Report NEP-CMP-2023-09-11

This is the archive for NEP-CMP, a report on new working papers in the area of Computational Economics. Stan Miles issued this report. It is usually issued weekly.

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Other reports in NEP-CMP

The following items were announced in this report:

• 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 2308.03704, arXiv.org.
• Karapanagiotis, Pantelis & Liebald, Marius, 2023. "Entity matching with similarity encoding: A supervised learning recommendation framework for linking (big) data," SAFE Working Paper Series 398, Leibniz Institute for Financial Research SAFE.
• Yen-Jui Chang & Wei-Ting Wang & Hao-Yuan Chen & Shih-Wei Liao & Ching-Ray Chang, 2023. "A novel approach for quantum financial simulation and quantum state preparation," Papers 2308.01844, arXiv.org, revised Apr 2024.
• Borgschulte, Mark & Guenzel, Marius & Liu, Canyao & Malmendier, Ulrike, 2023. "CEO Stress, Aging, and Death," IZA Discussion Papers 16366, Institute of Labor Economics (IZA).
• Tohid Atashbar, 2023. "How Nations Become Fragile: An AI-Augmented Bird’s-Eye View (with a Case Study of South Sudan)," IMF Working Papers 2023/167, International Monetary Fund.
• Bryan T. Kelly & Boris Kuznetsov & Semyon Malamud & Teng Andrea Xu, 2023. "Deep Learning from Implied Volatility Surfaces," Swiss Finance Institute Research Paper Series 23-60, Swiss Finance Institute.
• Sturm, Timo & Pumplun, Luisa & Gerlach, Jin & Kowalczyk, Martin & Buxmann, Peter, 2023. "Machine Learning Advice in Managerial Decision-Making: The Overlooked Role of Decision Makers’ Advice Utilization," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 139044, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
• Xianhua Peng & Chenyin Gong & Xue Dong He, 2023. "Reinforcement Learning for Financial Index Tracking," Papers 2308.02820, arXiv.org, revised Nov 2024.
• Chao Zhang & Xingyue Pu & Mihai Cucuringu & Xiaowen Dong, 2023. "Graph Neural Networks for Forecasting Multivariate Realized Volatility with Spillover Effects," Papers 2308.01419, arXiv.org.
• Tanut Treetanthiploet & Yufei Zhang & Lukasz Szpruch & Isaac Bowers-Barnard & Henrietta Ridley & James Hickey & Chris Pearce, 2023. "Insurance pricing on price comparison websites via reinforcement learning," Papers 2308.06935, arXiv.org.
• John V. Colias & Stella Park & Elizabeth Horn, 2023. "Optimizing B2B Product Offers with Machine Learning, Mixed Logit, and Nonlinear Programming," Papers 2308.07830, arXiv.org.
• 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 582, Central Bank of Brazil, Research Department.
• 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 119980, London School of Economics and Political Science, LSE Library.
• Harry Turunen & Anastasia Zhutova & Matthieu Lemoine, 2023. "Stochastic Simulation of the FR-BDF Model and an Assessment of Uncertainty around Conditional Forecasts," Working papers 920, Banque de France.
• Morgan Frank & Yong-Yeol Ahn & Esteban Moro, 2023. "AI exposure predicts unemployment risk," Papers 2308.02624, arXiv.org.
• Du, Tianyu & Kanodia, Ayush & Athey, Susan, 2023. "Torch-Choice: A PyTorch Package for Large-Scale Choice Modelling with Python," Research Papers 4106, Stanford University, Graduate School of Business.
• Rudy Morel & St'ephane Mallat & Jean-Philippe Bouchaud, 2023. "Path Shadowing Monte-Carlo," Papers 2308.01486, arXiv.org.
• Fabrice Duval & Christophe Elie-Dit-Cosaque, 2023. "Managers and AI-driven decisions: Exploring Managers’ Sensemaking Processes in Digital Transformation Contexts [Les managers et les décisions fondées sur l'intelligence artificielle : explorer les ," Post-Print hal-04165363, HAL.