Report NEP-CMP-2021-06-21

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:

• Ming Min & Ruimeng Hu, 2021. "Signatured Deep Fictitious Play for Mean Field Games with Common Noise," Papers 2106.03272, arXiv.org.
• Xavier Warin, 2021. "Reservoir optimization and Machine Learning methods," Papers 2106.08097, arXiv.org, revised May 2023.
• Victor Chernozhukov & Whitney K. Newey & Rahul Singh, 2021. "A Simple and General Debiased Machine Learning Theorem with Finite Sample Guarantees," Papers 2105.15197, arXiv.org, revised Oct 2022.
• Hinterlang, Natascha & Hollmayr, Josef, 2021. "Classification of monetary and fiscal dominance regimes using machine learning techniques," IMFS Working Paper Series 160, Goethe University Frankfurt, Institute for Monetary and Financial Stability (IMFS).
• Zhang, Han, 2021. "How Using Machine Learning Classification as a Variable in Regression Leads to Attenuation Bias and What to Do About It," SocArXiv 453jk, Center for Open Science.
• Kieran Wood & Stephen Roberts & Stefan Zohren, 2021. "Slow Momentum with Fast Reversion: A Trading Strategy Using Deep Learning and Changepoint Detection," Papers 2105.13727, arXiv.org, revised Dec 2021.
• Daniel Hopp, 2021. "Economic Nowcasting with Long Short-Term Memory Artificial Neural Networks (LSTM)," Papers 2106.08901, arXiv.org.
• Junran Wu & Ke Xu & Xueyuan Chen & Shangzhe Li & Jichang Zhao, 2021. "Price graphs: Utilizing the structural information of financial time series for stock prediction," Papers 2106.02522, arXiv.org, revised Nov 2021.
• Da Zhang & Qingyi Wang & Shaojie Song & Simiao Chen & Mingwei Li & Lu Shen & Siqi Zheng & Bofeng Cai & Shenhao Wang, 2021. "Estimating air quality co-benefits of energy transition using machine learning," Papers 2105.14318, arXiv.org.
• Pierre-Philippe Combes & Laurent Gobillon & Yanos Zylberberg, 2021. "Urban economics in a historical perspective: Recovering data with machine learning," Working Papers halshs-03231786, HAL.
• Matus, Kira & Veale, Michael, 2021. "Certification Systems for Machine Learning: Lessons from Sustainability," SocArXiv pm3wy, Center for Open Science.
• Lukas Gonon, 2021. "Random feature neural networks learn Black-Scholes type PDEs without curse of dimensionality," Papers 2106.08900, arXiv.org.
• Juan Manuel Dodero, 2021. "Artificial intelligence masters’ programmes - An analysis of curricula building blocks," JRC Research Reports JRC123713, Joint Research Centre.
• Nikolay Ivanov & Qiben Yan, 2021. "Constraint-Based Inference of Heuristics for Foreign Exchange Trade Model Optimization," Papers 2105.14194, arXiv.org.
• Jaller, Miguel & Rodier, Caroline & Zhang, Michael & Lin, Huachao & Lewis, Kathryn, 2021. "Fighting for Curb Space: Parking, Ride-Hailing, Urban Freight Deliveries, and Other Users," Institute of Transportation Studies, Working Paper Series qt3jn371hw, Institute of Transportation Studies, UC Davis.
• Paul de Guibert & Behrang Shirizadeh & Philippe Quirion, 2020. "Variable time-step: A method for improving computational tractability for energy system models with long-term storage," Post-Print hal-03100309, HAL.
• Koya Ishikawa & Kazuhide Nakata, 2021. "Online Trading Models with Deep Reinforcement Learning in the Forex Market Considering Transaction Costs," Papers 2106.03035, arXiv.org, revised Dec 2021.
• Jorge Guijarro-Ordonez & Markus Pelger & Greg Zanotti, 2021. "Deep Learning Statistical Arbitrage," Papers 2106.04028, arXiv.org, revised Oct 2022.
• Christophe Schalck & Meryem Schalck, 2021. "Predicting French SME Failures: New Evidence from Machine Learning Techniques," Working Papers 2021-009, Department of Research, Ipag Business School.
• Zhengqing Zhou & Guanyang Wang & Jose Blanchet & Peter W. Glynn, 2021. "Unbiased Optimal Stopping via the MUSE," Papers 2106.02263, arXiv.org, revised Dec 2022.
• Kaukin Andrey & Kosarev Vladimir, 2021. "Modeling and forecasting production indices using artificial neural networks, taking into account intersectoral relationships and comparing the predictive qualities of various architectures [Модели," Working Papers s21105, Russian Presidential Academy of National Economy and Public Administration.
• Kenneth W. Clements & Marc Jim M. Mariano & George Verikios, 2021. "Expenditure Patterns, Heterogeneity And Long-Term Structural Change," Economics Discussion / Working Papers 21-10, The University of Western Australia, Department of Economics.
• Ali Hirsa & Joerg Osterrieder & Branka Hadji-Misheva & Jan-Alexander Posth, 2021. "Deep reinforcement learning on a multi-asset environment for trading," Papers 2106.08437, arXiv.org.
• Liu Ziyin & Kentaro Minami & Kentaro Imajo, 2021. "Theoretically Motivated Data Augmentation and Regularization for Portfolio Construction," Papers 2106.04114, arXiv.org, revised Dec 2022.
• Sokbae Lee & Yuan Liao & Myung Hwan Seo & Youngki Shin, 2021. "Fast and Robust Online Inference with Stochastic Gradient Descent via Random Scaling," Papers 2106.03156, arXiv.org, revised Oct 2021.
• Mathieu Mercadier & Jean-Pierre Lardy, 2019. "Credit spread approximation and improvement using random forest regression," Post-Print hal-03241566, HAL.
• Guopeng Song & Roel Leus, 2021. "Parallel machine scheduling under uncertainty: The battle for robustness," Working Papers of Department of Decision Sciences and Information Management, Leuven 675543, KU Leuven, Faculty of Economics and Business (FEB), Department of Decision Sciences and Information Management, Leuven.
• Giovanni Dosi & Francesco Lamperti & Mariana Mazzucato & Mauro Napoletano & Andrea Roventini, 2021. "Mission-Oriented Policies and the "Entrepreneurial State" at Work: An Agent-Based Exploration," GREDEG Working Papers 2021-25, Groupe de REcherche en Droit, Economie, Gestion (GREDEG CNRS), Université Côte d'Azur, France.