Report NEP-CMP-2023-01-09

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:

• Kühl, Niklas & Schemmer, Max & Goutier, Marc & Satzger, Gerhard, 2022. "Artificial intelligence and machine learning," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 135656, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
• Zheng Cao & Raymond Guo & Wenyu Du & Jiayi Gao & Kirill V. Golubnichiy, 2022. "Optimizing Stock Option Forecasting with the Assembly of Machine Learning Models and Improved Trading Strategies," Papers 2211.15912, arXiv.org.
• Christian B. Hansen & Mark E. Schaffer & Thomas Wiemann & Achim Ahrens, 2022. "ddml: Double/debiased machine learning in Stata," Swiss Stata Conference 2022 02, Stata Users Group.
• Meisenbacher, Stephen & Norlander, Peter, 2022. "Creating Data from Unstructured Text with Context Rule Assisted Machine Learning (CRAML)," GLO Discussion Paper Series 1214, Global Labor Organization (GLO).
• Rameshwar Garg & Shriya Barpanda & Girish Rao Salanke N S & Ramya S, 2022. "Machine Learning Algorithms for Time Series Analysis and Forecasting," Papers 2211.14387, arXiv.org.
• Li, Ziqi, 2022. "Understanding Factors Influencing Willingness to Ridesharing Using Big Trip Data and Interpretable Machine Learning," OSF Preprints chy4p, Center for Open Science.
• Pierre Brugière & Gabriel Turinici, 2022. "Deep learning of Value at Risk through generative neural network models : the case of the Variational Auto Encoder," Working Papers hal-03880381, HAL.
• Sara Salamat & Nima Tavassoli & Behnam Sabeti & Reza Fahmi, 2022. "Text Representation Enrichment Utilizing Graph based Approaches: Stock Market Technical Analysis Case Study," Papers 2211.16103, arXiv.org.
• Jie Zou & Jiashu Lou & Baohua Wang & Sixue Liu, 2022. "A Novel Deep Reinforcement Learning Based Automated Stock Trading System Using Cascaded LSTM Networks," Papers 2212.02721, arXiv.org, revised Jul 2023.
• Morteza Tahami Pour Zarandi & Mehdi Ghasemi Meymandi & Mohammad Hemami, 2022. "A comprehensive study of cotton price fluctuations using multiple Econometric and LSTM neural network models," Papers 2212.01584, arXiv.org, revised Dec 2022.
• Jan Ditzen & Francesco Ravazzolo, 2022. "Dominant Drivers of National Inflation," BEMPS - Bozen Economics & Management Paper Series BEMPS97, Faculty of Economics and Management at the Free University of Bozen.
• Luigi Biagini & Simone Severini, 2022. "Can Machine Learning discover the determining factors in participation in insurance schemes? A comparative analysis," Papers 2212.03092, arXiv.org, revised Dec 2022.
• Damian Kisiel & Denise Gorse, 2022. "Axial-LOB: High-Frequency Trading with Axial Attention," Papers 2212.01807, arXiv.org.
• Ziwei Mei & Zhentao Shi & Peter C. B. Phillips, 2022. "The boosted HP filter is more general than you might think," Cowles Foundation Discussion Papers 2348, Cowles Foundation for Research in Economics, Yale University.
• Massimiliano Fessina & Giambattista Albora & Andrea Tacchella & Andrea Zaccaria, 2022. "Which products activate a product? An explainable machine learning approach," Papers 2212.03094, arXiv.org.
• Thi Thu Giang Nguyen & Robert Ślepaczuk, 2022. "The efficiency of various types of input layers of LSTM model in investment strategies on S&P500 index," Working Papers 2022-29, Faculty of Economic Sciences, University of Warsaw.
• Marc Wildi & Branka Hadji Misheva, 2022. "A Time Series Approach to Explainability for Neural Nets with Applications to Risk-Management and Fraud Detection," Papers 2212.02906, arXiv.org.
• Edouard Ribes, 2022. "Using classification techniques to accelerate client discovery: a case study for wealth management services," Working Papers hal-03887759, HAL.
• Kim Ristolainen, 2022. "Narrative Triggers of Information Sensitivity," Discussion Papers 156, Aboa Centre for Economics.
• Lokman Abbas-Turki & St'ephane Cr'epey & Bouazza Saadeddine, 2022. "Pathwise CVA Regressions With Oversimulated Defaults," Papers 2211.17005, arXiv.org.
• Tamay Besiroglu & Nicholas Emery-Xu & Neil Thompson, 2022. "Economic impacts of AI-augmented R&D," Papers 2212.08198, arXiv.org, revised Jan 2023.
• Edward I. Altman & Marco Balzano & Alessandro Giannozzi & Stjepan Srhoj, 2022. "Revisiting SME default predictors: The Omega Score," Working Papers 2022-19, Faculty of Economics and Statistics, Universität Innsbruck.
• Luigi Biagini, 2022. "Applications of Machine Learning for the Ratemaking in Agricultural Insurances," Papers 2212.03114, arXiv.org, revised Dec 2022.
• Mathias Valla & Xavier Milhaud & Anani Ayodélé Olympio, 2023. "Including individual Customer Lifetime Value and competing risks in tree-based lapse management strategy," Working Papers hal-03903047, HAL.
• Laura Bonacorsi & Vittoria Cerasi & Paola Galfrascoli & Matteo Manera, 2022. "ESG Factors and Firms' Credit Risk," Working Papers 507, University of Milano-Bicocca, Department of Economics, revised Dec 2022.
• Jingruo Sun, 2022. "Deep Galerkin Method for Mean Field Control Problem," Papers 2212.01719, arXiv.org, revised Feb 2024.
• Massimo Ferrari Minesso & Maria Sole Pagliari, 2022. "DSGE Nash: solving Nash Games in Macro Models With an application to optimal monetary policy under monopolistic commodity pricing," Working papers 884, Banque de France.
• BARRIOS Salvador & REUT Adriana & RISCADO Sara & VAN DER WIELEN Wouter, 2022. "Dynamic scoring of tax reforms in real time," JRC Working Papers on Taxation & Structural Reforms 2022-14, Joint Research Centre.
• Taylan Kabbani, 2022. "Metaheuristic Approach to Solve Portfolio Selection Problem," Papers 2211.17193, arXiv.org.
• Kühl, Niklas & Goutier, Marc & Baier, Lucas & Wolff, Clemens & Martin, Dominik, 2022. "Human vs. supervised machine learning: Who learns patterns faster?," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 135657, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
• Joel Terschuur, 2022. "Educational Inequality of Opportunity and Mobility in Europe," Papers 2212.02407, arXiv.org, revised Mar 2023.
• Griselda Deelstra & Lech A. Grzelak & Felix L. Wolf, 2022. "Accelerated Computations of Sensitivities for xVA," Papers 2211.17026, arXiv.org, revised Jan 2024.
• Tauchert, Christoph, 2022. "Adoption of AI-based Information Systems from an Organizational and User Perspective," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 135700, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
• Axenbeck, Janna & Berner, Anne & Kneib, Thomas, 2022. "What drives the relationship between digitalization and industrial energy demand? Exploring firm-level heterogeneity," ZEW Discussion Papers 22-059, ZEW - Leibniz Centre for European Economic Research.
• Michael E. Mura, 2022. "Moate Simulation of Stochastic Processes," Papers 2212.08509, arXiv.org.