Report NEP-BIG-2020-10-26

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:

• Saeed Nosratabadi & Amir Mosavi & Ramin Keivani & Sina Ardabili & Farshid Aram, 2020. "State of the Art Survey of Deep Learning and Machine Learning Models for Smart Cities and Urban Sustainability," Papers 2010.02670, arXiv.org.
• Sidra Mehtab & Jaydip Sen & Abhishek Dutta, 2020. "Stock Price Prediction Using Machine Learning and LSTM-Based Deep Learning Models," Papers 2009.10819, arXiv.org.
• Ya Chen & Mike Tsionas & Valentin Zelenyuk, 2020. "LASSO DEA for small and big data," CEPA Working Papers Series WP092020, School of Economics, University of Queensland, Australia.
• Hannes Mueller & Andre Groger & Jonathan Hersh & Andrea Matranga & Joan Serrat, 2020. "Monitoring War Destruction from Space: A Machine Learning Approach," Papers 2010.05970, arXiv.org, revised Oct 2020.
• Cosimo Magazzino & Marco Mele & Nicolas Schneider & Guillaume Vallet, 2020. "The relationship between nuclear energy consumption and economic growth: evidence from Switzerland," Post-Print halshs-02951860, HAL.
• Thomas Dierckx & Jesse Davis & Wim Schoutens, 2020. "Using Machine Learning and Alternative Data to Predict Movements in Market Risk," Papers 2009.07947, arXiv.org.
• Anastasios Petropoulos & Vassilis Siakoulis & Konstantinos P. Panousis & Loukas Papadoulas & Sotirios Chatzis, 2020. "A Deep Learning Approach for Dynamic Balance Sheet Stress Testing," Papers 2009.11075, arXiv.org, revised Sep 2022.
• Guido de Blasio & Alessio D'Ignazio & Marco Letta, 2020. "Predicting Corruption Crimes with Machine Learning. A Study for the Italian Municipalities," Working Papers 16/20, Sapienza University of Rome, DISS.
• Steven J. Davis & Stephen Hansen & Cristhian Seminario-Amez, 2020. "Firm-Level Risk Exposures and Stock Returns in the Wake of Covid-19," CESifo Working Paper Series 8594, CESifo.
• Olivier Darné & Amelie Charles, 2020. "Nowcasting GDP growth using data reduction methods: Evidence for the French economy," Post-Print hal-02948802, HAL.
• Albarrán, Irene & Molina, José Manuel & Gijón, Covadonga, 2020. "Perception of Artificial Intelligence in Spain," ITS Conference, Online Event 2020 224843, International Telecommunications Society (ITS).
• Junfeng Hu & Xiaosa Li & Yuru Xu & Shaowu Wu & Bin Zheng, 2020. "Evaluation of company investment value based on machine learning," Papers 2010.01996, arXiv.org.
• Andreas Gulyas & Krzysztof Pytka, 2020. "The Consequences of the COVID-19 Job Losses: Who Will Suffer Most and by How Much?," CRC TR 224 Discussion Paper Series crctr224_2020_212, University of Bonn and University of Mannheim, Germany.
• Pedro M. Gardete & Carlos D. Santos, 2020. "No data? No problem! A Search-based Recommendation System with Cold Starts," Papers 2010.03455, arXiv.org.
• Grzegorz Krochmal, 2020. "Sentiment of tweets and socio-economic characteristics as the determinants of voting behavior at the regional level. Case study of 2019 Polish parliamentary election," Papers 2010.03493, arXiv.org.
• Xing Wang & Yijun Wang & Bin Weng & Aleksandr Vinel, 2020. "Stock2Vec: A Hybrid Deep Learning Framework for Stock Market Prediction with Representation Learning and Temporal Convolutional Network," Papers 2010.01197, arXiv.org.
• Hamed Vaheb, 2020. "Asset Price Forecasting using Recurrent Neural Networks," Papers 2010.06417, arXiv.org, revised Oct 2020.
• Bruno Spilak & Wolfgang Karl Hardle, 2020. "Tail-risk protection: Machine Learning meets modern Econometrics," Papers 2010.03315, arXiv.org, revised Aug 2021.
• Oskar KOWALEWSKI & Paweł PISANY, 2020. "The Rise of Fintech: A Cross-Country Perspective," Working Papers 2020-ACF-07, IESEG School of Management.
• Susanto, Stefanny Magdalena, 2020. "Influence of big data and analysis of orientation effect on firm performance," OSF Preprints sjdpf, Center for Open Science.
• Artur Sokolovsky & Luca Arnaboldi, 2020. "A Generic Methodology for the Statistically Uniform & Comparable Evaluation of Automated Trading Platform Components," Papers 2009.09993, arXiv.org, revised Jun 2022.
• Andrew Clark, 2020. "A Pound Centric look at the Pound vs. Krona Exchange Rate Movement from 1844 to 1965," Economics Discussion Papers em-dp2020-22, Department of Economics, University of Reading.
• Bernhardt, Lea, 2020. "Common factors of withdrawn and prohibited mergers in the European Union," Working Paper 184/2020, Helmut Schmidt University, Hamburg.
• Qi Zhao, 2020. "A Deep Learning Framework for Predicting Digital Asset Price Movement from Trade-by-trade Data," Papers 2010.07404, arXiv.org.
• Joshua Wilde & Wei Chen & Sophie Lohmann, 2020. "COVID-19 and the future of US fertility: what can we learn from Google?," MPIDR Working Papers WP-2020-034, Max Planck Institute for Demographic Research, Rostock, Germany.
• Avinash Collis & Alex Moehring & Ananya Sen, 2020. "Economic Value of Data: Quantification Using Online Experiments," Working Papers 20-13, NET Institute.
• Kluge, Jan & Lappoehn, Sarah & Plank, Kerstin, 2020. "The Determinants of Economic Competitiveness," IHS Working Paper Series 24, Institute for Advanced Studies.