Report NEP-CMP-2021-12-06

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:

• Mao Guan & Xiao-Yang Liu, 2021. "Explainable Deep Reinforcement Learning for Portfolio Management: An Empirical Approach," Papers 2111.03995, arXiv.org, revised Dec 2021.
• Chaeshick Chung & Sukjin Park, 2021. "Deep Learning Market Microstructure: Dual-Stage Attention-Based Recurrent Neural Networks," Working Papers 2108, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy).
• Kaur, Karman & Prasad, Narayan & Prasad, Narayan, 2021. "Modelling Input Energy Used in Wheat Production in India Using Artificial Neural Network," 2021 Conference, August 17-31, 2021, Virtual 315051, International Association of Agricultural Economists.
• Zechu Li & Xiao-Yang Liu & Jiahao Zheng & Zhaoran Wang & Anwar Walid & Jian Guo, 2021. "FinRL-Podracer: High Performance and Scalable Deep Reinforcement Learning for Quantitative Finance," Papers 2111.05188, arXiv.org.
• Corredera, Alberto, 2022. "Prescriptive selection of machine learning hyperparameters with applications in power markets: retailer's optimal trading," DES - Working Papers. Statistics and Econometrics. WS 33693, Universidad Carlos III de Madrid. Departamento de Estadística.
• Klaus-Peter Hellwig, 2021. "Predicting Fiscal Crises: A Machine Learning Approach," IMF Working Papers 2021/150, International Monetary Fund.
• Anders Nõu & Darya Lapitskaya & Mustafa Hakan Eratalay & Rajesh Sharma, 2021. "Predicting Stock Return And Volatility With Machine Learning And Econometric Models: A Comparative Case Study Of The Baltic Stock Market," University of Tartu - Faculty of Economics and Business Administration Working Paper Series 135, Faculty of Economics and Business Administration, University of Tartu (Estonia).
• Bluwstein, Kristina & Buckmann, Marcus & Joseph, Andreas & Kapadia, Sujit & Şimşek, Özgür, 2021. "Credit growth, the yield curve and financial crisis prediction: evidence from a machine learning approach," Working Paper Series 2614, European Central Bank.
• Mizuho Kida & Simon Paetzold, 2021. "The Impact of Gray-Listing on Capital Flows: An Analysis Using Machine Learning," IMF Working Papers 2021/153, International Monetary Fund.
• Alexander Kell, 2021. "Modelling the transition to a low-carbon energy supply," Papers 2111.00987, arXiv.org.
• Emanuel Kohlscheen, 2021. "What does machine learning say about the drivers of inflation?," BIS Working Papers 980, Bank for International Settlements.
• Davide Cividino & Rebecca Westphal & Didier Sornette, 2021. "Multi-asset financial bubbles in an agent-based model with noise traders’ herding described by an n-vector Ising model," Swiss Finance Institute Research Paper Series 21-76, Swiss Finance Institute.
• Yue-Jun Zhang & Han Zhang & Rangan Gupta, 2021. "Forecasting the Artificial Intelligence Index Returns: A Hybrid Approach," Working Papers 202182, University of Pretoria, Department of Economics.
• Jeronymo Marcondes Pinto & Jennifer L. Castle, 2021. "A machine learning dynamic switching approach to forecasting when there are structural breaks," Economics Series Working Papers 950 JEL classification: C, University of Oxford, Department of Economics.
• Heimann, Tobias & Delzeit, Ruth, 2021. "Land for Fish: A scenario based CGE analysis of the effects of aquaculture production on agricultural markets," 2021 Conference, August 17-31, 2021, Virtual 315270, International Association of Agricultural Economists.
• Saiz, Lorena & Ashwin, Julian & Kalamara, Eleni, 2021. "Nowcasting euro area GDP with news sentiment: a tale of two crises," Working Paper Series 2616, European Central Bank.
• Olga Diukanova & Mariana Chioncel, 2021. "A GDP impact evaluation of R&D investments in Romania using the CGE model Rhomolo," JRC Working Papers on Territorial Modelling and Analysis 2021-10, Joint Research Centre.
• Bhumjai Tangsawasdirat & Suranan Tanpoonkiat & Burasakorn Tangsatchanan, 2021. "Credit Risk Database: Credit Scoring Models for Thai SMEs," PIER Discussion Papers 168, Puey Ungphakorn Institute for Economic Research.
• Lilian N. Rolim & Carolina Troncoso Baltar & Gilberto Tadeu Lima, 2021. "Income Distribution, Productivity Growth and Workers's Bargaining Power in an Agent-Based Macroeconomic Model," Working Papers, Department of Economics 2021_27, University of São Paulo (FEA-USP), revised 30 Nov 2021.
• Jaydip Sen & Abhishek Dutta & Sidra Mehtab, 2021. "Stock Portfolio Optimization Using a Deep Learning LSTM Model," Papers 2111.04709, arXiv.org.
• Brandon Buell & Reda Cherif & Carissa Chen & Karl Walentin & Jiawen Tang & Nils Wendt, 2021. "Impact of COVID-19: Nowcasting and Big Data to Track Economic Activity in Sub-Saharan Africa," IMF Working Papers 2021/124, International Monetary Fund.
• Giacomo De Giorgi & Matthew Harding & Gabriel Vasconcelos, 2021. "Predicting Mortality from Credit Reports," Papers 2111.03662, arXiv.org.
• Armand Hatchuel & Pascal Le Masson & Maxime Thomas & Benoit Weil, 2021. "What Is Generative In Generative Design Tools? Uncovering Topological Generativity With A C-K Model Of Evolutionary Algorithms," Post-Print hal-03398565, HAL.
• Simon B chler, Maximilian v. Ehrlich, 2021. "Quantifying Land Use Regulation and its Determinants - Ease of Residential Development across Swiss Municipalities," Diskussionsschriften credresearchpaper32, Universitaet Bern, Departement Volkswirtschaft - CRED.
• Felipe Gonzalez & Marc Petit & Yannick Perez, 2021. "Plug-in behavior of electric vehicles users: Insights from a large-scale trial and impacts for grid integration studies," Post-Print hal-03363782, HAL.
• Jelle Barkema & Borislava Mircheva & Mr. Mico Mrkaic & Yuanchen Yang, 2021. "License to Spill: How Do We Discuss Spillovers in Article IV Staff Reports," IMF Working Papers 2021/134, International Monetary Fund.
• Carlos A. Abanto-Valle & Gabriel Rodríguez & Luis M. Castro Cepero & Hernán B. Garrafa-Aragón, 2021. "Approximate Bayesian Estimation of Stochastic Volatility in Mean Models using Hidden Markov Models: Empirical Evidence from Stock Latin American Markets," Documentos de Trabajo / Working Papers 2021-502, Departamento de Economía - Pontificia Universidad Católica del Perú.