Report NEP-BIG-2017-07-23

This is the archive for NEP-BIG, a report on new working papers in the area of Big Data. Tom Coupé issued this report. It is usually issued weekly.

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Other reports in NEP-BIG

The following items were announced in this report:

• Dominique Guegan & Bertrand Hassani, 2017. "Regulatory Learning: how to supervise machine learning models? An application to credit scoring," Documents de travail du Centre d'Economie de la Sorbonne 17034, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
• Xiaojiao Yu, 2017. "Machine learning application in online lending risk prediction," Papers 1707.04831, arXiv.org.
• Vasilios Plakandaras & Rangan Gupta & Periklis Gogas & Theophilos Papadimitriou, 2017. "Forecasting the U.S. Real House Price Index," Papers 1707.04868, arXiv.org.
• Matthew F Dixon, 2017. "Sequence Classification of the Limit Order Book using Recurrent Neural Networks," Papers 1707.05642, arXiv.org.
• Nalan Basturk & Stefano Grassi & Lennart Hoogerheide & Anne Opschoor & Herman K. van Dijk, 2017. "The R package MitISEM: Efficient and robust simulation procedures for Bayesian inference," Working Paper 2017/10, Norges Bank.
• Takaya Fukui & Akihiko Takahashi, 2017. ""Investment with deep learning" (in Japanese)," CIRJE J-Series CIRJE-J-287, CIRJE, Faculty of Economics, University of Tokyo.