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Report NEP-BIG-2023-08-28
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:
- Andreas Kammerlander, 2022, "Economic Growth and Pollution in different Political Regimes," Discussion Paper Series, Department of International Economic Policy, University of Freiburg, number 43, Oct, revised Oct 2022.
- Tom Liu & Stefan Zohren, 2023, "Multi-Factor Inception: What to Do with All of These Features?," Papers, arXiv.org, number 2307.13832, Jul.
- Catherine E. A. Mulligan & Phil Godsiff, 2023, "Datalism and Data Monopolies in the Era of A.I.: A Research Agenda," Papers, arXiv.org, number 2307.08049, Jul.
- Valerio Capraro & Roberto Di Paolo & Veronica Pizziol, 2023, "Assessing Large Language Models' ability to predict how humans balance self-interest and the interest of others," Papers, arXiv.org, number 2307.12776, Jul, revised Feb 2024.
- Masanori Hirano & Kentaro Minami & Kentaro Imajo, 2023, "Adversarial Deep Hedging: Learning to Hedge without Price Process Modeling," Papers, arXiv.org, number 2307.13217, Jul.
- Ambrois, Matteo & Butticè, Vincenzo & Caviggioli, Federico & Cerulli, Giovanni & Croce, Annalisa & De Marco, Antonio & Giordano, Andrea & Resce, Giuliano & Toschi, Laura & Ughetto, Elisa & Zinilli, An, 2023, "Using machine learning to map the European cleantech sector," EIF Working Paper Series, European Investment Fund (EIF), number 2023/91.
- Zhiyu Cao & Zihan Chen & Prerna Mishra & Hamed Amini & Zachary Feinstein, 2023, "Modeling Inverse Demand Function with Explainable Dual Neural Networks," Papers, arXiv.org, number 2307.14322, Jul, revised Oct 2023.
- Christopher Gerling & Stefan Lessmann, 2023, "Multimodal Document Analytics for Banking Process Automation," Papers, arXiv.org, number 2307.11845, Jul, revised Nov 2023.
- Maxime L. D. Nicolas & Adrien Desroziers & Fabio Caccioli & Tomaso Aste, 2023, "ESG Reputation Risk Matters: An Event Study Based on Social Media Data," Papers, arXiv.org, number 2307.11571, Jul.
- Paolo Andreini & Cosimo Izzo & Giovanni Ricco, 2023, "Deep Dynamic Factor Models," Working Papers, Center for Research in Economics and Statistics, number 2023-08, May.
- Mathias Valla & Xavier Milhaud & Anani Ayodélé Olympio, 2023, "Including individual Customer Lifetime Value and competing risks in tree-based lapse management strategies," Post-Print, HAL, number hal-03903047, Sep, DOI: 10.1007/s13385-023-00358-0.
- V'elez Jim'enez & Rom'an Alberto & Lecuanda Ontiveros & Jos'e Manuel & Edgar Possani, 2023, "Sports Betting: an application of neural networks and modern portfolio theory to the English Premier League," Papers, arXiv.org, number 2307.13807, Jul.
- Piasenti, Stefano & Valente, Marica & van Veldhuizen, Roel & Pfeifer, Gregor, 2023, "Does Unfairness Hurt Women? The Effects of Losing Unfair Competitions," IZA Discussion Papers, IZA Network @ LISER, number 16324, Jul.
- Yuanhao Gong, 2023, "Dynamic Large Language Models on Blockchains," Papers, arXiv.org, number 2307.10549, Jul.
- Bryan T. Kelly & Dacheng Xiu, 2023, "Financial Machine Learning," NBER Working Papers, National Bureau of Economic Research, Inc, number 31502, Jul.
- Anna Kerkhof & Valentin Reich, 2023, "Gender Stereotypes in User-Generated Content," CESifo Working Paper Series, CESifo, number 10578.
- Damian Ślusarczyk & Robert Ślepaczuk, 2023, "Optimal Markowitz Portfolio Using Returns Forecasted with Time Series and Machine Learning Models," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2023-17.
- Bresson, Georges & Etienne, Jean-Michel & Lacroix, Guy, 2023, "Nighttime Light Pollution and Economic Activities: A Spatio-Temporal Model with Common Factors for US Counties," IZA Discussion Papers, IZA Network @ LISER, number 16342, Jul.
- Chinn, Menzie D. & Meunier, Baptiste & Stumpner, Sebastian, 2023, "Nowcasting world trade with machine learning: a three-step approach," Working Paper Series, European Central Bank, number 2836, Aug.
- Varun Sangwan & Vishesh Kumar Singh & Bibin Christopher V, 2023, "Contrasting the efficiency of stock price prediction models using various types of LSTM models aided with sentiment analysis," Papers, arXiv.org, number 2307.07868, Jul.
- Xiao-Yang Liu & Guoxuan Wang & Hongyang Yang & Daochen Zha, 2023, "FinGPT: Democratizing Internet-scale Data for Financial Large Language Models," Papers, arXiv.org, number 2307.10485, Jul, revised Nov 2023.
- Tessa Bauman & Bruno Gav{s}perov & Stjepan Beguv{s}i'c & Zvonko Kostanjv{c}ar, 2023, "Deep Reinforcement Learning for Robust Goal-Based Wealth Management," Papers, arXiv.org, number 2307.13501, Jul.
- Josef Teichmann & Hanna Wutte, 2023, "Machine Learning-powered Pricing of the Multidimensional Passport Option," Papers, arXiv.org, number 2307.14887, Jul.
- Park, Youngjun & Han, Sumin, 2023, "Encoding Urban Trajectory As A Language: Deep Learning Insights For Human Mobility Pattern," OSF Preprints, Center for Open Science, number guf3z, Jun, DOI: 10.31219/osf.io/guf3z.
- Ivan Letteri, 2023, "VolTS: A Volatility-based Trading System to forecast Stock Markets Trend using Statistics and Machine Learning," Papers, arXiv.org, number 2307.13422, Jul, revised Aug 2023.