Printed from https://ideas.repec.org/n/nep-big/2019-01-14.html
Report NEP-BIG-2019-01-14
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:
- Beutel, Johannes & List, Sophia & von Schweinitz, Gregor, 2018, "An evaluation of early warning models for systemic banking crises: Does machine learning improve predictions?," Discussion Papers, Deutsche Bundesbank, number 48/2018.
- Kim, Moon-Koo & Park, Jong-Hyun & Lee, Duk Hee, 2018, "Antecedents and consequences of individuals' trust formation in artificial intelligence in Korea," 22nd ITS Biennial Conference, Seoul 2018. Beyond the boundaries: Challenges for business, policy and society, International Telecommunications Society (ITS), number 190390.
- Gregory, Terry & Salomons, Anna & Zierahn-Weilage, Ulrich, 2019, "Racing With or Against the Machine? Evidence from Europe," IZA Discussion Papers, IZA Network @ LISER, number 12063, Jan.
- Lechner, Michael, 2019, "Modified Causal Forests for Estimating Heterogeneous Causal Effects," Economics Working Paper Series, University of St. Gallen, School of Economics and Political Science, number 1901, Jan.
- Reaz Chowdhury & M. R. C. Mahdy & Tanisha Nourin Alam & Golam Dastegir Al Quaderi, 2018, "Predicting the Stock Price of Frontier Markets Using Modified Black-Scholes Option Pricing Model and Machine Learning," Papers, arXiv.org, number 1812.10619, Dec.
- Item repec:hal:wpaper:hal-01949221 is not listed on IDEAS anymore
- Mubashir Qasim, 2019, "Sustainability and Wellbeing: A Text Analysis of New Zealand Parliamentary Debates, Official Yearbooks and Ministerial Documents," Working Papers in Economics, University of Waikato, number 19/01, Jan.
- Dominik Gutt, 2018, "In the Eye of the Beholder? Empirically Decomposing Different Economic Implications of the Online Rating Variance," Working Papers Dissertations, Paderborn University, Faculty of Business Administration and Economics, number 40, Dec.
- Abu Taher, Sheikh & Uddin, Md. Kama, 2018, "Use of big data in financial sector of Bangladesh – A review," 22nd ITS Biennial Conference, Seoul 2018. Beyond the boundaries: Challenges for business, policy and society, International Telecommunications Society (ITS), number 190348.
- Miyazaki, Kumiko & Sato & Ryusuke, 2018, "Adoption of AI in Firms and the Issues to be Overcome - An Empirical Analyses of the Evolutionary Path of Development by Firms," 22nd ITS Biennial Conference, Seoul 2018. Beyond the boundaries: Challenges for business, policy and society, International Telecommunications Society (ITS), number 190377.
- Elias Cavalcante-Filho & Flavio Abdenur, Rodrigo De Losso, 2018, "Machine learning applied to accounting variables yields the risk-return metrics of private company portfolios," Working Papers, Department of Economics, University of São Paulo (FEA-USP), number 2018_23, Dec.
- Marcelo Sardelich & Suresh Manandhar, 2018, "Multimodal deep learning for short-term stock volatility prediction," Papers, arXiv.org, number 1812.10479, Dec.
- William Irungu Nganga & Julien Chevallier & Simon Wagura Ndiritu, 2018, "Regime changes and fiscal sustainability in Kenya with comparative nonlinear Granger causalities across East-African countries," Working Papers, HAL, number halshs-01941226, Nov.
- Lael Brainard, 2018, "What Are We Learning about Artificial Intelligence in Financial Services?: a speech at Fintech and the New Financial Landscape, Philadelphia, Pennsylvania," Speech, Board of Governors of the Federal Reserve System (U.S.), number 1021, Nov.
- Neng-Chieh Chang, 2018, "Semiparametric Difference-in-Differences with Potentially Many Control Variables," Papers, arXiv.org, number 1812.10846, Dec, revised Jan 2019.
- Adriano Koshiyama & Nick Firoozye & Philip Treleaven, 2019, "Generative Adversarial Networks for Financial Trading Strategies Fine-Tuning and Combination," Papers, arXiv.org, number 1901.01751, Jan, revised Mar 2019.
- Victor Chernozhukov & Kaspar Wuthrich & Yinchu Zhu, 2018, "Debiasing and $t$-tests for synthetic control inference on average causal effects," Papers, arXiv.org, number 1812.10820, Dec, revised May 2025.