanna, A., Multi-DQN: An ensemble of Deep Q-learning agents for stock market forecasting (2021), Expert Systems with Applications
Barra. S., Carta, S.M., Corriga, A., Podda, A.S., Recupero, D.R., Deep learning and time series-To-image encoding for financial forecasting (2020), IEEE/CAA Journal of Automatica Sinica
Carta, S.M, Consoli, S., Piras, L., Podda, A.S., and Recupero, D.R., Dynamic Industry- specific Lexicon Generation for Stock Market Forecast (2020), The Sixth International Conference on Machine Learning, Optimization, and Data Science
Carta, S.M., Corriga, A., Ferreira A., Podda, A.S., A Multi-Layer and Multi-Ensemble Stock Trader Using Deep Learning and Deep Reinforcement Learning (2020), Applied Intelligence
Carta, S.M., Recupero, D.R., Stanciu, M., Saia, R., A General Framework for Risk Controlled Trading Based on Machine Learning and Statistical Arbitrage (2020), The Sixth International Conference on Machine Learning, Optimization, and Data Science
Carta, S.M., Corriga, A., Ferreira, A., Recupero, D.R., Saia, R., A holistic auto-configurable ensemble machine learning strategy for financial trading (2019), Computation