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. 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:

• Item repec:dar:wpaper:135656 is not listed on IDEAS anymore

• 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, arXiv.org, number 2211.15912, Nov.
• Christian B. Hansen & Mark E. Schaffer & Thomas Wiemann & Achim Ahrens, 2022, "ddml: Double/debiased machine learning in Stata," Swiss Stata Conference 2022, Stata Users Group, number 02, Nov.
• Meisenbacher, Stephen & Norlander, Peter, 2022, "Creating Data from Unstructured Text with Context Rule Assisted Machine Learning (CRAML)," GLO Discussion Paper Series, Global Labor Organization (GLO), number 1214.
• Rameshwar Garg & Shriya Barpanda & Girish Rao Salanke N S & Ramya S, 2022, "Machine Learning Algorithms for Time Series Analysis and Forecasting," Papers, arXiv.org, number 2211.14387, Nov.
• Li, Ziqi, 2022, "Understanding Factors Influencing Willingness to Ridesharing Using Big Trip Data and Interpretable Machine Learning," OSF Preprints, Center for Open Science, number chy4p, Apr, DOI: 10.31219/osf.io/chy4p.
• Item repec:hal:wpaper:hal-03880381 is not listed on IDEAS anymore

• Sara Salamat & Nima Tavassoli & Behnam Sabeti & Reza Fahmi, 2022, "Text Representation Enrichment Utilizing Graph based Approaches: Stock Market Technical Analysis Case Study," Papers, arXiv.org, number 2211.16103, Nov.
• Jie Zou & Jiashu Lou & Baohua Wang & Sixue Liu, 2022, "A Novel Deep Reinforcement Learning Based Automated Stock Trading System Using Cascaded LSTM Networks," Papers, arXiv.org, number 2212.02721, Dec, 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, arXiv.org, number 2212.01584, Dec, revised Dec 2022.
• Jan Ditzen & Francesco Ravazzolo, 2022, "Dominant Drivers of National Inflation," BEMPS - Bozen Economics & Management Paper Series, Faculty of Economics and Management at the Free University of Bozen, number BEMPS97, Dec.
• Luigi Biagini & Simone Severini, 2022, "Can Machine Learning discover the determining factors in participation in insurance schemes? A comparative analysis," Papers, arXiv.org, number 2212.03092, Dec, revised Dec 2022.
• Damian Kisiel & Denise Gorse, 2022, "Axial-LOB: High-Frequency Trading with Axial Attention," Papers, arXiv.org, number 2212.01807, Dec.
• Ziwei Mei & Zhentao Shi & Peter C. B. Phillips, 2022, "The boosted HP filter is more general than you might think," Cowles Foundation Discussion Papers, Cowles Foundation for Research in Economics, Yale University, number 2348, Sep.
• Massimiliano Fessina & Giambattista Albora & Andrea Tacchella & Andrea Zaccaria, 2022, "Which products activate a product? An explainable machine learning approach," Papers, arXiv.org, number 2212.03094, Dec.
• 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, Faculty of Economic Sciences, University of Warsaw, number 2022-29.
• Marc Wildi & Branka Hadji Misheva, 2022, "A Time Series Approach to Explainability for Neural Nets with Applications to Risk-Management and Fraud Detection," Papers, arXiv.org, number 2212.02906, Dec.
• Edouard Ribes, 2022, "Using classification techniques to accelerate client discovery: a case study for wealth management services," Working Papers, HAL, number hal-03887759, Dec.
• Kim Ristolainen, 2022, "Narrative Triggers of Information Sensitivity," Discussion Papers, Aboa Centre for Economics, number 156, Dec.
• Lokman Abbas-Turki & St'ephane Cr'epey & Bouazza Saadeddine, 2022, "Pathwise CVA Regressions With Oversimulated Defaults," Papers, arXiv.org, number 2211.17005, Nov.
• Tamay Besiroglu & Nicholas Emery-Xu & Neil Thompson, 2022, "Economic impacts of AI-augmented R&D," Papers, arXiv.org, number 2212.08198, Dec, revised Jan 2023.
• Edward I. Altman & Marco Balzano & Alessandro Giannozzi & Stjepan Srhoj, 2022, "Revisiting SME default predictors: The Omega Score," Working Papers, Faculty of Economics and Statistics, Universität Innsbruck, number 2022-19.
• Luigi Biagini, 2022, "Applications of Machine Learning for the Ratemaking in Agricultural Insurances," Papers, arXiv.org, number 2212.03114, Dec, revised Dec 2022.
• Item repec:hal:wpaper:hal-03903047 is not listed on IDEAS anymore

• Laura Bonacorsi & Vittoria Cerasi & Paola Galfrascoli & Matteo Manera, 2022, "ESG Factors and Firms' Credit Risk," Working Papers, University of Milano-Bicocca, Department of Economics, number 507, Dec, revised Dec 2022.
• Jingruo Sun, 2022, "Deep Galerkin Method for Mean Field Control Problem," Papers, arXiv.org, number 2212.01719, Dec, 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, Banque de France, number 884.
• 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, Joint Research Centre, number 2022-14, Dec.
• Taylan Kabbani, 2022, "Metaheuristic Approach to Solve Portfolio Selection Problem," Papers, arXiv.org, number 2211.17193, Nov.
• 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), Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL), number 135657.
• Joel Terschuur, 2022, "Educational Inequality of Opportunity and Mobility in Europe," Papers, arXiv.org, number 2212.02407, Dec, revised Mar 2023.
• Griselda Deelstra & Lech A. Grzelak & Felix L. Wolf, 2022, "Accelerated Computations of Sensitivities for xVA," Papers, arXiv.org, number 2211.17026, Nov, 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), Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL), number 135700.
• Axenbeck, Janna & Berner, Anne & Kneib, Thomas, 2022, "What drives the relationship between digitalization and industrial energy demand? Exploring firm-level heterogeneity," ZEW Discussion Papers, ZEW - Leibniz Centre for European Economic Research, number 22-059.
• Michael E. Mura, 2022, "Moate Simulation of Stochastic Processes," Papers, arXiv.org, number 2212.08509, Dec.

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. 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: