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 (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:

• Item repec:ipt:decwpa:2018-08 is not listed on IDEAS anymore

• Catherine D'Hondt & Rudy De Winne & Eric Ghysels & Steve Raymond, 2019, "Artificial Intelligence Alter Egos: Who benefits from Robo-investing?," Papers, arXiv.org, number 1907.03370, Jul.
• Item repec:ipt:decwpa:2018-09 is not listed on IDEAS anymore

• Michael Allan Ribers & Hannes Ullrich, 2019, "Battling Antibiotic Resistance: Can Machine Learning Improve Prescribing?," Papers, arXiv.org, number 1906.03044, Jun.
• Jeremy D. Turiel & Tomaso Aste, 2019, "P2P Loan acceptance and default prediction with Artificial Intelligence," Papers, arXiv.org, number 1907.01800, Jul.
• A Itkin, 2019, "Deep learning calibration of option pricing models: some pitfalls and solutions," Papers, arXiv.org, number 1906.03507, Jun.
• Emir Hrnjic & Nikodem Tomczak, 2019, "Machine learning and behavioral economics for personalized choice architecture," Papers, arXiv.org, number 1907.02100, Jul.
• Jose Luis Montiel Olea & Pietro Ortoleva & Mallesh M Pai & Andrea Prat, 2019, "Competing Models," Papers, arXiv.org, number 1907.03809, Jul, revised Nov 2021.
• Brandon Da Silva & Sylvie Shang Shi, 2019, "Style Transfer with Time Series: Generating Synthetic Financial Data," Papers, arXiv.org, number 1906.03232, May, revised Dec 2019.
• Pelau, Corina & Ene, Irina, 2018, "Consumers’ perception on human-like artificial intelligence devices," MPRA Paper, University Library of Munich, Germany, number 94617.
• Paola Tubaro & Antonio A. Casilli, 2019, "Micro-work, artificial intelligence and the automotive industry," Post-Print, HAL, number hal-02148979, Jun, DOI: 10.1007/s40812-019-00121-1.
• Xinyi Li & Yinchuan Li & Yuancheng Zhan & Xiao-Yang Liu, 2019, "Optimistic Bull or Pessimistic Bear: Adaptive Deep Reinforcement Learning for Stock Portfolio Allocation," Papers, arXiv.org, number 1907.01503, Jun.
• Soybilgen, Baris, 2018, "Identifying US business cycle regimes using dynamic factors and neural network models," MPRA Paper, University Library of Munich, Germany, number 94715, Jul.
• Francois Belletti & Davis King & Kun Yang & Roland Nelet & Yusef Shafi & Yi-Fan Chen & John Anderson, 2019, "Tensor Processing Units for Financial Monte Carlo," Papers, arXiv.org, number 1906.02818, Jun, 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, number hal-02160862, Jun.
• Fabrice Daniel, 2019, "Financial Time Series Data Processing for Machine Learning," Papers, arXiv.org, number 1907.03010, Jul.
• Michael Lechner & Gabriel Okasa, 2019, "Random Forest Estimation of the Ordered Choice Model," Papers, arXiv.org, number 1907.02436, Jul, 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, arXiv.org, number 1906.03210, Jun.
• Zihao Zhang & Stefan Zohren & Stephen Roberts, 2019, "Extending Deep Learning Models for Limit Order Books to Quantile Regression," Papers, arXiv.org, number 1906.04404, Jun.
• Hyungjun Park & Min Kyu Sim & Dong Gu Choi, 2019, "An intelligent financial portfolio trading strategy using deep Q-learning," Papers, arXiv.org, number 1907.03665, Jul, revised Nov 2019.
• Yuxuan Huang & Luiz Fernando Capretz & Danny Ho, 2019, "Neural Network Models for Stock Selection Based on Fundamental Analysis," Papers, arXiv.org, number 1906.05327, Jun.
• Rute Martins Caeiro, 2019, "From Learning to Doing: Diffusion of Agricultural Innovations in Guinea-Bissau," NBER Working Papers, National Bureau of Economic Research, Inc, number 26065, Jul.
• Lotfi Boudabsa & Damir Filipovic, 2019, "Machine learning with kernels for portfolio valuation and risk management," Papers, arXiv.org, number 1906.03726, Jun, revised May 2021.
• Sandra Johnson & Peter Robinson & Kishore Atreya & Claudio Lisco, 2019, "Invoice Financing of Supply Chains with Blockchain technology and Artificial Intelligence," Papers, arXiv.org, number 1906.03306, May.
• Erika Arraño & Katherine Jara, 2019, "Índice de Avisos Laborales de Internet," Economic Statistics Series, Central Bank of Chile, number 129, Jul.

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 (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: