Report NEP-CMP-2019-05-27

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:

• Daniel Ladley, 2019, "The Design and Regulation of High Frequency Traders," Discussion Papers in Economics, Division of Economics, School of Business, University of Leicester, number 19/02, Mar.
• Chunding Li & Jing Wang & John Whalley, 2019, "Trade Protectionism and US Manufacturing Employment," NBER Working Papers, National Bureau of Economic Research, Inc, number 25860, May.
• Gawlitza, Joshua & Sturm, Timo & Spohrer, Kai & Henzler, Thomas & Akin, Ibrahim & Schönberg, Stefan & Borggrefe, Martin & Haubenreisser, Holger & Trinkmann, Frederik, 2019, "Predicting Pulmonary Function Testing from Quantified Computed Tomography Using Machine Learning Algorithms in Patients with COPD," 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 113226, Mar.
• Kim, T.Y., 2018, "Improving warehouse responsiveness by job priority management," Econometric Institute Research Papers, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute, number EI2018-02, Jan.
• Christopher Kath & Florian Ziel, 2019, "Conformal Prediction Interval Estimations with an Application to Day-Ahead and Intraday Power Markets," Papers, arXiv.org, number 1905.07886, May, revised Sep 2020.
• Reaz Chowdhury & M. Arifur Rahman & M. Sohel Rahman & M. R. C. Mahdy, 2019, "Predicting and Forecasting the Price of Constituents and Index of Cryptocurrency Using Machine Learning," Papers, arXiv.org, number 1905.08444, May.
• de Kok, Ties, 2019, "Essays on reporting and information processing," Other publications TiSEM, Tilburg University, School of Economics and Management, number 468fd12b-19c0-4c7b-a33a-6.
• Wu, Guoyuan & Ye, Fei & Hao, Peng & Esaid, Danial & Boriboonsomsin, Kanok & Barth, Matthew J., 2019, "Deep Learning–based Eco-driving System for Battery Electric Vehicles," Institute of Transportation Studies, Working Paper Series, Institute of Transportation Studies, UC Davis, number qt9fz140zt, May.
• Sudiksha Joshi, 2019, "Time Series Analysis and Forecasting of the US Housing Starts using Econometric and Machine Learning Model," Papers, arXiv.org, number 1905.07848, May.
• Patel, Abhishek & Anand, Rajesh, 2019, "Fast Security Constraint Unit Commitment by Utilizing Chaotic Crow Search Algorithm," MPRA Paper, University Library of Munich, Germany, number 93971, May.
• Samuel Asante Gyamerah & Philip Ngare & Dennis Ikpe, 2019, "Hedging crop yields against weather uncertainties -- a weather derivative perspective," Papers, arXiv.org, number 1905.07546, May, revised Aug 2019.
• Krupitzer, Christian & Drechsel, Guido & Mateja, Deborah & Pollklasener, Alina & Schrage, Florian & Sturm, Timo & Tomasovic, Aleksandar & Becker, Christian, 2018, "Using Spreadsheet-defined Rules for Reasoning in Self-Adaptive Systems," 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 113225, Mar.
• Arthur Turrell & Bradley J. Speigner & Jyldyz Djumalieva & David Copple & James Thurgood, 2019, "Transforming Naturally Occurring Text Data Into Economic Statistics: The Case of Online Job Vacancy Postings," NBER Working Papers, National Bureau of Economic Research, Inc, number 25837, May.
• Seth G. Benzell & Laurence J. Kotlikoff & Guillermo Lagarda & Yifan Ye, 2018, "Simulating U.S. Business Cash Flow Taxation in a 17-Region Global Model," Boston University - Department of Economics - The Institute for Economic Development Working Papers Series, Boston University - Department of Economics, number dp-312, Nov.
• Ludovic Gouden`ege & Andrea Molent & Antonino Zanette, 2019, "Machine Learning for Pricing American Options in High-Dimensional Markovian and non-Markovian models," Papers, arXiv.org, number 1905.09474, May, revised Jun 2019.
• Shangeth Rajaa & Jajati Keshari Sahoo, 2019, "Convolutional Feature Extraction and Neural Arithmetic Logic Units for Stock Prediction," Papers, arXiv.org, number 1905.07581, May.
• Lisa R. Goldberg & Saad Mouti, 2019, "Sustainable Investing and the Cross-Section of Returns and Maximum Drawdown," Papers, arXiv.org, number 1905.05237, May, revised Dec 2023.
• Item repec:iab:iabdpa:201913 is not listed on IDEAS anymore

• Periklis Gogas & Theophilos Papadimitriou & Vasilios Plakandaras & Rangan Gupta, 2019, "The Informational Content of the Term-Spread in Forecasting the U.S. Inflation Rate: A Nonlinear Approach," DUTH Research Papers in Economics, Democritus University of Thrace, Department of Economics, number 3-2016, May.
• Berardi, Michele, 2019, "A probabilistic interpretation of the constant gain algorithm," MPRA Paper, University Library of Munich, Germany, number 94023, May.

Report NEP-CMP-2019-05-27

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: