Report NEP-CMP-2020-06-15

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.

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Other reports in NEP-CMP

The following items were announced in this report:

• Michael Puglia & Adam Tucker, 2020. "Machine Learning, the Treasury Yield Curve and Recession Forecasting," Finance and Economics Discussion Series 2020-038, Board of Governors of the Federal Reserve System (U.S.).
• Bruno Bouchard & Adil Reghai & Benjamin Virrion, 2020. "Computation of Expected Shortfall by fast detection of worst scenarios," Working Papers hal-02619589, HAL.
• Maake, Witness & Van Zyl, Terence, 2020. "Applications of Machine Learning to Estimating the Sizes and Market Impact of Hidden Orders in the BRICS Financial Markets," MPRA Paper 99075, University Library of Munich, Germany.
• Shiro Takeda & Toshi H. Arimura, 2020. "A Computable General Equilibrium Analysis of Environmental Tax Reform in Japan," RIEEM Discussion Paper Series 2002, Research Institute for Environmental Economics and Management, Waseda University.
• Qiu, Yue & Xie, Tian & Yu, Jun, 2020. "Forecast combinations in machine learning," Economics and Statistics Working Papers 13-2020, Singapore Management University, School of Economics.
• Kalamara, Eleni & Turrell, Arthur & Redl, Chris & Kapetanios, George & Kapadia, Sujit, 2020. "Making text count: economic forecasting using newspaper text," Bank of England working papers 865, Bank of England.
• Marcin Chlebus & Zuzanna Osika, 2020. "Comparison of tree-based models performance in prediction of marketing campaign results using Explainable Artificial Intelligence tools," Working Papers 2020-15, Faculty of Economic Sciences, University of Warsaw.
• Giuseppe Attanasi & Samuele Centorrino & Elena Manzoni, 2020. "Zero-Intelligence vs. Human Agents: An Experimental Analysis of the Efficiency of Double Auctions and Over-the-Counter Markets of Varying Sizes," Working Papers 05/2020, University of Verona, Department of Economics.
• Hess Chung & Etienne Gagnon & Taisuke Nakata & Matthias Paustian & Bernd Schlusche & James Trevino & Diego Vilán & Wei Zheng, 2020. "Monetary Policy Options at the Effective Lower Bound: Assessing the Federal Reserve’s Current Policy Toolkit," CARF F-Series CARF-F-483, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
• Schönheit, David & Hladik, Dirk & Hobbie, Hannes & Möst, Dominik, 2020. "ELMOD documentation: Modeling of flow-based market coupling and congestion management," EconStor Preprints 217278, ZBW - Leibniz Information Centre for Economics.
• Diego d’Andria & Jason DeBacker & Richard W. Evans & Jonathan Pycroft & Wouter van der Wielen & Magdalena Zachlod-Jelec, 2020. "EDGE-M3: A Dynamic General Equilibrium Micro-Macro Model for the EU Member States," JRC Working Papers on Taxation & Structural Reforms 2020-03, Joint Research Centre.
• Jarmulska, Barbara, 2020. "Random forest versus logit models: which offers better early warning of fiscal stress?," Working Paper Series 2408, European Central Bank.
• Andrii Babii & Eric Ghysels & Jonas Striaukas, 2020. "Machine Learning Time Series Regressions with an Application to Nowcasting," Papers 2005.14057, arXiv.org, revised Dec 2020.
• Fabio Antonelli & Alessandro Ramponi & Sergio Scarlatti, 2020. "A moment matching method for option pricing under stochastic interest rates," Papers 2005.14063, arXiv.org.
• Wang, Dandan, 2020. "Forecasting gasoline prices with mixed random forest error correction models," UC3M Working papers. Economics 30557, Universidad Carlos III de Madrid. Departamento de Economía.
• Subhadeep & Mukhopadhyay & Kaijun Wang, 2020. "Breiman's "Two Cultures" Revisited and Reconciled," Papers 2005.13596, arXiv.org.
• Zihao Zhang & Stefan Zohren & Stephen Roberts, 2020. "Deep Learning for Portfolio Optimization," Papers 2005.13665, arXiv.org, revised Jan 2021.
• Michael Creel, 2020. "Inference Using Simulated Neural Moments," Working Papers 1182, Barcelona School of Economics.
• Ian M. Trotter & Lu'is A. C. Schmidt & Bruno C. M. Pinto & Andrezza L. Batista & J'essica Pellenz & Maritza Isidro & Aline Rodrigues & Attawan G. S. Suela & Loredany Rodrigues, 2020. "COVID-19 and Global Economic Growth: Policy Simulations with a Pandemic-Enabled Neoclassical Growth Model," Papers 2005.13722, arXiv.org, revised Jun 2020.
• Xinyue Cui & Zhaoyu Xu & Yue Zhou, 2020. "Using Machine Learning to Forecast Future Earnings," Papers 2005.13995, arXiv.org.
• Jan H van Heerden, 2020. "The Possible Effects of the Extended Lockdown Period on the South African Economy: A CGE Analysis," Working Papers 202042, University of Pretoria, Department of Economics.
• Jaqueson K. Galimberti, 2020. "Information weighting under least squares learning," CAMA Working Papers 2020-46, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
• Christian Dehm & Thai Nguyen & Mitja Stadje, 2020. "Non-concave expected utility optimization with uncertain time horizon," Papers 2005.13831, arXiv.org, revised Oct 2021.