Report NEP-CMP-2021-11-22

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.

Subscribe to this report: email, RSS, or Mastodon.

Other reports in NEP-CMP

The following items were announced in this report:

• Hofer, Florian & Birkner, Benjamin & Spindler, Martin, 2021. "Power of machine learning algorithms for predicting dropouts from a German telemonitoring program using standardized claims data," hche Research Papers 24, University of Hamburg, Hamburg Center for Health Economics (hche).
• Zhang, Hongwei, 2021. "Empirical asset pricing and ensemble machine learning," Other publications TiSEM 15134355-ab64-47b0-b581-5, Tilburg University, School of Economics and Management.
• Pratha Khandelwal & Philip Nadler & Rossella Arcucci & William Knottenbelt & Yi-Ke Guo, 2021. "A Scalable Inference Method For Large Dynamic Economic Systems," Papers 2110.14346, arXiv.org.
• Werner, Tobias, 2021. "Algorithmic and human collusion," DICE Discussion Papers 372, Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE).
• Shi, Chengchun & Xu, Tianlin & Bergsma, Wicher & Li, Lexin, 2021. "Double generative adversarial networks for conditional independence testing," LSE Research Online Documents on Economics 112550, London School of Economics and Political Science, LSE Library.
• Selim Amrouni & Aymeric Moulin & Jared Vann & Svitlana Vyetrenko & Tucker Balch & Manuela Veloso, 2021. "ABIDES-Gym: Gym Environments for Multi-Agent Discrete Event Simulation and Application to Financial Markets," Papers 2110.14771, arXiv.org.
• Denisa BANULESCU-RADU & Meryem YANKOL-SCHALCK, 2021. "Fraud detection in the era of Machine Learning: a household insurance case," LEO Working Papers / DR LEO 2904, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
• Mohamed Ben Alaya & Ahmed Kebaier & Djibril Sarr, 2021. "Deep Calibration of Interest Rates Model," Papers 2110.15133, arXiv.org, revised Sep 2024.
• Andrea Coletta & Matteo Prata & Michele Conti & Emanuele Mercanti & Novella Bartolini & Aymeric Moulin & Svitlana Vyetrenko & Tucker Balch, 2021. "Towards Realistic Market Simulations: a Generative Adversarial Networks Approach," Papers 2110.13287, arXiv.org.
• Leonardo N. Ferreira, 2021. "Forecasting with VAR-teXt and DFM-teXt Models:exploring the predictive power of central bank communication," Working Papers Series 559, Central Bank of Brazil, Research Department.
• Nestoras Chalkidis & Rahul Savani, 2021. "Trading via Selective Classification," Papers 2110.14914, arXiv.org, revised Oct 2021.
• Andrea Albarea & Michele Bernasconi & Anna Marenzi & Dino Rizzi, 2021. "Tax evasion, behavioral microsimulation models and flat-rate tax reforms. Analysis for Italy," Working Papers 2021:26, Department of Economics, University of Venice "Ca' Foscari".
• van Lieshout, R.N. & van den Akker, J.M. & R. Mendes Borges & T. Druijf & Quaglietta, E., 2021. "Microscopic Simulation of Decentralized Dispatching Strategies in Railways," Econometric Institute Research Papers EI-1708, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.