Report NEP-BIG-2020-08-24

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:

• Hellerstein, Judith K. & Neumark, David, 2020. "Social Capital, Networks, and Economic Wellbeing," IZA Discussion Papers 13413, Institute of Labor Economics (IZA).
• Ivan Slobozhan & Peter Ormosi & Rajesh Sharma, 2020. "Which bills are lobbied? Predicting and interpreting lobbying activity in the US," Working Paper series, University of East Anglia, Centre for Competition Policy (CCP) 2020-03, Centre for Competition Policy, University of East Anglia, Norwich, UK..
• Yang Li & Yi Pan, 2020. "A Novel Ensemble Deep Learning Model for Stock Prediction Based on Stock Prices and News," Papers 2007.12620, arXiv.org.
• Henri Bourdeau & Corentin Petit & Christophe Midler, 2019. "Du concept à la mise en œuvre du machine learning dans les entreprises : L'expérience de Datapred," Post-Print hal-02873935, HAL.
• Yongtong Shao & Minghao Li & Dermot J. Hayes & Wendong Zhang & Tao Xiong & Wei Xie, 2020. "China's Missing Pigs: Correcting China's Hog Inventory Data Using a Machine Learning Approach," Center for Agricultural and Rural Development (CARD) Publications 20-wp607, Center for Agricultural and Rural Development (CARD) at Iowa State University.
• Marcin Chlebus & Michał Dyczko & Michał Woźniak, 2020. "Nvidia’s stock returns prediction using machine learning techniques for time series forecasting problem," Working Papers 2020-22, Faculty of Economic Sciences, University of Warsaw.
• Dominique Guegan, 2020. "A Note on the Interpretability of Machine Learning Algorithms," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-02900929, HAL.
• Dominique Guégan, 2020. "A Note on the Interpretability of Machine Learning Algorithms," Documents de travail du Centre d'Economie de la Sorbonne 20012, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
• Longbing Cao & Qiang Yang & Philip S. Yu, 2020. "Data science and AI in FinTech: An overview," Papers 2007.12681, arXiv.org, revised Jul 2021.
• A. R. Provenzano & D. Trifir`o & A. Datteo & L. Giada & N. Jean & A. Riciputi & G. Le Pera & M. Spadaccino & L. Massaron & C. Nordio, 2020. "Machine Learning approach for Credit Scoring," Papers 2008.01687, arXiv.org.
• von Essen, Emma & Jansson, Joakim, 2020. "Misogynistic and xenophobic hate language online: a matter of anonymity," Working Paper Series 7/2020, Stockholm University, Swedish Institute for Social Research.
• K., Sai Manoj & Aithal, Sreeramana, 2020. "Data Mining and Machine Learning Techniques for Cyber Security Intrusion Detection," MPRA Paper 101753, University Library of Munich, Germany.
• Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & St'ephane Surprenant, 2020. "Macroeconomic Data Transformations Matter," Papers 2008.01714, arXiv.org, revised Mar 2021.
• Neng-Chieh Chang, 2020. "The Mode Treatment Effect," Papers 2007.11606, arXiv.org.
• Anindya Goswami & Sharan Rajani & Atharva Tanksale, 2020. "Data-Driven Option Pricing using Single and Multi-Asset Supervised Learning," Papers 2008.00462, arXiv.org, revised Dec 2020.
• Augusto Cerqua & Roberta Di Stefano & Marco Letta & Sara Miccoli, 2020. "Local mortality estimates during the COVID-19 pandemic in Italy," Working Papers 14/20, Sapienza University of Rome, DISS.
• María Florencia Camusso & Ramiro Emmanuel Jorge, 2019. "Google Correlate y Google Trends como herramientas para realizar un nowcast de las ventas minoristas," Asociación Argentina de Economía Política: Working Papers 4127, Asociación Argentina de Economía Política.
• Prat, Andrea & Montiel Olea , José Luis & Ortoleva, Pietro & Pai, Mallesh, 2019. "Competing Models," CEPR Discussion Papers 14066, C.E.P.R. Discussion Papers.
• Heni Boubaker & Giorgio Canarella & Rangan Gupta & Stephen M. Miller, 2020. "Hybrid ARFIMA Wavelet Artificial Neural Network Model for DJIA Index Forecasting," Working papers 2020-10, University of Connecticut, Department of Economics.
• Illya Barziy & Marcin Chlebus, 2020. "HRP performance comparison in portfolio optimization under various codependence and distance metrics," Working Papers 2020-21, Faculty of Economic Sciences, University of Warsaw.
• Zhongfang Zhuang & Chin-Chia Michael Yeh & Liang Wang & Wei Zhang & Junpeng Wang, 2020. "Multi-stream RNN for Merchant Transaction Prediction," Papers 2008.01670, arXiv.org.
• Chao Deng & Xizhi Su & Chao Zhou, 2020. "Relative wealth concerns with partial information and heterogeneous priors," Papers 2007.11781, arXiv.org.
• Munoz,Juan Eduardo & Gallegos Munoz,Jose Victor & Olivieri,Sergio Daniel, 2020. "Big Data for Sampling Design : The Venezuelan Migration Crisis in Ecuador," Policy Research Working Paper Series 9329, The World Bank.
• Kwadwo Osei Bonsu, 2020. "Weighted Accuracy Algorithmic Approach In Counteracting Fake News And Disinformation," Papers 2008.01535, arXiv.org, revised Aug 2020.
• Alessandro Gnoatto & Athena Picarelli & Christoph Reisinger, 2020. "Deep xVA solver - A neural network based counterparty credit risk management framework," Working Papers 07/2020, University of Verona, Department of Economics.