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Report NEP-BIG-2020-09-21
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:
- Jian Pei, 2020, "A Survey on Data Pricing: from Economics to Data Science," Papers, arXiv.org, number 2009.04462, Sep, revised Nov 2020.
- Foltas, Alexander, 2020, "Testing investment forecast efficiency with textual data," Working Papers, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin, number 19, DOI: 10.18452/21651.
- Stefano Bianchini & Moritz Muller & Pierre Pelletier, 2020, "Deep Learning in Science," Papers, arXiv.org, number 2009.01575, Sep, revised Sep 2020.
- Zhiqiang Ma & Grace Bang & Chong Wang & Xiaomo Liu, 2020, "Towards Earnings Call and Stock Price Movement," Papers, arXiv.org, number 2009.01317, Aug.
- Zhengxin Joseph Ye & Bjorn W. Schuller, 2020, "Capturing dynamics of post-earnings-announcement drift using genetic algorithm-optimised supervised learning," Papers, arXiv.org, number 2009.03094, Sep.
- Shuaiqiang Liu & Lech A. Grzelak & Cornelis W. Oosterlee, 2020, "The Seven-League Scheme: Deep learning for large time step Monte Carlo simulations of stochastic differential equations," Papers, arXiv.org, number 2009.03202, Sep, revised Sep 2021.
- Jesús Fernández-Villaverde & Samuel Hurtado & Galo Nuño, 2020, "Financial Frictions and the Wealth Distribution," CESifo Working Paper Series, CESifo, number 8482.
- Boeing, Geoff, 2020, "Exploring Urban Form Through Openstreetmap Data: A Visual Introduction," SocArXiv, Center for Open Science, number rnwgv, Aug, DOI: 10.31219/osf.io/rnwgv.
- Yang Ning & Sida Peng & Jing Tao, 2020, "Doubly Robust Semiparametric Difference-in-Differences Estimators with High-Dimensional Data," Papers, arXiv.org, number 2009.03151, Sep.
- Kayo MURAKAMI & Hideki SHIMADA & Yoshiaki USHIFUSA & Takanori IDA, 2020, "Heterogeneous Treatment Effects of Nudge and Rebate:Causal Machine Learning in a Field Experiment on Electricity Conservation," Discussion papers, Graduate School of Economics , Kyoto University, number e-20-003, Sep.
- Gries, Thomas & Naudé, Wim, 2020, "Artificial Intelligence, Income Distribution and Economic Growth," GLO Discussion Paper Series, Global Labor Organization (GLO), number 632.
- Yan Wang & Xuelei Sherry Ni, 2020, "Improving Investment Suggestions for Peer-to-Peer (P2P) Lending via Integrating Credit Scoring into Profit Scoring," Papers, arXiv.org, number 2009.04536, Sep.
- Eric Benhamou & David Saltiel & Jean-Jacques Ohana & Jamal Atif, 2020, "Detecting and adapting to crisis pattern with context based Deep Reinforcement Learning," Papers, arXiv.org, number 2009.07200, Sep, revised Nov 2020.
- Qiao Zhou & Ningning Liu, 2020, "A Stock Prediction Model Based on DCNN," Papers, arXiv.org, number 2009.03239, Sep.
- Stephanie Assad & Robert Clark & Daniel Ershov & Lei Xu, 2020, "Algorithmic Pricing and Competition: Empirical Evidence from the German Retail Gasoline Market," CESifo Working Paper Series, CESifo, number 8521.
- Danielle Li & Lindsey R. Raymond & Peter Bergman, 2020, "Hiring as Exploration," NBER Working Papers, National Bureau of Economic Research, Inc, number 27736, Aug.
- Pihnastyi, Oleh & Khodusov, Valery, 2020, "Neural model of conveyor type transport system," MPRA Paper, University Library of Munich, Germany, number 101527, May, revised 01 May 2020.
- Bonacini, Luca & Gallo, Giovanni & Patriarca, Fabrizio, 2020, "Identifying policy challenges of COVID-19 in hardly reliable data and judging the success of lockdown measures," GLO Discussion Paper Series, Global Labor Organization (GLO), number 534 [pre.].
- Gänßle, Sophia, 2020, "Big data comes to Hollywood: Audiovisuelle Medienmärkte im digitalen Zeitalter," Ilmenau Economics Discussion Papers, Ilmenau University of Technology, Institute of Economics, number 144.
- Nicholas Economides & Ioannis Lianos, 2020, "Restrictions on Privacy and Exploitation in the Digital Economy: A Market Failure Perspective," Working Papers, NET Institute, number 20-05, Sep.
- A. Fronzetti Colladon & S. Grassi & F. Ravazzolo & F. Violante, 2020, "Forecasting financial markets with semantic network analysis in the COVID-19 crisis," Papers, arXiv.org, number 2009.04975, Sep, revised Jul 2023.
- Chen, Nan-Kuang & Cheng, Han-Liang, 2020, "A Study of Financial Cycles and the Macroeconomy in Taiwan," MPRA Paper, University Library of Munich, Germany, number 101296, Jun.
- Angelo Cozzubo, 2020, "The social costs of crime over trust: An approach with machine learning," 2020 Stata Conference, Stata Users Group, number 27, Aug.
- Andrew Bacher-Hicks & Joshua S. Goodman & Christine Mulhern, 2020, "Inequality in Household Adaptation to Schooling Shocks: Covid-Induced Online Learning Engagement in Real Time," CESifo Working Paper Series, CESifo, number 8454.