Report NEP-BIG-2021-01-25

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:

• Nikolas Zolas & Zachary Kroff & Erik Brynjolfsson & Kristina McElheran & David Beede & Catherine Buffington & Nathan Goldschlag & Lucia Foster & Emin Dinlersoz, 2020. "Advanced Technologies Adoption and Use by U.S. Firms: Evidence from the Annual Business Survey," Working Papers 20-40, Center for Economic Studies, U.S. Census Bureau.
• Jeremy Fouliard & Michael Howell & Hélène Rey & Vania Stavrakeva, 2020. "Answering the Queen: Machine Learning and Financial Crises," NBER Working Papers 28302, National Bureau of Economic Research, Inc.
• Jeffrey Grogger & Sean Gupta & Ria Ivandic & Tom Kirchmaier, 2020. "Comparing Conventional and Machine-Learning Approaches to Risk Assessment in Domestic Abuse Cases," NBER Working Papers 28293, National Bureau of Economic Research, Inc.
• Sridhar Ravula, 2021. "Bankruptcy prediction using disclosure text features," Papers 2101.00719, arXiv.org.
• Daniel Borup & David E. Rapach & Erik Christian Montes Schütte, 2021. "Now- and Backcasting Initial Claims with High-Dimensional Daily Internet Search-Volume Data," CREATES Research Papers 2021-02, Department of Economics and Business Economics, Aarhus University.
• Kim Christensen & Mathias Siggaard & Bezirgen Veliyev, 2021. "A machine learning approach to volatility forecasting," CREATES Research Papers 2021-03, Department of Economics and Business Economics, Aarhus University.
• Kentaro Imajo & Kentaro Minami & Katsuya Ito & Kei Nakagawa, 2020. "Deep Portfolio Optimization via Distributional Prediction of Residual Factors," Papers 2012.07245, arXiv.org.
• Tamara, Novian & Dwi Muchisha, Nadya & Andriansyah, Andriansyah & Soleh, Agus M, 2020. "Nowcasting Indonesia’s GDP Growth Using Machine Learning Algorithms," MPRA Paper 105235, University Library of Munich, Germany.
• Kathrin Glau & Linus Wunderlich, 2020. "The Deep Parametric PDE Method: Application to Option Pricing," Papers 2012.06211, arXiv.org.
• Mykola Babiak & Jozef Barunik, 2020. "Deep Learning, Predictability, and Optimal Portfolio Returns," CERGE-EI Working Papers wp677, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
• Hinrichs, Nils & Kolbe, Jens & Werwatz, Axel, 2020. "AVM and high dimensional data: Do ridge, the lasso or the elastic net provide an "automated" solution?," FORLand Working Papers 22 (2020), Humboldt University Berlin, DFG Research Unit 2569 FORLand "Agricultural Land Markets – Efficiency and Regulation".
• DE NIGRIS Sarah & CRAGLIA Massimo & NEPELSKI Daniel & HRADEC Jiri & GOMEZ-GONZALES Emilio & GOMEZ GUTIERREZ Emilia & VAZQUEZ-PRADA BAILLET Miguel & RIGHI Riccardo & DE PRATO Giuditta & LOPEZ COBO Mont, 2020. "AI Watch : AI Uptake in Health and Healthcare, 2020," JRC Research Reports JRC122675, Joint Research Centre.
• Rodríguez-García, Jair Hissarly & Venegas-Martínez, Francisco, 2021. "Reducción de la brecha del crédito en México en un ambiente de incertidumbre generada por la pandemia COVID-19: Un enfoque de ciencia de datos (machine learning) [Reducing the credit gap in Mexico ," MPRA Paper 105133, University Library of Munich, Germany.
• Daniel Poh & Bryan Lim & Stefan Zohren & Stephen Roberts, 2020. "Building Cross-Sectional Systematic Strategies By Learning to Rank," Papers 2012.07149, arXiv.org.
• NARITA Yusuke & AIHARA Shunsuke & SAITO Yuta & MATSUTANI Megumi & YATA Kohei, 2020. "Machine Learning as Natural Experiment: Method and Deployment at Japanese Firms (Japanese)," Discussion Papers (Japanese) 20045, Research Institute of Economy, Trade and Industry (RIETI).
• Fernando Martinez-Plumed & Emilia Gomez Gutierrez & Jose Hernandez-Orallo, 2020. "AI Watch Assessing Technology Readiness Levels for Artificial Intelligence," JRC Research Reports JRC122014, Joint Research Centre.
• Le Trung Hieu, 2020. "Deep Reinforcement Learning for Stock Portfolio Optimization," Papers 2012.06325, arXiv.org.
• Mr. Arnoud W.A. Boot & Peter Hoffmann & Mr. Luc Laeven & Mr. Lev Ratnovski, 2020. "Financial Intermediation and Technology: What’s Old, What’s New?," IMF Working Papers 2020/161, International Monetary Fund.
• Naudé, Wim & Dimitri, Nicola, 2021. "Public Procurement and Innovation for Human-Centered Artificial Intelligence," IZA Discussion Papers 14021, Institute of Labor Economics (IZA).
• Andrew Bennett & Nathan Kallus, 2020. "The Variational Method of Moments," Papers 2012.09422, arXiv.org, revised Mar 2023.
• Jiequn Han & Ruimeng Hu, 2021. "Recurrent Neural Networks for Stochastic Control Problems with Delay," Papers 2101.01385, arXiv.org, revised Jun 2021.
• Pumplun, Luisa & Fecho, Mariska & Islam, Nihal & Buxmann, Peter, 2021. "Machine Learning Systems in Clinics – How Mature Is the Adoption Process in Medical Diagnostics?," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 124660, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
• Maria Lopez Conde & Ian Twinn, 2019. "How Artificial Intelligence is Making Transport Safer, Cleaner, More Reliable and Efficient in Emerging Markets," World Bank Publications - Reports 33387, The World Bank Group.
• Ziyuan Xia & Jeffery Chen & Anchen Sun, 2021. "Mining the Relationship Between COVID-19 Sentiment and Market Performance," Papers 2101.02587, arXiv.org, revised Mar 2023.
• Sturm, Timo & Fecho, Mariska & Buxmann, Peter, 2021. "To Use or Not to Use Artificial Intelligence? A Framework for the Ideation and Evaluation of Problems to Be Solved with Artificial Intelligence," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 124702, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
• Sturm, Timo & Fecho, Mariska & Buxmann, Peter, 2021. "To Use or Not to Use Artificial Intelligence? A Framework for the Ideation and Evaluation of Problems to Be Solved with Artificial Intelligence," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 124636, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
• Xavier Warin, 2021. "Deep learning for efficient frontier calculation in finance," Papers 2101.02044, arXiv.org, revised Feb 2022.
• Mariano Zeron & Ignacio Ruiz, 2020. "Tensoring volatility calibration," Papers 2012.07440, arXiv.org, revised Dec 2020.