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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. Stanley Miles issued this report. It is usually issued weekly.Subscribe to this report: email, RSS, or Mastodon, or Bluesky.
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, University of Hamburg, Hamburg Center for Health Economics (hche), number 24.
- Zhang, Hongwei, 2021, "Empirical asset pricing and ensemble machine learning," Other publications TiSEM, Tilburg University, School of Economics and Management, number 15134355-ab64-47b0-b581-5.
- Pratha Khandelwal & Philip Nadler & Rossella Arcucci & William Knottenbelt & Yi-Ke Guo, 2021, "A Scalable Inference Method For Large Dynamic Economic Systems," Papers, arXiv.org, number 2110.14346, Oct.
- Werner, Tobias, 2021, "Algorithmic and human collusion," DICE Discussion Papers, Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE), number 372.
- Shi, Chengchun & Xu, Tianlin & Bergsma, Wicher & Li, Lexin, 2021, "Double generative adversarial networks for conditional independence testing," LSE Research Online Documents on Economics, London School of Economics and Political Science, LSE Library, number 112550, Dec.
- 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, arXiv.org, number 2110.14771, Oct.
- Denisa BANULESCU-RADU & Meryem YANKOL-SCHALCK, 2021, "Fraud detection in the era of Machine Learning: a household insurance case," LEO Working Papers / DR LEO, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans, number 2904.
- Mohamed Ben Alaya & Ahmed Kebaier & Djibril Sarr, 2021, "Deep Calibration of Interest Rates Model," Papers, arXiv.org, number 2110.15133, Oct, 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, arXiv.org, number 2110.13287, Oct.
- Leonardo N. Ferreira, 2021, "Forecasting with VAR-teXt and DFM-teXt Models:exploring the predictive power of central bank communication," Working Papers Series, Central Bank of Brazil, Research Department, number 559, Nov.
- Nestoras Chalkidis & Rahul Savani, 2021, "Trading via Selective Classification," Papers, arXiv.org, number 2110.14914, Oct, 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, Department of Economics, University of Venice "Ca' Foscari", number 2021:26.
- 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, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute, number EI-1708, Nov.