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Report NEP-BIG-2023-10-09
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:
- Lawson,Cina & Koudeka, Morlé & Cardenas Martinez,Ana Lucia & Alberro Encinas,Luis Inaki & Karippacheril, Tina George, 2023, "Novissi Togo - Harnessing Artificial Intelligence to Deliver Shock-Responsive Social Protection," The Social Policy and Labor Discussion Paper Series, The World Bank, number 184975, Sep.
- Abir Sridi & Paul Bilokon, 2023, "Applying Deep Learning to Calibrate Stochastic Volatility Models," Papers, arXiv.org, number 2309.07843, Sep, revised Sep 2023.
- Luke Sanborn & Matthew Sahagun, 2023, "Media Moments and Corporate Connections: A Deep Learning Approach to Stock Movement Classification," Papers, arXiv.org, number 2309.06559, Sep.
- German Rodikov & Nino Antulov-Fantulin, 2023, "Introducing the $\sigma$-Cell: Unifying GARCH, Stochastic Fluctuations and Evolving Mechanisms in RNN-based Volatility Forecasting," Papers, arXiv.org, number 2309.01565, Sep.
- Christopher Bockel-Rickermann & Sam Verboven & Tim Verdonck & Wouter Verbeke, 2023, "A Causal Perspective on Loan Pricing: Investigating the Impacts of Selection Bias on Identifying Bid-Response Functions," Papers, arXiv.org, number 2309.03730, Sep.
- Tanvir Ahmed Khan, 2023, "Can Unbiased Predictive AI Amplify Bias?," Working Paper, Economics Department, Queen's University, number 1510, Jul.
- Sami Ben Jabeur & Rabeh Khalfaoui & Wissal Ben Arfi, 2021, "The effect of green energy, global environmental indexes, and stock markets in predicting oil price crashes: Evidence from explainable machine learning," Post-Print, HAL, number hal-03797577, Nov, DOI: 10.1016/j.jenvman.2021.113511.
- Mia Ellis & Cynthia Kinnan & Margaret S. McMillan & Sarah Shaukat, 2023, "What Predicts the Growth of Small Firms? Evidence from Tanzanian Commercial Loan Data," NBER Working Papers, National Bureau of Economic Research, Inc, number 31620, Aug.
- Chen Liu & Minh-Ngoc Tran & Chao Wang & Richard Gerlach & Robert Kohn, 2023, "Global Neural Networks and The Data Scaling Effect in Financial Time Series Forecasting," Papers, arXiv.org, number 2309.02072, Sep, revised Feb 2025.
- Pinski, Marc & Hofmann, Thomas & Benlian, Alexander, 2023, "Executive AI Literacy: A Text-Mining Approach to Understand Existing and Demanded AI Skills of Leaders in Unicorn Firms," 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 139226.
- Van-Thien Nguyen & René Carraz, 2023, "A Novel Matching Algorithm for Academic Patent Paper Pairs: An Exploratory Study of Japan's national research universities and laboratories," Working Papers of BETA, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg, number 2023-29.
- Santino Del Fava & Rangan Gupta & Christian Pierdzioch & Lavinia Rognone, 2023, "Forecasting International Financial Stress: The Role of Climate Risks," Working Papers, University of Pretoria, Department of Economics, number 202329, Sep.
- Christian Oliver Ewald & Kevin Kamm, 2023, "On the Impact of Feeding Cost Risk in Aquaculture Valuation and Decision Making," Papers, arXiv.org, number 2309.02970, Sep.