Report NEP-CMP-2021-02-22

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:

• Hampus Engsner, 2021, "Least Squares Monte Carlo applied to Dynamic Monetary Utility Functions," Papers, arXiv.org, number 2101.10947, Jan, revised Apr 2021.
• Marco Ortu & Nicola Uras & Claudio Conversano & Giuseppe Destefanis & Silvia Bartolucci, 2021, "On Technical Trading and Social Media Indicators in Cryptocurrencies' Price Classification Through Deep Learning," Papers, arXiv.org, number 2102.08189, Feb, revised Feb 2021.
• Kumar Yashaswi, 2021, "Deep Reinforcement Learning for Portfolio Optimization using Latent Feature State Space (LFSS) Module," Papers, arXiv.org, number 2102.06233, Feb.
• Hoogendoorn, Y.N. & Dalmeijer, K., 2021, "Resource-robust valid inequalities for set covering and set partitioning models," Econometric Institute Research Papers, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute, number EI 2020-08, Jan.
• Xiaoyan Wang & Xi Lin & Meng Li, 2021, "Aggregate Modeling and Equilibrium Analysis of the Crowdsourcing Market for Autonomous Vehicles," Papers, arXiv.org, number 2102.07147, Feb.
• Celine de Quatrebarbes & Bertrand Laporte & Stéphane Calipel, 2021, "Fighting the soaring prices of agricultural food products. VAT versus Trade tariffs exemptions in a context of imperfect competition in Niger : CGE and micro-simulation approach," Working Papers, HAL, number hal-03138369, Feb.
• Niclas Boehmer & Markus Brill & Ulrike Schmidt-Kraepelin, 2021, "Selecting Matchings via Multiwinner Voting: How Structure Defeats a Large Candidate Space," Papers, arXiv.org, number 2102.07441, Feb.
• Andrew Butler & Roy H. Kwon, 2021, "Integrating prediction in mean-variance portfolio optimization," Papers, arXiv.org, number 2102.09287, Feb, revised Nov 2022.
• Lenka Nechvatalova, 2021, "Multi-Horizon Equity Returns Predictability via Machine Learning," Working Papers IES, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, number 2021/02, Feb, revised Feb 2021.
• Bauer, Kevin & Hinz, Oliver & Weber, Patrick, 2021, "KI in der Finanzbranche: Im Spannungsfeld zwischen technologischer Innovation und regulatorischer Anforderung," SAFE White Paper Series, Leibniz Institute for Financial Research SAFE, number 80.
• Oscar Claveria & Enric Monte & Salvador Torra, 2021, ""Nowcasting and forecasting GDP growth with machine-learning sentiment indicators"," IREA Working Papers, University of Barcelona, Research Institute of Applied Economics, number 202103, Feb, revised Feb 2021.
• Falilou Fall & Paul Cahu, 2021, "A simulation framework to project pension spending: The Czech pension system," OECD Economics Department Working Papers, OECD Publishing, number 1657, Feb, DOI: 10.1787/e4e79fad-en.
• Anton Korinek & Joseph E. Stiglitz, 2021, "Artificial Intelligence, Globalization, and Strategies for Economic Development," NBER Working Papers, National Bureau of Economic Research, Inc, number 28453, Feb.
• Zihao Zhang & Bryan Lim & Stefan Zohren, 2021, "Deep Learning for Market by Order Data," Papers, arXiv.org, number 2102.08811, Feb, revised Jul 2021.
• Hui Chen & Antoine Didisheim & Simon Scheidegger, 2021, "Deep Structural Estimation: With an Application to Option Pricing," Papers, arXiv.org, number 2102.09209, Feb.
• Vasil Marchev & Angel Marchev Jr, 2021, "Methods for Simulating Multi-dimensional Data for Financial Services Recommendation," Bulgarian Economic Papers, Faculty of Economics and Business Administration, Sofia University St Kliment Ohridski - Bulgaria // Center for Economic Theories and Policies at Sofia University St Kliment Ohridski, number bep-2021-02, Feb, revised Feb 2021.
• A. Christian Silva & Fernando F. Ferreira, 2021, "Surrogate Monte Carlo," Papers, arXiv.org, number 2102.08186, Feb.
• Oleg Szehr, 2021, "Hedging of Financial Derivative Contracts via Monte Carlo Tree Search," Papers, arXiv.org, number 2102.06274, Feb, revised Apr 2021.
• Fan Cheng & Rob J Hyndman & Anastasios Panagiotelis, 2021, "Manifold Learning with Approximate Nearest Neighbors," Monash Econometrics and Business Statistics Working Papers, Monash University, Department of Econometrics and Business Statistics, number 3/21.
• Vikram Manjunath & Thayer Morrill, 2021, "Interview Hoarding," Papers, arXiv.org, number 2102.06440, Feb, revised Oct 2021.
• Nguyen, Cuong, 2019, "Simulation of the Costs and Benefits of Delayed Retirement: Evidence from Vietnam," MPRA Paper, University Library of Munich, Germany, number 106180, Dec.
• Mehmet Balcilar & David Gabauer & Rangan Gupta & Christian Pierdzioch, 2021, "Uncertainty and Forecastability of Regional Output Growth in the United Kingdom: Evidence from Machine Learning," Working Papers, University of Pretoria, Department of Economics, number 202111, Feb.

Report NEP-CMP-2021-02-22

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: