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. 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:

• Mao Guan & Xiao-Yang Liu, 2021, "Explainable Deep Reinforcement Learning for Portfolio Management: An Empirical Approach," Papers, arXiv.org, number 2111.03995, Nov, revised Dec 2021.
• Chaeshick Chung & Sukjin Park, 2021, "Deep Learning Market Microstructure: Dual-Stage Attention-Based Recurrent Neural Networks," Working Papers, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy), number 2108.
• 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, International Association of Agricultural Economists, number 315051, Aug, DOI: 10.22004/ag.econ.315051.
• 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, arXiv.org, number 2111.05188, Nov.
• Corredera Barbado, Alberto & Ruiz Mora, Carlos, 2022, "Prescriptive selection of machine learning hyperparameters with applications in power markets: retailer's optimal trading," DES - Working Papers. Statistics and Econometrics. WS, Universidad Carlos III de Madrid. Departamento de Estadística, number 33693, Oct.
• Klaus-Peter Hellwig, 2021, "Predicting Fiscal Crises: A Machine Learning Approach," IMF Working Papers, International Monetary Fund, number 2021/150, May.
• 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, Faculty of Economics and Business Administration, University of Tartu (Estonia), number 135.
• 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, European Central Bank, number 2614, Nov.
• Mizuho Kida & Simon Paetzold, 2021, "The Impact of Gray-Listing on Capital Flows: An Analysis Using Machine Learning," IMF Working Papers, International Monetary Fund, number 2021/153, May.
• Alexander Kell, 2021, "Modelling the transition to a low-carbon energy supply," Papers, arXiv.org, number 2111.00987, Sep.
• Emanuel Kohlscheen, 2021, "What does machine learning say about the drivers of inflation?," BIS Working Papers, Bank for International Settlements, number 980, Nov.
• 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, Swiss Finance Institute, number 21-76, Nov.
• Yue-Jun Zhang & Han Zhang & Rangan Gupta, 2021, "Forecasting the Artificial Intelligence Index Returns: A Hybrid Approach," Working Papers, University of Pretoria, Department of Economics, number 202182, Nov.
• Jeronymo Marcondes Pinto & Jennifer L. Castle, 2021, "A machine learning dynamic switching approach to forecasting when there are structural breaks," Economics Series Working Papers, University of Oxford, Department of Economics, number 950 JEL classification: C, Oct.
• 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, International Association of Agricultural Economists, number 315270, Aug, DOI: 10.22004/ag.econ.315270.
• Saiz, Lorena & Ashwin, Julian & Kalamara, Eleni, 2021, "Nowcasting euro area GDP with news sentiment: a tale of two crises," Working Paper Series, European Central Bank, number 2616, Nov.
• 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, Joint Research Centre, number 2021-10, Nov.
• Bhumjai Tangsawasdirat & Suranan Tanpoonkiat & Burasakorn Tangsatchanan, 2021, "Credit Risk Database: Credit Scoring Models for Thai SMEs," PIER Discussion Papers, Puey Ungphakorn Institute for Economic Research, number 168, Nov.
• 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, University of São Paulo (FEA-USP), number 2021_27, Nov, revised 30 Nov 2021.
• Jaydip Sen & Abhishek Dutta & Sidra Mehtab, 2021, "Stock Portfolio Optimization Using a Deep Learning LSTM Model," Papers, arXiv.org, number 2111.04709, Nov.
• 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, International Monetary Fund, number 2021/124, May.
• Giacomo De Giorgi & Matthew Harding & Gabriel Vasconcelos, 2021, "Predicting Mortality from Credit Reports," Papers, arXiv.org, number 2111.03662, Nov.
• 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, number hal-03398565, Aug.
• Simon B chler, Maximilian v. Ehrlich, 2021, "Quantifying Land Use Regulation and its Determinants - Ease of Residential Development across Swiss Municipalities," Diskussionsschriften, Universitaet Bern, Departement Volkswirtschaft - CRED, number credresearchpaper32, Aug.
• 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, number hal-03363782, Nov, DOI: 10.1016/j.etran.2021.100131.
• 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, International Monetary Fund, number 2021/134, May.
• 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, Departamento de Economía - Pontificia Universidad Católica del Perú, number 2021-502, DOI: 10.18800/2079-8474.0502.

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. 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: