Report NEP-CMP-2020-01-06

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.

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Other reports in NEP-CMP

The following items were announced in this report:

• Firuz Kamalov, 2019, "Forecasting significant stock price changes using neural networks," Papers, arXiv.org, number 1912.08791, Nov.
• Sidra Mehtab & Jaydip Sen, 2019, "A Robust Predictive Model for Stock Price Prediction Using Deep Learning and Natural Language Processing," Papers, arXiv.org, number 1912.07700, Dec.
• Jie Fang & Shutao Xia & Jianwu Lin & Zhikang Xia & Xiang Liu & Yong Jiang, 2019, "Alpha Discovery Neural Network based on Prior Knowledge," Papers, arXiv.org, number 1912.11761, Dec, revised Nov 2020.
• K, Ashin Nishan M & ASHIQ, MUHAMMED V, 2019, "Role of Energy use in the Prediction of CO2 Emissions and Growth in India: An Application of Artificial Neural Networks (ANN)," SocArXiv, Center for Open Science, number gkpbu, Dec, DOI: 10.31219/osf.io/gkpbu.
• Simon Cramer & Torsten Trimborn, 2019, "Stylized Facts and Agent-Based Modeling," Papers, arXiv.org, number 1912.02684, Dec.
• Jiequn Han & Ruimeng Hu, 2019, "Deep Fictitious Play for Finding Markovian Nash Equilibrium in Multi-Agent Games," Papers, arXiv.org, number 1912.01809, Dec, revised Jun 2020.
• Florian Botte & Thomas Dallery, 2019, "Analyse systématique du modèle de Bhaduri-Marglin à prix flexibles. "Ca dépend de la valeur des paramètres"," Post-Print, HAL, number hal-02335695, Dec.
• Michael Benzaquen & Jean-Philippe Bouchaud, 2018, "A fractional reaction–diffusion description of supply and demand," Post-Print, HAL, number hal-02323544, Feb, DOI: 10.1140/epjb/e2017-80246-9.
• Kanai, Ryota & Fujisawa, Ippei & Tamai, Shinya & Magata, Atsushi & Yasumoto, Masahiro, 2019, "Artificial Consciousness as a Platform for Artificial General Intelligence," OSF Preprints, Center for Open Science, number e4jh2, Nov, DOI: 10.31219/osf.io/e4jh2.
• Jawwad Noor, 2019, "Intuitive Beliefs," Cowles Foundation Discussion Papers, Cowles Foundation for Research in Economics, Yale University, number 2216, Dec.
• Yosuke Uno & Ko Adachi, 2019, ""Don't know" Tells: Calculating Non-Response Bias in Firms' Inflation Expectations Using Machine Learning Techniques," Bank of Japan Working Paper Series, Bank of Japan, number 19-E-17, Dec.
• Grodecka, Anna & Hull, Isaiah, 2019, "The Impact of Local Taxes and Public Services on Property Values," Working Paper Series, Sveriges Riksbank (Central Bank of Sweden), number 374, Apr.
• Gert Bijnens & Shyngys Karimov & Jozef Konings, 2019, "Wage Indexation and Jobs. A Machine Learning Approach," Working Papers of Department of Economics, Leuven, KU Leuven, Faculty of Economics and Business (FEB), Department of Economics, Leuven, number 643831, Nov.
• Kevin Kuo, 2019, "Generative Synthesis of Insurance Datasets," Papers, arXiv.org, number 1912.02423, Dec, revised Aug 2020.
• Alexandru, Daia, 2019, "Experimented Kinetic Energy As Features For Natural Language Classification," OSF Preprints, Center for Open Science, number drwc6, Jun, DOI: 10.31219/osf.io/drwc6.
• Alexandru, Daia, 2019, "I Ntroducing A New T Echnical I Ndicator Based On Octav O Nicescu I Nformational E Nergy And Compare It With B Ollinger Bands For S&P 500 M Ovement P Redictions," OSF Preprints, Center for Open Science, number m478b, Jun, DOI: 10.31219/osf.io/m478b.
• Olga Ivanova & d'Artis Kancs & Mark Thissen, 2019, "EU Economic Modelling System," EERI Research Paper Series, Economics and Econometrics Research Institute (EERI), Brussels, number EERI RP 2019/10, Oct.
• Morris A. Davis & Jesse Gregory & Daniel A. Hartley & Kegon T. K. Tan, 2019, "Neighborhood Effects and Housing Vouchers," Working Papers, Human Capital and Economic Opportunity Working Group, number 2019-084, Dec.
• Wong, William & Tsuchiya, Naotsugu, 2020, "Evidence accumulation clustering using combinations of features," OSF Preprints, Center for Open Science, number epb6t, May, DOI: 10.31219/osf.io/epb6t.
• Dahlke, Steven, 2019, "Modeling market power on a constrained electricity network," OSF Preprints, Center for Open Science, number 9vep7, May, DOI: 10.31219/osf.io/9vep7.
• Ian Burn & Patrick Button & Luis Felipe Munguia Corella & David Neumark, 2019, "Older Workers Need Not Apply? Ageist Language in Job Ads and Age Discrimination in Hiring," NBER Working Papers, National Bureau of Economic Research, Inc, number 26552, Dec.
• Satoshi KONDO & Daisuke MIYAKAWA & Kengo SHIRAKI & Miki SUGA & Teppei USUKI, 2019, "Using Machine Learning to Detect and Forecast Accounting Fraud," Discussion papers, Research Institute of Economy, Trade and Industry (RIETI), number 19103, Dec.
• Lily Shen & Stephen L. Ross, 2019, "Information Value of Property Description: A Machine Learning Approach," Working papers, University of Connecticut, Department of Economics, number 2019-20, Dec, revised Sep 2020.
• Hoogervorst, R. & Dollevoet, T.A.B. & Maróti, G. & Huisman, D., 2019, "A Variable Neighborhood Search Heuristic for Rolling Stock Rescheduling," Econometric Institute Research Papers, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute, number EI2019-34, Dec.
• Filipe Fontanela & Antoine Jacquier & Mugad Oumgari, 2019, "A Quantum algorithm for linear PDEs arising in Finance," Papers, arXiv.org, number 1912.02753, Dec, revised Feb 2021.
• Vuong, Quan-Hoang, 2018, "Sự trỗi dậy của Computational Entrepreneurship," OSF Preprints, Center for Open Science, number 6n9wb, Dec, DOI: 10.31219/osf.io/6n9wb.
• Daisuke MIYAKAWA, 2019, "Shocks to Supply Chain Networks and Firm Dynamics: An Application of Double Machine Learning," Discussion papers, Research Institute of Economy, Trade and Industry (RIETI), number 19100, Dec.
• Zongxi Li & A. Max Reppen & Ronnie Sircar, 2019, "A Mean Field Games Model for Cryptocurrency Mining," Papers, arXiv.org, number 1912.01952, Dec, revised Jan 2022.
• Kyle Colangelo & Ying-Ying Lee, 2019, "Double debiased machine learning nonparametric inference with continuous treatments," CeMMAP working papers, Centre for Microdata Methods and Practice, Institute for Fiscal Studies, number CWP54/19, Oct.

Report NEP-CMP-2020-01-06

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: