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Report NEP-CMP-2023-02-13
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:
- Gebreel, Alia Youssef, 2023, "An overview of machine learning, deep learning, and artificial intelligence," OSF Preprints, Center for Open Science, number 7cuxz, Jan, DOI: 10.31219/osf.io/7cuxz.
- Jian Guo & Saizhuo Wang & Lionel M. Ni & Heung-Yeung Shum, 2022, "Quant 4.0: Engineering Quantitative Investment with Automated, Explainable and Knowledge-driven Artificial Intelligence," Papers, arXiv.org, number 2301.04020, Dec.
- Tohid Atashbar & Rui Aruhan Shi, 2022, "Deep Reinforcement Learning: Emerging Trends in Macroeconomics and Future Prospects," IMF Working Papers, International Monetary Fund, number 2022/259, Dec.
- Clark, Andrew E. & D'Ambrosio, Conchita & Gentile, Niccoló & Tkatchenko, Alexandre, 2022, "What makes a satisfying life? Prediction and interpretation with machine-learning algorithms," LSE Research Online Documents on Economics, London School of Economics and Political Science, LSE Library, number 117887, Jun.
- Farmer, J. Doyne & Dyer, Joel & Cannon, Patrick & Schmon, Sebastian, 2022, "Calibrating Agent-based Models to Microdata with Graph Neural Networks," INET Oxford Working Papers, Institute for New Economic Thinking at the Oxford Martin School, University of Oxford, number 2022-30, Jun.
- Peer Nagy & Jan-Peter Calliess & Stefan Zohren, 2023, "Asynchronous Deep Double Duelling Q-Learning for Trading-Signal Execution in Limit Order Book Markets," Papers, arXiv.org, number 2301.08688, Jan, revised Sep 2023.
- Wassima Lakhchini & Rachid Wahabi & Mounime El Kabbouri, 2022, "Artificial Intelligence & Machine Learning in Finance: A literature review," Post-Print, HAL, number hal-03916744, Dec, DOI: 10.5281/zenodo.7454232.
- Oparina, Ekaterina & Kaiser, Caspar & Gentile, Niccoló & Tkatchenko, Alexandre & Clark, Andrew E. & De Neve, Jan-Emmanuel & D'Ambrosio, Conchita, 2022, "Human wellbeing and machine learning," LSE Research Online Documents on Economics, London School of Economics and Political Science, LSE Library, number 117955, Jul.
- Yuanrong Wang & Yinsen Miao & Alexander CY Wong & Nikita P Granger & Christian Michler, 2023, "Domain-adapted Learning and Interpretability: DRL for Gas Trading," Papers, arXiv.org, number 2301.08359, Jan, revised Sep 2023.
- Luca Eduardo Fierro & Federico Giri & Alberto Russo, 2023, "Inequality-Constrained Monetary Policy in a Financialized Economy," Working Papers, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali, number 474, Jan.
- Yuanrong Wang & Vignesh Raja Swaminathan & Nikita P. Granger & Carlos Ros Perez & Christian Michler, 2023, "Domain-adapted Learning and Imitation: DRL for Power Arbitrage," Papers, arXiv.org, number 2301.08360, Jan, revised Sep 2023.
- Axenbeck, Janna & Breithaupt, Patrick, 2022, "Measuring the digitalisation of firms: A novel text mining approach," ZEW Discussion Papers, ZEW - Leibniz Centre for European Economic Research, number 22-065.
- Damir Filipović & Puneet Pasricha, 2022, "Empirical Asset Pricing via Ensemble Gaussian Process Regression," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 22-95, Dec.
- Crespo, Marelys & Gadat, Sébastien & Gendre, Xavier, 2023, "Stochastic Langevin Monte Carlo for (weakly) log-concave posterior distributions," TSE Working Papers, Toulouse School of Economics (TSE), number 23-1398, Jan.
- Yongping Bao & Ludwig Danwitz & Fabian Dvorak & Sebastian Fehrler & Lars Hornuf & Hsuan Yu Lin & Bettina von Helversen, 2022, "Similarity and Consistency in Algorithm-Guided Exploration," CESifo Working Paper Series, CESifo, number 10188.
- Laureti, Lucio & Costantiello, Alberto & Leogrande, Angelo, 2023, "The Role of Government Effectiveness in the Light of ESG Data at Global Level," MPRA Paper, University Library of Munich, Germany, number 115998, Jan.
- Jamotton, Charlotte & Hainaut, Donatien & Hames, Thomas, 2023, "Insurance analytics with clustering techniques," LIDAM Discussion Papers ISBA, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA), number 2023002, Jan.
- Jaehyuk Choi & Yue Kuen Kwok, 2023, "Simulation schemes for the Heston model with Poisson conditioning," Papers, arXiv.org, number 2301.02800, Jan, revised Nov 2023.
- Yasa Syed & Guanyang Wang, 2023, "Optimal randomized multilevel Monte Carlo for repeatedly nested expectations," Papers, arXiv.org, number 2301.04095, Jan, revised May 2023.
- Zhang, Junyi & Dassios, Angelos, 2023, "Truncated Poisson-Dirichlet approximation for Dirichlet process hierarchical models," LSE Research Online Documents on Economics, London School of Economics and Political Science, LSE Library, number 117690, Jan.
- Brière, Marie & Huynh, Karen & Laudy, Olav & Pouget, Sébastien, 2023, "What do we Learn from a Machine Understanding: News Content? Stock Market Reaction to News," TSE Working Papers, Toulouse School of Economics (TSE), number 23-1401, Jan.
- Stijn Broecke, 2023, "Artificial intelligence and labour market matching," OECD Social, Employment and Migration Working Papers, OECD Publishing, number 284, Jan, DOI: 10.1787/2b440821-en.
- Ozili, Peterson K., 2023, "Digital finance research and developments around the World: a literature review," MPRA Paper, University Library of Munich, Germany, number 115780.