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Report NEP-CMP-2020-11-09
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:
- Miquel Noguer i Alonso & Sonam Srivastava, 2020, "Deep Reinforcement Learning for Asset Allocation in US Equities," Papers, arXiv.org, number 2010.04404, Oct.
- Dan Wang & Tianrui Wang & Ionuc{t} Florescu, 2020, "Is Image Encoding Beneficial for Deep Learning in Finance? An Analysis of Image Encoding Methods for the Application of Convolutional Neural Networks in Finance," Papers, arXiv.org, number 2010.08698, Oct.
- Yucheng Yang & Zhong Zheng & Weinan E, 2020, "Interpretable Neural Networks for Panel Data Analysis in Economics," Papers, arXiv.org, number 2010.05311, Oct, revised Nov 2020.
- Ollech, Daniel & Webel, Karsten, 2020, "A random forest-based approach to identifying the most informative seasonality tests," Discussion Papers, Deutsche Bundesbank, number 55/2020.
- Sean Cao & Wei Jiang & Baozhong Yang & Alan L. Zhang, 2020, "How to Talk When a Machine is Listening?: Corporate Disclosure in the Age of AI," NBER Working Papers, National Bureau of Economic Research, Inc, number 27950, Oct.
- P.B. Dixon & J.A. Giesecke & J. Nassios & M.T. Rimmer, 2020, "The Effects of Financial Decoupling of the U.S. and China: Simulations with a Global Financial CGE Model," Centre of Policy Studies/IMPACT Centre Working Papers, Victoria University, Centre of Policy Studies/IMPACT Centre, number g-309, Oct.
- Isao Yagi & Mahiro Hoshino & Takanobu Mizuta, 2020, "Analysis of the impact of maker-taker fees on the stock market using agent-based simulation," Papers, arXiv.org, number 2010.08992, Oct.
- David Byrd & Antigoni Polychroniadou, 2020, "Differentially Private Secure Multi-Party Computation for Federated Learning in Financial Applications," Papers, arXiv.org, number 2010.05867, Oct.
- Nosratabadi, Saeed & Mosavi, Amir & Duan, Puhong & Ghamisi, Pedram & Filip, Ferdinand & Band, Shahab S. & Reuter, Uwe & Gama, Joao & Gandomi, Amir H., 2020, "Data science in economics: comprehensive review of advanced machine learning and deep learning methods," OSF Preprints, Center for Open Science, number yc6e2, Oct, DOI: 10.31219/osf.io/yc6e2.
- Eric Benhamou & David Saltiel & Sandrine Ungari & Abhishek Mukhopadhyay, 2020, "Bridging the gap between Markowitz planning and deep reinforcement learning," Papers, arXiv.org, number 2010.09108, Sep.
- Shenhao Wang & Baichuan Mo & Jinhua Zhao, 2020, "Theory-based residual neural networks: A synergy of discrete choice models and deep neural networks," Papers, arXiv.org, number 2010.11644, Oct.
- Rangan Gupta & Christian Pierdzioch & Afees A. Salisu, 2020, "Oil-Price Uncertainty and the U.K. Unemployment Rate: A Forecasting Experiment with Random Forests Using 150 Years of Data," Working Papers, University of Pretoria, Department of Economics, number 202095, Oct.
- Elior Nehemya & Yael Mathov & Asaf Shabtai & Yuval Elovici, 2020, "Taking Over the Stock Market: Adversarial Perturbations Against Algorithmic Traders," Papers, arXiv.org, number 2010.09246, Oct, revised Sep 2021.
- Huber, Martin & Imhof, David, 2020, "Transnational machine learning with screens for flagging bid-rigging cartels," FSES Working Papers, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland, number 519, Oct.
- Ma, Ji, 2020, "Automated coding using machine-learning and remapping the U.S. nonprofit sector: A guide and benchmark," OSF Preprints, Center for Open Science, number pt3q9, Oct, DOI: 10.31219/osf.io/pt3q9.
- Taeyoung Doh & Dongho Song & Shu-Kuei X. Yang, 2020, "Deciphering Federal Reserve Communication via Text Analysis of Alternative FOMC Statements," Research Working Paper, Federal Reserve Bank of Kansas City, number RWP 20-14, Oct, revised 16 Oct 2025, DOI: 10.18651/RWP2020-14.
- Patrick T. Harker, 2020, "The Economy, the Pandemic, and Machine Learning," Speech, Federal Reserve Bank of Philadelphia, number 88805, Sep.
- Pradipta Banerjee & Subhrabrata Choudhury, 2020, "Pandemic Lessons -- Devising an assessment framework to analyse policies for sustainability," Papers, arXiv.org, number 2010.04833, Oct, revised May 2021.
- Hamzawi, Salah G., , "Management and Planning of Airport Gate Capacity: A New Microcomputer Based Gate Assignment Simulation Model," 21st Annual Canadian Transportation Research Forum, Vancouver, British Columbia, May 28-30, 1986, Canadian Transportation Research Forum (CTRF), number 305954, DOI: 10.22004/ag.econ.305954.
- Peiwan Wang & Lu Zong, 2020, "Are Crises Predictable? A Review of the Early Warning Systems in Currency and Stock Markets," Papers, arXiv.org, number 2010.10132, Oct.
- Item repec:esm:wpaper:esmt-20-01_r1 is not listed on IDEAS anymore
- Eren Kurshan & Hongda Shen & Jiahao Chen, 2020, "Towards Self-Regulating AI: Challenges and Opportunities of AI Model Governance in Financial Services," Papers, arXiv.org, number 2010.04827, Oct.
- Feng Zhang & Ruite Guo & Honggao Cao, 2020, "Information Coefficient as a Performance Measure of Stock Selection Models," Papers, arXiv.org, number 2010.08601, Oct.
- Tien Ha Duong, My & Van Nguyen, Diep & Thanh Nguyen, Phong, 2019, "Using Fuzzy Approach to Model Skill Shortage in Vietnam’s Labor Market in the Context of Industry 4.0," MPRA Paper, University Library of Munich, Germany, number 103512, Nov, revised 07 May 2020.
- S. Borağan Aruoba & Pablo Cuba-Borda & Kenji Higa-Flores & Frank Schorfheide & Sergio Villalvazo, 2020, "Piecewise-Linear Approximations and Filtering for DSGE Models with Occasionally Binding Constraints," NBER Working Papers, National Bureau of Economic Research, Inc, number 27991, Oct.