Report NEP-BIG-2019-07-22

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:

• Bertin Martens & Songül Tolan, 2018. "Will this time be different? A review of the literature on the Impact of Artificial Intelligence on Employment, Incomes and Growth," JRC Working Papers on Digital Economy 2019-04, Joint Research Centre (Seville site).
• Catherine D'Hondt & Rudy De Winne & Eric Ghysels & Steve Raymond, 2019. "Artificial Intelligence Alter Egos: Who benefits from Robo-investing?," Papers 1907.03370, arXiv.org.
• Bertin Martens, 2018. "The impact of data access regimes on artificial intelligence and machine learning," JRC Working Papers on Digital Economy 2019-05, Joint Research Centre (Seville site).
• Michael Allan Ribers & Hannes Ullrich, 2019. "Battling Antibiotic Resistance: Can Machine Learning Improve Prescribing?," Papers 1906.03044, arXiv.org.
• Jeremy D. Turiel & Tomaso Aste, 2019. "P2P Loan acceptance and default prediction with Artificial Intelligence," Papers 1907.01800, arXiv.org.
• A Itkin, 2019. "Deep learning calibration of option pricing models: some pitfalls and solutions," Papers 1906.03507, arXiv.org.
• Emir Hrnjic & Nikodem Tomczak, 2019. "Machine learning and behavioral economics for personalized choice architecture," Papers 1907.02100, arXiv.org.
• Jose Luis Montiel Olea & Pietro Ortoleva & Mallesh M Pai & Andrea Prat, 2019. "Competing Models," Papers 1907.03809, arXiv.org, revised Nov 2021.
• Brandon Da Silva & Sylvie Shang Shi, 2019. "Style Transfer with Time Series: Generating Synthetic Financial Data," Papers 1906.03232, arXiv.org, revised Dec 2019.
• Pelau, Corina & Ene, Irina, 2018. "Consumers’ perception on human-like artificial intelligence devices," MPRA Paper 94617, University Library of Munich, Germany.
• Paola Tubaro & Antonio A. Casilli, 2019. "Micro-work, artificial intelligence and the automotive industry," Post-Print hal-02148979, HAL.
• Xinyi Li & Yinchuan Li & Yuancheng Zhan & Xiao-Yang Liu, 2019. "Optimistic Bull or Pessimistic Bear: Adaptive Deep Reinforcement Learning for Stock Portfolio Allocation," Papers 1907.01503, arXiv.org.
• Soybilgen, Baris, 2018. "Identifying US business cycle regimes using dynamic factors and neural network models," MPRA Paper 94715, University Library of Munich, Germany.
• Francois Belletti & Davis King & Kun Yang & Roland Nelet & Yusef Shafi & Yi-Fan Chen & John Anderson, 2019. "Tensor Processing Units for Financial Monte Carlo," Papers 1906.02818, arXiv.org, revised Jan 2020.
• Rémy Le Boennec & Fouad Hadj Selem & Ghazaleh Khodabandelou, 2019. "La mobilité individuelle motorisée dans les déplacements domicile-travail : préférence modale ou choix contraint ? Une approche par le machine learning," Post-Print hal-02160862, HAL.
• Fabrice Daniel, 2019. "Financial Time Series Data Processing for Machine Learning," Papers 1907.03010, arXiv.org.
• Michael Lechner & Gabriel Okasa, 2019. "Random Forest Estimation of the Ordered Choice Model," Papers 1907.02436, arXiv.org, revised Sep 2022.
• Clement Gastaud & Theophile Carniel & Jean-Michel Dalle, 2019. "The varying importance of extrinsic factors in the success of startup fundraising: competition at early-stage and networks at growth-stage," Papers 1906.03210, arXiv.org.
• Zihao Zhang & Stefan Zohren & Stephen Roberts, 2019. "Extending Deep Learning Models for Limit Order Books to Quantile Regression," Papers 1906.04404, arXiv.org.
• Hyungjun Park & Min Kyu Sim & Dong Gu Choi, 2019. "An intelligent financial portfolio trading strategy using deep Q-learning," Papers 1907.03665, arXiv.org, revised Nov 2019.
• Yuxuan Huang & Luiz Fernando Capretz & Danny Ho, 2019. "Neural Network Models for Stock Selection Based on Fundamental Analysis," Papers 1906.05327, arXiv.org.
• Rute Martins Caeiro, 2019. "From Learning to Doing: Diffusion of Agricultural Innovations in Guinea-Bissau," NBER Working Papers 26065, National Bureau of Economic Research, Inc.
• Lotfi Boudabsa & Damir Filipovic, 2019. "Machine learning with kernels for portfolio valuation and risk management," Papers 1906.03726, arXiv.org, revised May 2021.
• Sandra Johnson & Peter Robinson & Kishore Atreya & Claudio Lisco, 2019. "Invoice Financing of Supply Chains with Blockchain technology and Artificial Intelligence," Papers 1906.03306, arXiv.org.
• Erika Arraño & Katherine Jara, 2019. "Índice de Avisos Laborales de Internet," Economic Statistics Series 129, Central Bank of Chile.