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Report NEP-BIG-2023-09-11
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:
- Bryan T. Kelly & Boris Kuznetsov & Semyon Malamud & Teng Andrea Xu, 2023, "Deep Learning from Implied Volatility Surfaces," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 23-60, Aug.
- Tohid Atashbar, 2023, "How Nations Become Fragile: An AI-Augmented Bird’s-Eye View (with a Case Study of South Sudan)," IMF Working Papers, International Monetary Fund, number 2023/167, Aug.
- Karapanagiotis, Pantelis & Liebald, Marius, 2023, "Entity matching with similarity encoding: A supervised learning recommendation framework for linking (big) data," SAFE Working Paper Series, Leibniz Institute for Financial Research SAFE, number 398.
- Yancheng Liang & Jiajie Zhang & Hui Li & Xiaochen Liu & Yi Hu & Yong Wu & Jinyao Zhang & Yongyan Liu & Yi Wu, 2023, "DeRisk: An Effective Deep Learning Framework for Credit Risk Prediction over Real-World Financial Data," Papers, arXiv.org, number 2308.03704, Aug.
- Borgschulte, Mark & Guenzel, Marius & Liu, Canyao & Malmendier, Ulrike, 2023, "CEO Stress, Aging, and Death," IZA Discussion Papers, IZA Network @ LISER, number 16366, Aug.
- Dhruv Desai & Ashmita Dhiman & Tushar Sharma & Deepika Sharma & Dhagash Mehta & Stefano Pasquali, 2023, "Quantifying Outlierness of Funds from their Categories using Supervised Similarity," Papers, arXiv.org, number 2308.06882, Aug.
- Item repec:fip:fedkrr:96511 is not listed on IDEAS anymore
- John V. Colias & Stella Park & Elizabeth Horn, 2023, "Optimizing B2B Product Offers with Machine Learning, Mixed Logit, and Nonlinear Programming," Papers, arXiv.org, number 2308.07830, Aug.
- Suss, Joel & Kemeny, Thomas & Connor, Dylan Shane, 2023, "GEOWEALTH: spatial wealth inequality data for the United States, 1960-2020," LSE Research Online Documents on Economics, London School of Economics and Political Science, LSE Library, number 119980, Aug.
- Chao Zhang & Xingyue Pu & Mihai Cucuringu & Xiaowen Dong, 2023, "Graph Neural Networks for Forecasting Multivariate Realized Volatility with Spillover Effects," Papers, arXiv.org, number 2308.01419, Aug.
- Michael G. Mueller-Smith & Benjamin Pyle & Caroline Walker, 2023, "Estimating the Impact of the Age of Criminal Majority: Decomposing Multiple Treatments in a Regression Discontinuity Framework," NBER Working Papers, National Bureau of Economic Research, Inc, number 31523, Aug.
- Stefano Piasenti & Marica Valente & Roel van Veldhuizen & Gregor Pfeifer, 2023, "Does Unfairness Hurt Women? The Effects of Losing Unfair Competitions," Working Papers, Faculty of Economics and Statistics, Universität Innsbruck, number 2023-11, Nov.
- Valter T. Yoshida Jr & Alan de Genaro & Rafael Schiozer & Toni R. E. dos Santos, 2023, "A Novel Credit Model Risk Measure: does more data lead to lower model risk in credit scoring models?," Working Papers Series, Central Bank of Brazil, Research Department, number 582, Aug.
- Ioannis Papageorgiou & Ioannis Kontoyiannis, 2023, "The Bayesian Context Trees State Space Model for time series modelling and forecasting," Papers, arXiv.org, number 2308.00913, Aug, revised Aug 2025.
- Fantazzini, Dean & Kurbatskii, Alexey & Mironenkov, Alexey & Lycheva, Maria, 2022, "Forecasting oil prices with penalized regressions, variance risk premia and Google data," MPRA Paper, University Library of Munich, Germany, number 118239.
- Xianhua Peng & Chenyin Gong & Xue Dong He, 2023, "Reinforcement Learning for Financial Index Tracking," Papers, arXiv.org, number 2308.02820, Aug, revised Nov 2024.