Report NEP-BIG-2023-06-26
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.Subscribe to this report: email, RSS, or Mastodon, or Bluesky.
Other reports in NEP-BIG
The following items were announced in this report:
- Bennett Schmanski & Chiara Scotti & Clara Vega, 2023. "Fed Communication, News, Twitter, and Echo Chambers," Finance and Economics Discussion Series 2023-036, Board of Governors of the Federal Reserve System (U.S.).
- Andrea Ajello & Diego Silva & Travis Adams & Francisco Vazquez-Grande, 2023. "More than Words: Twitter Chatter and Financial Market Sentiment," Finance and Economics Discussion Series 2023-034, Board of Governors of the Federal Reserve System (U.S.).
- Sinan Deng & John Inekwe & Vladimir Smirnov & Andrew Wait & Chao Wang, 2023. "Machine Learning and Deep Learning Forecasts of Electricity Imbalance Prices," Working Papers 2023-03, University of Sydney, School of Economics.
- Benjamin Fan & Edward Qiao & Anran Jiao & Zhouzhou Gu & Wenhao Li & Lu Lu, 2023. "Deep Learning for Solving and Estimating Dynamic Macro-Finance Models," Papers 2305.09783, arXiv.org.
- Jingjing Guo, 2023. "Gated Deeper Models are Effective Factor Learners," Papers 2305.10693, arXiv.org.
- Michael Allan Ribers & Hannes Ullrich, 2023. "Machine learning and physician prescribing: a path to reduced antibiotic use," Berlin School of Economics Discussion Papers 0019, Berlin School of Economics.
- Khuc, Quy Van & Tran, Duc-Trung, 2023. "Contingent valuation machine learning (CVML): A novel method for estimating citizens’ willingness- to- pay for safer and cleaner environment," OSF Preprints r35bz, Center for Open Science.
- Mollen, Anne & Hondrich, Lukas, 2023. "From risk mitigation to employee action along the machine learning pipeline: A paradigm shift in European regulatory perspectives on automated decision-making systems in the workplace," Working Paper Forschungsförderung 278, Hans-Böckler-Stiftung, Düsseldorf.
- Pletcher, Scott Nicholas, 2023. "Practical and Ethical Perspectives on AI-Based Employee Performance Evaluation," OSF Preprints 29yej, Center for Open Science.
- Maximilian Ahrens & Deniz Erdemlioglu & Michael McMahon & Christopher J. Neely & Xiye Yang, 2023. "Mind Your Language: Market Responses to Central Bank Speeches," Working Papers 2023-013, Federal Reserve Bank of St. Louis, revised 28 Sep 2024.
- Ludovic Gouden`ege & Andrea Molent & Antonino Zanette, 2023. "Backward Hedging for American Options with Transaction Costs," Papers 2305.06805, arXiv.org, revised Jun 2023.
- Carpenter, Jeffrey P. & Lyford, Alex & Zhang, Mingfang, 2023. "A Behaviorally-Validated Warm Glow Questionnaire," IZA Discussion Papers 16205, Institute of Labor Economics (IZA).
- Petar Soric & Enric Monte & Salvador Torra & Oscar Claveria, 2022. "“Density forecasts of inflation using Gaussian process regression models”," AQR Working Papers 202207, University of Barcelona, Regional Quantitative Analysis Group, revised Jul 2022.
- Lavko, Matus & Klein, Tony & Walther, Thomas, 2023. "Reinforcement Learning and Portfolio Allocation: Challenging Traditional Allocation Methods," QBS Working Paper Series 2023/01, Queen's University Belfast, Queen's Business School.
- Marcin Chlebus & Artur Nowak, 2023. "From Alchemy to Analytics: Unleashing the Potential of Technical Analysis in Predicting Noble Metal Price Movement," Working Papers 2023-13, Faculty of Economic Sciences, University of Warsaw.
- Anbar Aizenman & Connor M. Brennan & Tomaz Cajner & Cynthia L. Doniger & Jacob Williams, 2023. "Measuring Job Loss during the Pandemic Recession in Real Time with Twitter Data," Finance and Economics Discussion Series 2023-035, Board of Governors of the Federal Reserve System (U.S.).
- Kai Gehring & Matteo Grigoletto, 2023. "Analyzing Climate Change Policy Narratives with the Character-Role Narrative Framework," CESifo Working Paper Series 10429, CESifo.
- Occhini, Giulia & Tranos, Emmanouil & Wolf, Levi John, 2023. "Occupational segregation in the digital economy? A Natural Language Processing approach using UK Web Data," SocArXiv z8xta, Center for Open Science.
- Masanori Hirano & Kentaro Imajo & Kentaro Minami & Takuya Shimada, 2023. "Efficient Learning of Nested Deep Hedging using Multiple Options," Papers 2305.12264, arXiv.org.
- Moritz Grebe & Sinem Kandemir & Peter Tillmann, 2023. "Uncertainty about the War in Ukraine: Measurement and Effects on the German Business Cycle," MAGKS Papers on Economics 202314, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
- Hasan, Sacha & Yuan, Yingfang, 2023. "Minority Ethnic Vulnerabilities in the Use of Digital Housing Services Across Age Groups," SocArXiv jtc8k, Center for Open Science.