Report NEP-BIG-2020-03-23

This is the archive for NEP-BIG, a report on new working papers in the area of Big Data. Tom Coupé issued this report. It is usually issued weekly.

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Other reports in NEP-BIG

The following items were announced in this report:

• Francesco Giavazzi & Felix Iglhaut & Giacomo Lemoli & Gaia Rubera, 2020. "Terrorist Attacks, Cultural Incidents and the Vote for Radical Parties: Analyzing Text from Twitter," NBER Working Papers 26825, National Bureau of Economic Research, Inc.
• Weiwei Jiang, 2020. "Applications of deep learning in stock market prediction: recent progress," Papers 2003.01859, arXiv.org.
• Manav Kaushik & A K Giri, 2020. "Forecasting Foreign Exchange Rate: A Multivariate Comparative Analysis between Traditional Econometric, Contemporary Machine Learning & Deep Learning Techniques," Papers 2002.10247, arXiv.org.
• Pietro Battiston & Simona Gamba & Alessandro Santoro, 2020. "Optimizing Tax Administration Policies with Machine Learning," Working Papers 436, University of Milano-Bicocca, Department of Economics, revised Mar 2020.
• Parisa Golbayani & Dan Wang & Ionut Florescu, 2020. "Application of Deep Neural Networks to assess corporate Credit Rating," Papers 2003.02334, arXiv.org.
• Marijn A. Bolhuis & Brett Rayner, 2020. "The More the Merrier? A Machine Learning Algorithm for Optimal Pooling of Panel Data," IMF Working Papers 20/44, International Monetary Fund.
• Marijn A. Bolhuis & Brett Rayner, 2020. "Deus ex Machina? A Framework for Macro Forecasting with Machine Learning," IMF Working Papers 20/45, International Monetary Fund.
• Steven Y. K. Wong & Jennifer Chan & Lamiae Azizi & Richard Y. D. Xu, 2020. "Time-varying neural network for stock return prediction," Papers 2003.02515, arXiv.org, revised Jan 2021.
• Sofia Samoili & Montserrat Lopez Cobo & Emilia Gomez & Giuditta De Prato & Fernando Martinez-Plumed & Blagoj Delipetrev, 2020. "AI Watch. Defining Artificial Intelligence. Towards an operational definition and taxonomy of artificial intelligence," JRC Research Reports JRC118163, Joint Research Centre.
• Shubhankar Mohapatra & Nauman Ahmed & Paulo Alencar, 2020. "KryptoOracle: A Real-Time Cryptocurrency Price Prediction Platform Using Twitter Sentiments," Papers 2003.04967, arXiv.org.
• Zura Kakushadze & Willie Yu, 2020. "Machine Learning Treasury Yields," Papers 2003.05095, arXiv.org.
• Micah Goldblum & Avi Schwarzschild & Ankit B. Patel & Tom Goldstein, 2020. "Adversarial Attacks on Machine Learning Systems for High-Frequency Trading," Papers 2002.09565, arXiv.org, revised Oct 2021.
• Ana Thaís Martínez & Luis M. Torres, 2019. "Compras públicas y Big Data : El caso mexicano," Informes de Investigación 17928, Fedesarrollo.
• Paolo Brunori & Guido Neidhofer, 2020. "The Evolution of Inequality of Opportunity in Germany: A Machine Learning Approach," CEDLAS, Working Papers 0259, CEDLAS, Universidad Nacional de La Plata.
• Chengyuan Zhang & Fuxin Jiang & Shouyang Wang & Shaolong Sun, 2020. "A New Decomposition Ensemble Approach for Tourism Demand Forecasting: Evidence from Major Source Countries," Papers 2002.09201, arXiv.org.
• Miguel Jorquera, 2019. "Compras públicas y Big Data : Investigación en Chile sobre índice de riesgo de corrupción," Informes de Investigación 17924, Fedesarrollo.
• Andree,Bo Pieter Johannes & Spencer,Phoebe Girouard & Chamorro,Andres & Dogo,Harun, 2019. "Environment and Development : Penalized Non-Parametric Inference of Global Trends in Deforestation, Pollution and Carbon," Policy Research Working Paper Series 8756, The World Bank.
• Pablo Montes M., 2019. "Nota Técnica Regional : Compras públicas y Big Data," Informes de Investigación 17926, Fedesarrollo.
• Vincent Van Roy, 2020. "AI Watch - National strategies on Artificial Intelligence: A European perspective in 2019," JRC Research Reports JRC119974, Joint Research Centre.
• Oksana Bashchenko & Alexis Marchal, 2020. "Deep Learning for Asset Bubbles Detection," Swiss Finance Institute Research Paper Series 20-08, Swiss Finance Institute.
• Oksana Bashchenko & Alexis Marchal, 2020. "Deep Learning, Jumps, and Volatility Bursts," Swiss Finance Institute Research Paper Series 20-10, Swiss Finance Institute.
• Ben Moews & Gbenga Ibikunle, 2020. "Predictive intraday correlations in stable and volatile market environments: Evidence from deep learning," Papers 2002.10385, arXiv.org.
• Sofia Samoili & Riccardo Righi & Melisande Cardona & Montserrat Lopez-Cobo & Miguel Vazquez-Prada Baillet & Giuditta De-Prato, 2020. "TES analysis of AI Worldwide Ecosystem in 2009-2018," JRC Research Reports JRC120106, Joint Research Centre.
• Pape,Utz Johann & Wollburg,Philip Randolph, 2019. "Estimation of Poverty in Somalia Using Innovative Methodologies," Policy Research Working Paper Series 8735, The World Bank.
• Özkes, Ali & Hanaki, Nobuyuki, 2020. "Talkin' Bout Cooperation," Department for Strategy and Innovation Working Paper Series 08/2020, WU Vienna University of Economics and Business.
• Montobbio, Fabio & Staccioli, Jacopo & Virgillito, Maria Enrica & Vivarelli, Marco, 2020. "Robots and the Origin of Their Labour-Saving Impact," IZA Discussion Papers 12967, Institute of Labor Economics (IZA).
• Yang Yifan & Guo Ju'e & Sun Shaolong & Li Yixin, 2020. "A new hybrid approach for crude oil price forecasting: Evidence from multi-scale data," Papers 2002.09656, arXiv.org.
• James Wallbridge, 2020. "Transformers for Limit Order Books," Papers 2003.00130, arXiv.org.
• Paul Hubert & Fabien Labondance, 2020. "Central Bank Tone and the Dispersion of Views within Monetary Policy Committees," Documents de Travail de l'OFCE 2020-02, Observatoire Francais des Conjonctures Economiques (OFCE).
• Yuri F. Saporito & Zhaoyu Zhang, 2020. "PDGM: a Neural Network Approach to Solve Path-Dependent Partial Differential Equations," Papers 2003.02035, arXiv.org, revised Apr 2020.