Report NEP-BIG-2021-06-28

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.

Subscribe to this report: email, RSS, or Mastodon.

Other reports in NEP-BIG

The following items were announced in this report:

• Victor Klockmann & Alicia von Schenk & Marie Claire Villeval, 2021. "Artificial Intelligence, Ethics, and Diffused Pivotality," Working Papers halshs-03237453, HAL.
• Liping Yang, 2021. "Next-Day Bitcoin Price Forecast Based on Artificial intelligence Methods," Papers 2106.12961, arXiv.org.
• Katsafados, Apostolos G. & Leledakis, George N. & Pyrgiotakis, Emmanouil G. & Androutsopoulos, Ion & Fergadiotis, Manos, 2021. "Machine Learning in U.S. Bank Merger Prediction: A Text-Based Approach," MPRA Paper 108272, University Library of Munich, Germany.
• Juranek, Steffen & Otneim, Håkon, 2021. "Using machine learning to predict patent lawsuits," Discussion Papers 2021/6, Norwegian School of Economics, Department of Business and Management Science.
• Liao Zhu & Haoxuan Wu & Martin T. Wells, 2021. "A News-based Machine Learning Model for Adaptive Asset Pricing," Papers 2106.07103, arXiv.org.
• Ivan Fursov & Matvey Morozov & Nina Kaploukhaya & Elizaveta Kovtun & Rodrigo Rivera-Castro & Gleb Gusev & Dmitry Babaev & Ivan Kireev & Alexey Zaytsev & Evgeny Burnaev, 2021. "Adversarial Attacks on Deep Models for Financial Transaction Records," Papers 2106.08361, arXiv.org.
• Toru Kitagawa & Shosei Sakaguchi & Aleksey Tetenov, 2021. "Constrained Classification and Policy Learning," Papers 2106.12886, arXiv.org, revised Jul 2023.
• Jordan Vazquez & Cécile Godé & Jean-Fabrice Lebraty, 2021. "Environnement big data et prise de décision : maintien de l'ordre durant un évènement sportif d'ampleur," Post-Print hal-03252399, HAL.
• Florian Eckerli & Joerg Osterrieder, 2021. "Generative Adversarial Networks in finance: an overview," Papers 2106.06364, arXiv.org, revised Jul 2021.
• Hengxu Lin & Dong Zhou & Weiqing Liu & Jiang Bian, 2021. "Learning Multiple Stock Trading Patterns with Temporal Routing Adaptor and Optimal Transport," Papers 2106.12950, arXiv.org, revised Jun 2021.
• Muyang Ge & Shen Zhou & Shijun Luo & Boping Tian, 2021. "3D Tensor-based Deep Learning Models for Predicting Option Price," Papers 2106.02916, arXiv.org, revised Sep 2021.
• Victor Klockmann & Alicia von Schenk & Marie Claire Villeval, 2021. "Artificial Intelligence, Ethics, and Intergenerational Responsibility," Working Papers halshs-03237437, HAL.
• Vipul Satone & Dhruv Desai & Dhagash Mehta, 2021. "Fund2Vec: Mutual Funds Similarity using Graph Learning," Papers 2106.12987, arXiv.org.
• Izumi Yamashita & Akiyoshi Murakami & Stephanie Cairns & Fernando Galindo-Rueda, 2021. "Measuring the AI content of government-funded R&D projects: A proof of concept for the OECD Fundstat initiative," OECD Science, Technology and Industry Working Papers 2021/09, OECD Publishing.
• Vincent Van Roy & Fiammetta Rossetti & Karine Perset & Laura Galindo-Romero, 2021. "AI Watch - National strategies on Artificial Intelligence: A European perspective, 2021 edition," JRC Research Reports JRC122684, Joint Research Centre.
• Jaydip Sen & Sidra Mehtab, 2021. "Design and Analysis of Robust Deep Learning Models for Stock Price Prediction," Papers 2106.09664, arXiv.org.
• Goller, Daniel & Harrer, Tamara & Lechner, Michael & Wolff, Joachim, 2021. "Active labour market policies for the long-term unemployed: New evidence from causal machine learning," Economics Working Paper Series 2108, University of St. Gallen, School of Economics and Political Science.
• Anand Deo & Karthyek Murthy, 2021. "Efficient Black-Box Importance Sampling for VaR and CVaR Estimation," Papers 2106.10236, arXiv.org.
• Kamaladdin Fataliyev & Aneesh Chivukula & Mukesh Prasad & Wei Liu, 2021. "Stock Market Analysis with Text Data: A Review," Papers 2106.12985, arXiv.org, revised Jul 2021.
• Oecd, 2021. "Tools for trustworthy AI: A framework to compare implementation tools for trustworthy AI systems," OECD Digital Economy Papers 312, OECD Publishing.
• Daniel Goller & Tamara Harrer & Michael Lechner & Joachim Wolff, 2021. "Active labour market policies for the long-term unemployed: New evidence from causal machine learning," Papers 2106.10141, arXiv.org, revised May 2023.
• Wenyong Zhang & Lingfei Li & Gongqiu Zhang, 2021. "A Two-Step Framework for Arbitrage-Free Prediction of the Implied Volatility Surface," Papers 2106.07177, arXiv.org, revised Jan 2022.
• Nektarios Aslanidis & Aurelio F. Bariviera & 'Oscar G. L'opez, 2021. "The link between Bitcoin and Google Trends attention," Papers 2106.07104, arXiv.org.
• Daniel Aaronson & Scott A. Brave & R. Andrew Butters & Daniel Sacks & Boyoung Seo, 2020. "Using the Eye of the Storm to Predict the Wave of Covid-19 UI Claims," Working Paper Series WP-2020-10, Federal Reserve Bank of Chicago, revised 16 Apr 2020.
• Shohei Ohsawa, 2021. "Truthful Self-Play," Papers 2106.03007, arXiv.org, revised Feb 2023.
• Monica Pratesi & Claudio Ceccarelli & Stefano Menghinello, 2021. "Citizen-Generated Data and Official Statistics: an application to SDG indicators," Discussion Papers 2021/274, Dipartimento di Economia e Management (DEM), University of Pisa, Pisa, Italy.
• Meena Jagadeesan & Celestine Mendler-Dunner & Moritz Hardt, 2021. "Alternative Microfoundations for Strategic Classification," Papers 2106.12705, arXiv.org.
• Maciej Berk{e}sewicz & Dagmara Nikulin & Marcin Szymkowiak & Kamil Wilak, 2021. "The gig economy in Poland: evidence based on mobile big data," Papers 2106.12827, arXiv.org.
• Mathieu Mercadier & Jean-Pierre Lardy, 2021. "Credit spread approximation and improvement using random forest regression," Papers 2106.07358, arXiv.org.
• Long Chen & Yadong Huang & Shumiao Ouyang & Wei Xiong, 2021. "The Data Privacy Paradox and Digital Demand," NBER Working Papers 28854, National Bureau of Economic Research, Inc.
• Zach Y. Brown & Alexander MacKay, 2021. "Competition in Pricing Algorithms," NBER Working Papers 28860, National Bureau of Economic Research, Inc.
• Newland, Carlos & Rosiello, Juan Carlos & Salinas, Roberto, 2021. "Influencers on Economic Issues in Latin America, Spain and the United States – II," Studies in Applied Economics 183, The Johns Hopkins Institute for Applied Economics, Global Health, and the Study of Business Enterprise.