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 (Tom Coupe) 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, Center for Economic Studies, U.S. Census Bureau, number 20-40, Dec.
• Jeremy Fouliard & Michael Howell & Hélène Rey & Vania Stavrakeva, 2020, "Answering the Queen: Machine Learning and Financial Crises," NBER Working Papers, National Bureau of Economic Research, Inc, number 28302, Dec.
• 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, National Bureau of Economic Research, Inc, number 28293, Dec.
• Sridhar Ravula, 2021, "Bankruptcy prediction using disclosure text features," Papers, arXiv.org, number 2101.00719, Jan.
• 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, Department of Economics and Business Economics, Aarhus University, number 2021-02, Jan.
• Kim Christensen & Mathias Siggaard & Bezirgen Veliyev, 2021, "A machine learning approach to volatility forecasting," CREATES Research Papers, Department of Economics and Business Economics, Aarhus University, number 2021-03, Jan.
• Kentaro Imajo & Kentaro Minami & Katsuya Ito & Kei Nakagawa, 2020, "Deep Portfolio Optimization via Distributional Prediction of Residual Factors," Papers, arXiv.org, number 2012.07245, Dec.
• Tamara, Novian & Dwi Muchisha, Nadya & Andriansyah, Andriansyah & Soleh, Agus M, 2020, "Nowcasting Indonesia’s GDP Growth Using Machine Learning Algorithms," MPRA Paper, University Library of Munich, Germany, number 105235, Jun.
• Kathrin Glau & Linus Wunderlich, 2020, "The Deep Parametric PDE Method: Application to Option Pricing," Papers, arXiv.org, number 2012.06211, Dec.
• Mykola Babiak & Jozef Barunik, 2020, "Deep Learning, Predictability, and Optimal Portfolio Returns," CERGE-EI Working Papers, The Center for Economic Research and Graduate Education - Economics Institute, Prague, number wp677, Dec.
• 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, Humboldt University Berlin, DFG Research Unit 2569 FORLand "Agricultural Land Markets – Efficiency and Regulation", number 22 (2020), DOI: 10.18452/21263.
• 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, Joint Research Centre, number JRC122675, Dec.
• 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 in an environment of uncertainty generated by the ," MPRA Paper, University Library of Munich, Germany, number 105133, Jan.
• Daniel Poh & Bryan Lim & Stefan Zohren & Stephen Roberts, 2020, "Building Cross-Sectional Systematic Strategies By Learning to Rank," Papers, arXiv.org, number 2012.07149, Dec.
• Yusuke NARITA & Shunsuke AIHARA & Yuta SAITO & Megumi MATSUTANI & Kohei YATA, 2020, "Machine Learning as Natural Experiment: Method and Deployment at Japanese Firms (Japanese)," Discussion Papers (Japanese), Research Institute of Economy, Trade and Industry (RIETI), number 20045, Dec.
• Fernando Martinez-Plumed & Emilia Gomez Gutierrez & Jose Hernandez-Orallo, 2020, "AI Watch Assessing Technology Readiness Levels for Artificial Intelligence," JRC Research Reports, Joint Research Centre, number JRC122014, Nov.
• Le Trung Hieu, 2020, "Deep Reinforcement Learning for Stock Portfolio Optimization," Papers, arXiv.org, number 2012.06325, Dec.
• 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, International Monetary Fund, number 2020/161, Aug.
• Naudé, Wim & Dimitri, Nicola, 2021, "Public Procurement and Innovation for Human-Centered Artificial Intelligence," IZA Discussion Papers, IZA Network @ LISER, number 14021, Jan.
• Andrew Bennett & Nathan Kallus, 2020, "The Variational Method of Moments," Papers, arXiv.org, number 2012.09422, Dec, revised Mar 2023.
• Jiequn Han & Ruimeng Hu, 2021, "Recurrent Neural Networks for Stochastic Control Problems with Delay," Papers, arXiv.org, number 2101.01385, Jan, 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), Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL), number 124660, Jan.
• 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, The World Bank Group, number 33387, Nov.
• Ziyuan Xia & Jeffery Chen & Anchen Sun, 2021, "Mining the Relationship Between COVID-19 Sentiment and Market Performance," Papers, arXiv.org, number 2101.02587, Jan, revised Mar 2023.
• Item repec:dar:wpaper:124702 is not listed on IDEAS anymore

• 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), Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL), number 124636, Jan.
• Xavier Warin, 2021, "Deep learning for efficient frontier calculation in finance," Papers, arXiv.org, number 2101.02044, Jan, revised Feb 2022.
• Mariano Zeron & Ignacio Ruiz, 2020, "Tensoring volatility calibration," Papers, arXiv.org, number 2012.07440, Dec, revised Dec 2020.

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 (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: