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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 (Tom Coupe) issued this report. It is usually issued weekly.Subscribe to this report: email, RSS, or Mastodon, or Bluesky.
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, National Bureau of Economic Research, Inc, number 26825, Mar.
- Weiwei Jiang, 2020, "Applications of deep learning in stock market prediction: recent progress," Papers, arXiv.org, number 2003.01859, Feb.
- Manav Kaushik & A K Giri, 2020, "Forecasting Foreign Exchange Rate: A Multivariate Comparative Analysis between Traditional Econometric, Contemporary Machine Learning & Deep Learning Techniques," Papers, arXiv.org, number 2002.10247, Feb.
- Pietro Battiston & Simona Gamba & Alessandro Santoro, 2020, "Optimizing Tax Administration Policies with Machine Learning," Working Papers, University of Milano-Bicocca, Department of Economics, number 436, Mar, revised Mar 2020.
- Parisa Golbayani & Dan Wang & Ionut Florescu, 2020, "Application of Deep Neural Networks to assess corporate Credit Rating," Papers, arXiv.org, number 2003.02334, Mar.
- Item repec:imf:imfwpa:20/44 is not listed on IDEAS anymore
- Item repec:imf:imfwpa:20/45 is not listed on IDEAS anymore
- Steven Y. K. Wong & Jennifer Chan & Lamiae Azizi & Richard Y. D. Xu, 2020, "Time-varying neural network for stock return prediction," Papers, arXiv.org, number 2003.02515, Mar, 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, Joint Research Centre, number JRC118163, Feb.
- Shubhankar Mohapatra & Nauman Ahmed & Paulo Alencar, 2020, "KryptoOracle: A Real-Time Cryptocurrency Price Prediction Platform Using Twitter Sentiments," Papers, arXiv.org, number 2003.04967, Feb.
- Zura Kakushadze & Willie Yu, 2020, "Machine Learning Treasury Yields," Papers, arXiv.org, number 2003.05095, Mar.
- Micah Goldblum & Avi Schwarzschild & Ankit B. Patel & Tom Goldstein, 2020, "Adversarial Attacks on Machine Learning Systems for High-Frequency Trading," Papers, arXiv.org, number 2002.09565, Feb, revised Oct 2021.
- Ana Thaís Martínez & Luis M. Torres, 2019, "Compras públicas y Big Data : El caso mexicano," Informes de Investigación, Fedesarrollo, number 17928, Jul.
- Paolo Brunori & Guido Neidhofer, 2020, "The Evolution of Inequality of Opportunity in Germany: A Machine Learning Approach," CEDLAS, Working Papers, CEDLAS, Universidad Nacional de La Plata, number 0259, Mar.
- Chengyuan Zhang & Fuxin Jiang & Shouyang Wang & Shaolong Sun, 2020, "A New Decomposition Ensemble Approach for Tourism Demand Forecasting: Evidence from Major Source Countries," Papers, arXiv.org, number 2002.09201, Feb.
- Miguel Jorquera, 2019, "Compras públicas y Big Data : Investigación en Chile sobre índice de riesgo de corrupción," Informes de Investigación, Fedesarrollo, number 17924, Jul.
- 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, The World Bank, number 8756, Feb.
- Pablo Montes M., 2019, "Nota Técnica Regional : Compras públicas y Big Data," Informes de Investigación, Fedesarrollo, number 17926, Jul.
- Vincent Van Roy, 2020, "AI Watch - National strategies on Artificial Intelligence: A European perspective in 2019," JRC Research Reports, Joint Research Centre, number JRC119974, Feb.
- Oksana Bashchenko & Alexis Marchal, 2020, "Deep Learning for Asset Bubbles Detection," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 20-08, Mar.
- Oksana Bashchenko & Alexis Marchal, 2020, "Deep Learning, Jumps, and Volatility Bursts," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 20-10, Mar.
- Ben Moews & Gbenga Ibikunle, 2020, "Predictive intraday correlations in stable and volatile market environments: Evidence from deep learning," Papers, arXiv.org, number 2002.10385, Feb.
- 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, Joint Research Centre, number JRC120106, Feb.
- Pape,Utz Johann & Wollburg,Philip Randolph, 2019, "Estimation of Poverty in Somalia Using Innovative Methodologies," Policy Research Working Paper Series, The World Bank, number 8735, Feb.
- Özkes, Ali & Hanaki, Nobuyuki, 2020, "Talkin' Bout Cooperation," Department for Strategy and Innovation Working Paper Series, WU Vienna University of Economics and Business, number 08/2020, Mar.
- Montobbio, Fabio & Staccioli, Jacopo & Virgillito, Maria Enrica & Vivarelli, Marco, 2020, "Robots and the Origin of Their Labour-Saving Impact," IZA Discussion Papers, IZA Network @ LISER, number 12967, Feb.
- 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, arXiv.org, number 2002.09656, Feb.
- James Wallbridge, 2020, "Transformers for Limit Order Books," Papers, arXiv.org, number 2003.00130, Feb.
- Paul Hubert & Fabien Labondance, 2020, "Central Bank Tone and the Dispersion of Views within Monetary Policy Committees," Documents de Travail de l'OFCE, Observatoire Francais des Conjonctures Economiques (OFCE), number 2020-02, Jan.
- Yuri F. Saporito & Zhaoyu Zhang, 2020, "PDGM: a Neural Network Approach to Solve Path-Dependent Partial Differential Equations," Papers, arXiv.org, number 2003.02035, Mar, revised Apr 2020.