Report NEP-BIG-2020-03-09

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:

• de Cornière, Alexandre & Taylor, Greg, 2020. "Data and Competition: a General Framework with Applications to Mergers, Market Structure, and Privacy Policy," TSE Working Papers 20-1076, Toulouse School of Economics (TSE).
• Daniel Guterding, 2020. "Inventory effects on the price dynamics of VSTOXX futures quantified via machine learning," Papers 2002.08207, arXiv.org.
• Tesi Aliaj & Aris Anagnostopoulos & Stefano Piersanti, 2020. "Firms Default Prediction with Machine Learning," Papers 2002.11705, arXiv.org.
• Masaya Abe & Kei Nakagawa, 2020. "Cross-sectional Stock Price Prediction using Deep Learning for Actual Investment Management," Papers 2002.06975, arXiv.org.
• Yusuke Uchiyama & Kei Nakagawa, 2020. "TPLVM: Portfolio Construction by Student's $t$-process Latent Variable Model," Papers 2002.06243, arXiv.org.
• Born, Andreas & Janssen, Aljoscha, 2020. "Does a District-Vote Matter for the Behavior of Politicians? A Textual Analysis of Parliamentary Speeches," Working Paper Series 1320, Research Institute of Industrial Economics.
• Oksana Bashchenko & Alexis Marchal, 2020. "Deep Learning for Asset Bubbles Detection," Papers 2002.06405, arXiv.org.
• Greg Lewis & Vasilis Syrgkanis, 2020. "Double/Debiased Machine Learning for Dynamic Treatment Effects via g-Estimation," Papers 2002.07285, arXiv.org, revised Jun 2021.
• Matthew Dixon & Igor Halperin, 2020. "G-Learner and GIRL: Goal Based Wealth Management with Reinforcement Learning," Papers 2002.10990, arXiv.org.
• Evgeny Ponomarev & Ivan Oseledets & Andrzej Cichocki, 2020. "Using Reinforcement Learning in the Algorithmic Trading Problem," Papers 2002.11523, arXiv.org.
• Yusuke Narita & Shota Yasui & Kohei Yata, 2020. "Debiased Off-Policy Evaluation for Recommendation Systems," Papers 2002.08536, arXiv.org, revised Aug 2021.
• Chi Chen & Li Zhao & Wei Cao & Jiang Bian & Chunxiao Xing, 2020. "Trimming the Sail: A Second-order Learning Paradigm for Stock Prediction," Papers 2002.06878, arXiv.org.
• Shaolong Sun & Yanzhao Li & Ju-e Guo & Shouyang Wang, 2020. "Tourism Demand Forecasting: An Ensemble Deep Learning Approach," Papers 2002.07964, arXiv.org, revised Jan 2021.
• Carmine de Franco & Christophe Geissler & Vincent Margot & Bruno Monnier, 2020. "ESG investments: Filtering versus machine learning approaches," Papers 2002.07477, arXiv.org, revised Apr 2020.
• Matteo Cinelli & Valerio Ficcadenti & Jessica Riccioni, 2020. "The interconnectedness of the economic content in the speeches of the US Presidents," Papers 2002.07880, arXiv.org.