Report NEP-BIG-2022-04-04

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:

• Giuseppe Cascarino & Mirko Moscatelli & Fabio Parlapiano, 2022. "Explainable Artificial Intelligence: interpreting default forecasting models based on Machine Learning," Questioni di Economia e Finanza (Occasional Papers) 674, Bank of Italy, Economic Research and International Relations Area.
• Chao Zhang & Yihuang Zhang & Mihai Cucuringu & Zhongmin Qian, 2022. "Volatility forecasting with machine learning and intraday commonality," Papers 2202.08962, arXiv.org, revised Feb 2023.
• Rian Dolphin & Barry Smyth & Ruihai Dong, 2022. "Stock Embeddings: Learning Distributed Representations for Financial Assets," Papers 2202.08968, arXiv.org.
• Keil, Petr & Chase, Jonathan, 2022. "Interpolation of temporal biodiversity change, loss, and gain across scales: a machine learning approach," EcoEvoRxiv rky7b, Center for Open Science.
• Mukund Sundararajan & Walid Krichene, 2022. "Reciprocity in Machine Learning," Papers 2202.09480, arXiv.org.
• Jurić, Tado, 2022. "Predicting refugee flows from Ukraine with an approach to Big (Crisis) Data: a new opportunity for refugee and humanitarian studies," EconStor Preprints 251215, ZBW - Leibniz Information Centre for Economics.
• Damir Filipović & Markus Pelger & Ye Ye, 2022. "Stripping the Discount Curve - a Robust Machine Learning Approach," Swiss Finance Institute Research Paper Series 22-24, Swiss Finance Institute.
• Andrés Fernández Díaz & Benito Rodríguez Mallol, 2022. "Inteligencia artificial: una reevaluación," Documentos de trabajo de la Facultad de Ciencias Económicas y Empresariales 22-01, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales.
• Amir Taherizadeh & Catherine Beaudry, 2022. "Vers une meilleure compréhension de la transformation numérique optimisée par l’IA et de ses implications pour les PME manufacturières au Canada - Une recherche qualitative exploratoire," CIRANO Project Reports 2022rp-04, CIRANO.
• Luca Coraggio & Marco Pagano & Annalisa Scognamiglio & Joacim Tåg, 2022. "JAQ of All Trades: Job Mismatch, Firm Productivity and Managerial Quality," CSEF Working Papers 641, Centre for Studies in Economics and Finance (CSEF), University of Naples, Italy, revised 24 Oct 2022.
• Matthias Lalisse, 2022. "Measuring the Impact of Campaign Finance on Congressional Voting: A Machine Learning Approach," Working Papers Series inetwp178, Institute for New Economic Thinking.
• Kristof Wiedermann, 2022. "An SMP-Based Algorithm for Solving the Constrained Utility Maximization Problem via Deep Learning," Papers 2202.07771, arXiv.org.
• Igna, Ioana & Venturini, Francesco, 2022. "The determinants of AI innovation across European firms," Papers in Innovation Studies 2022/3, Lund University, CIRCLE - Centre for Innovation Research.
• De Castro, Angelo, 2022. "The Ebb of Fiat and the Flow of Cryptocurrency," OSF Preprints trpwc, Center for Open Science.
• DUCH BROWN Nestor & GOMEZ-HERRERA Estrella & MUELLER-LANGER Frank & TOLAN Songul, 2022. "Market Power and Artificial Intelligence Work on Online Labour Markets," JRC Working Papers on Digital Economy 2021-10, Joint Research Centre.
• Kvam, Emilie & Molnar, Peter & Wankel, Ingvild & Odegaard, Bernt Arne, 2022. "Do sustainable company stock prices increase with ESG scrutiny? Evidence using social media," UiS Working Papers in Economics and Finance 2022/1, University of Stavanger.
• Harold Houba & Evgenia Motchenkova & Hui Wang, 2022. "Personalized Pricing, Competition and Welfare," Tinbergen Institute Discussion Papers 22-020/VII, Tinbergen Institute.