Report NEP-BIG-2019-04-15

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:

• Shihao Gu & Bryan T. Kelly & Dacheng Xiu, 2018. "Empirical Asset Pricing via Machine Learning," Swiss Finance Institute Research Paper Series 18-71, Swiss Finance Institute.
• Naudé, Wim, 2019. "The Race against the Robots and the Fallacy of the Giant Cheesecake: Immediate and Imagined Impacts of Artificial Intelligence," IZA Discussion Papers 12218, Institute of Labor Economics (IZA).
• Fossen, Frank M. & Sorgner, Alina, 2019. "New Digital Technologies and Heterogeneous Employment and Wage Dynamics in the United States: Evidence from Individual-Level Data," IZA Discussion Papers 12242, Institute of Labor Economics (IZA).
• Adamantios Ntakaris & Giorgio Mirone & Juho Kanniainen & Moncef Gabbouj & Alexandros Iosifidis, 2019. "Feature Engineering for Mid-Price Prediction with Deep Learning," Papers 1904.05384, arXiv.org, revised Jun 2019.
• Arianna Martinelli & Andrea Mina & Massimo Moggi, 2019. "The Enabling Technologies of Industry 4.0: Examining the Seeds of the Fourth Industrial Revolution," LEM Papers Series 2019/09, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
• Antonio Lima & Hasan Bakhshi, 2018. "Classifying occupations using web-based job advertisements: an application to STEM and creative occupations," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2018-08, Economic Statistics Centre of Excellence (ESCoE).
• Feng Zhou & Zhang Qun & Didier Sornette & Liu Jiang, 2018. "Cascading Logistic Regression Onto Gradient Boosted Decision Trees to Predict Stock Market Changes Using Technical Analysis," Swiss Finance Institute Research Paper Series 18-50, Swiss Finance Institute, revised Aug 2018.
• Storm, Hugo & Heckelei, Thomas & Baylis, Kathy & Mittenzwei, Klaus, 2019. "Identifying effects of farm subsidies on structural change using neural networks," Discussion Papers 287343, University of Bonn, Institute for Food and Resource Economics.
• Hali Edison & Hector Carcel, 2019. "Text Data Analysis Using Latent Dirichlet Allocation: An Application to FOMC Transcripts," Bank of Lithuania Discussion Paper Series 11, Bank of Lithuania.
• Bryan Lim & Stefan Zohren & Stephen Roberts, 2019. "Enhancing Time Series Momentum Strategies Using Deep Neural Networks," Papers 1904.04912, arXiv.org, revised Sep 2020.
• Claudia Biancotti & Paolo Ciocca, 2019. "Opening Internet Monopolies to Competition with Data Sharing Mandates," Policy Briefs PB19-3, Peterson Institute for International Economics.
• Item repec:spo:wpecon:info:hdl:2441/3tcpvf3sd399op9sgtn8tq5bhd is not listed on IDEAS anymore

• Item repec:spo:wpmain:info:hdl:2441/3tcpvf3sd399op9sgtn8tq5bhd is not listed on IDEAS anymore

• Pauline Affeldt & Tomaso Duso & Florian Szücs, 2019. "25 Years of European Merger Control," Discussion Papers of DIW Berlin 1797, DIW Berlin, German Institute for Economic Research.
• James B. Bullard, 2018. "Welcoming Remarks: at the Sixth Annual Community Banking in the 21st Century Research and Policy Conference, Federal Reserve System, Conference of State Bank Supervisors (CSBS) and Federal Deposit Ins," Speech 322, Federal Reserve Bank of St. Louis.
• Pierre Henry-Labordere, 2019. "(Martingale) Optimal Transport And Anomaly Detection With Neural Networks: A Primal-dual Algorithm," Papers 1904.04546, arXiv.org, revised Apr 2019.
• Giovanni Peri & Akira Sasahara, 2019. "The Impact of Global Warming on Rural-Urban Migrations: Evidence from Global Big Data," NBER Working Papers 25728, National Bureau of Economic Research, Inc.