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Report NEP-BIG-2019-02-11
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:
- Adam Hale Shapiro & Daniel J. Wilson, 2021, "Taking the Fed at its Word: A New Approach to Estimating Central Bank Objectives using Text Analysis," Working Paper Series, Federal Reserve Bank of San Francisco, number 2019-2, Jan, DOI: 10.24148/wp2019-02.
- Hunt Allcott & Luca Braghieri & Sarah Eichmeyer & Matthew Gentzkow, 2019, "The Welfare Effects of Social Media," NBER Working Papers, National Bureau of Economic Research, Inc, number 25514, Jan.
- Faisal I Qureshi, 2018, "Investigating Limit Order Book Characteristics for Short Term Price Prediction: a Machine Learning Approach," Papers, arXiv.org, number 1901.10534, Dec.
- Frondel, Manuel & Kussel, Gerhard & Sommer, Stephan & Vance, Colin, 2019, "Local cost for global benefit: The case of wind turbines," Ruhr Economic Papers, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen, number 791, revised 2019, DOI: 10.4419/86788919.
- Leonardo Felizardo & Afonso Pinto, 2019, "A Study on Neural Network Architecture Applied to the Prediction of Brazilian Stock Returns," Papers, arXiv.org, number 1901.09143, Jan.
- Stephany, Fabian, 2018, "It is not only size that matters: How unique is the Estonian e-governance success story?," Working Papers, Agenda Austria, number 15.
- Shuaiqiang Liu & Cornelis W. Oosterlee & Sander M. Bohte, 2019, "Pricing options and computing implied volatilities using neural networks," Papers, arXiv.org, number 1901.08943, Jan, revised Apr 2019.
- Guanhao Feng & Jingyu He, 2019, "Factor Investing: A Bayesian Hierarchical Approach," Papers, arXiv.org, number 1902.01015, Feb, revised Sep 2020.
- Karlson Pfannschmidt & Pritha Gupta & Bjorn Haddenhorst & Eyke Hullermeier, 2019, "Learning Context-Dependent Choice Functions," Papers, arXiv.org, number 1901.10860, Jan, revised Oct 2021.
- Ahrens, Achim & Hansen, Christian B. & Schaffer, Mark E, 2019, "lassopack: Model Selection and Prediction with Regularized Regression in Stata," IZA Discussion Papers, IZA Network @ LISER, number 12081, Jan.
- Brühl, Volker, 2019, "Big Data, Data Mining, Machine Learning und Predictive Analytics: Ein konzeptioneller Überblick," CFS Working Paper Series, Center for Financial Studies (CFS), number 617.