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Report NEP-BIG-2019-05-27
This is the archive for NEP-BIG, a report on new working papers in the area of Big Data. Tom Coupé (Tom Coupe) issued this report. It is usually issued weekly.Subscribe to this report: email, RSS, or Mastodon, or Bluesky.
Other reports in NEP-BIG
The following items were announced in this report:
- Valentin Zelenyuk, 2019, "Data Envelopment Analysis and Business Analytics: The Big Data Challenges and Some Solutions," CEPA Working Papers Series, School of Economics, University of Queensland, Australia, number WP072019, May.
- Ho Fai Chan & Bruno S. Frey & Ahmed Skali & Benno Torgler, 2019, "Political Entrenchment and GDP Misreporting," CREMA Working Paper Series, Center for Research in Economics, Management and the Arts (CREMA), number 2019-02, May.
- Daron Acemoglu & Pascual Restrepo, 2018, "Artificial Intelligence, Automation and Work," Boston University - Department of Economics - The Institute for Economic Development Working Papers Series, Boston University - Department of Economics, number dp-298, Jan.
- 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.
- Shangeth Rajaa & Jajati Keshari Sahoo, 2019, "Convolutional Feature Extraction and Neural Arithmetic Logic Units for Stock Prediction," Papers, arXiv.org, number 1905.07581, May.
- 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.
- 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.
- Item repec:iab:iabdpa:201913 is not listed on IDEAS anymore
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.