Report NEP-BIG-2020-11-16

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:

• Katsafados, Apostolos G. & Androutsopoulos, Ion & Chalkidis, Ilias & Fergadiotis, Manos & Leledakis, George N. & Pyrgiotakis, Emmanouil G., 2020. "Textual Information and IPO Underpricing: A Machine Learning Approach," MPRA Paper 103813, University Library of Munich, Germany.
• Michael Allan Ribers & Hannes Ullrich, 2020. "Machine Predictions and Human Decisions with Variation in Payoffs and Skills," Discussion Papers of DIW Berlin 1911, DIW Berlin, German Institute for Economic Research.
• Max H. Farrell & Tengyuan Liang & Sanjog Misra, 2020. "Deep Learning for Individual Heterogeneity: An Automatic Inference Framework," Papers 2010.14694, arXiv.org, revised Jul 2021.
• Amir Mukeri & Habibullah Shaikh & D. P. Gaikwad, 2020. "Financial Data Analysis Using Expert Bayesian Framework For Bankruptcy Prediction," Papers 2010.13892, arXiv.org, revised Oct 2020.
• Sidra Mehtab & Jaydip Sen, 2020. "Stock Price Prediction Using CNN and LSTM-Based Deep Learning Models," Papers 2010.13891, arXiv.org.
• Septimiu Szabo, 2020. "Transition to Industry 4.0 in the Visegrád Countries," European Economy - Economic Briefs 052, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
• Andrés Alonso & José Manuel Carbó, 2020. "Machine learning in credit risk: measuring the dilemma between prediction and supervisory cost," Working Papers 2032, Banco de España.
• Stefan Penczynski & Konrad Maliszewski & Andrew Fearne, 2020. "The impact of data visualisation on the use of shopper insight in the marketing decisionmaking of small food producers," Working Paper series, University of East Anglia, Centre for Behavioural and Experimental Social Science (CBESS) 20-05, School of Economics, University of East Anglia, Norwich, UK..
• Christiansen, T. & Weeks, M., 2020. "Distributional Aspects of Microcredit Expansions," Cambridge Working Papers in Economics 20100, Faculty of Economics, University of Cambridge.
• Elizabeth Fons & Paula Dawson & Xiao-jun Zeng & John Keane & Alexandros Iosifidis, 2020. "Evaluating data augmentation for financial time series classification," Papers 2010.15111, arXiv.org.
• Jon Ellingsen & Vegard H. Larsen & Leif Anders Thorsrud, 2020. "News Media vs. FRED-MD for Macroeconomic Forecasting," CESifo Working Paper Series 8639, CESifo.
• Richard Bluhm & Melanie Krause, 2020. "Top Lights: Bright cities and their contribution to economic development," SoDa Laboratories Working Paper Series 2020-08, Monash University, SoDa Laboratories.
• Sanghamitra Mukherjee, 2020. "Boosting Renewable Energy Technology Uptake in Ireland: A Machine Learning Approach," Working Papers 202027, School of Economics, University College Dublin.
• Waterschoot, Cedric, 2020. "The future of theory: should social protection board the big data train?," SocArXiv hmuva, Center for Open Science.
• Andrew B. Martinez, 2020. "Extracting Information from Different Expectations," Working Papers 2020-008, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
• Julia Cage & Nicolas Herve & Beatrice Mazoyer, 2020. "Social Media and Newsroom Production Decisions," Working Papers 20-14, NET Institute.
• Alvaro Gomez Losada & Montserrat Lopez-Cobo & Sofia Samoili & Georgios Alaveras & Miguel Vazquez-Prada Baillet & Melisande Cardona & Riccardo Righi & Lukasz Ziemba & Giuditta De-Prato, 2020. "Estimation of supply and demand of tertiary education places in advanced digital profiles in the EU: Focus on Artificial Intelligence, High Performance Computing, Cybersecurity and Data Science," JRC Research Reports JRC121683, Joint Research Centre.
• Perone, G., 2020. "Comparison of ARIMA, ETS, NNAR and hybrid models to forecast the second wave of COVID-19 hospitalizations in Italy," Health, Econometrics and Data Group (HEDG) Working Papers 20/18, HEDG, c/o Department of Economics, University of York.
• Item repec:iim:iimawp:14638 is not listed on IDEAS anymore

• Tae-Hwy Lee & Ekaterina Seregina, 2020. "Learning from Forecast Errors: A New Approach to Forecast Combination," Working Papers 202024, University of California at Riverside, Department of Economics.
• Nataliia Ostapenko, 2020. "Macroeconomic expectations: news sentiment analysis," Bank of Estonia Working Papers wp2020-5, Bank of Estonia, revised 13 Aug 2020.
• Stefan Kremsner & Alexander Steinicke & Michaela Szolgyenyi, 2020. "A deep neural network algorithm for semilinear elliptic PDEs with applications in insurance mathematics," Papers 2010.15757, arXiv.org, revised Dec 2020.
• Michael Ryan, 2020. "A Narrative Approach to Creating Instruments with Unstructured and Voluminous Text: An Application to Policy Uncertainty," Working Papers in Economics 20/10, University of Waikato.
• Faizaan Pervaiz & Christopher Goh & Ashley Pennington & Samuel Holt & James West & Shaun Ng, 2020. "Fear and Volatility in Digital Assets," Papers 2010.15611, arXiv.org.
• Xianchao Wu, 2020. "Event-Driven Learning of Systematic Behaviours in Stock Markets," Papers 2010.15586, arXiv.org.
• Antti J. Tanskanen, 2020. "Deep reinforced learning enables solving rich discrete-choice life cycle models to analyze social security reforms," Papers 2010.13471, arXiv.org, revised Feb 2022.
• Obradovich, Nick & Özak, Ömer & Martín, Ignacio & Ortuño-Ortín, Ignacio & Awad, Edmond & Cebrián, Manuel & Cuevas, Rubén & Desmet, Klaus & Rahwan, Iyad & Cuevas, Ángel, 2020. "Expanding the Measurement of Culture with a Sample of Two Billion Humans," GLO Discussion Paper Series 696, Global Labor Organization (GLO).
• Carmine De Franco & Johann Nicolle & Huy^en Pham, 2020. "Discrete-time portfolio optimization under maximum drawdown constraint with partial information and deep learning resolution," Papers 2010.15779, arXiv.org, revised Oct 2020.
• Alvarez, Santiago E. & Lein, Sarah M., 2020. "Tracking Inflation on a Daily Basis," Working papers 2020/16, Faculty of Business and Economics - University of Basel.
• Zhou, Alvin, 2020. "Communicating corporate LGBTQ advocacy: A computational comparison of the global CSR discourse," OSF Preprints gz7bw, Center for Open Science.