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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 (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:
- Bennett Schmanski & Chiara Scotti & Clara Vega, 2023, "Fed Communication, News, Twitter, and Echo Chambers," Finance and Economics Discussion Series, Board of Governors of the Federal Reserve System (U.S.), number 2023-036, May, DOI: 10.17016/FEDS.2023.036.
- Andrea Ajello & Diego Silva & Travis Adams & Francisco Vazquez-Grande, 2023, "More than Words: Twitter Chatter and Financial Market Sentiment," Finance and Economics Discussion Series, Board of Governors of the Federal Reserve System (U.S.), number 2023-034, May, DOI: 10.17016/FEDS.2023.034.
- Sinan Deng & John Inekwe & Vladimir Smirnov & Andrew Wait & Chao Wang, 2023, "Machine Learning and Deep Learning Forecasts of Electricity Imbalance Prices," Working Papers, University of Sydney, School of Economics, number 2023-03, Jun.
- Benjamin Fan & Edward Qiao & Anran Jiao & Zhouzhou Gu & Wenhao Li & Lu Lu, 2023, "Deep Learning for Solving and Estimating Dynamic Macro-Finance Models," Papers, arXiv.org, number 2305.09783, May.
- Jingjing Guo, 2023, "Gated Deeper Models are Effective Factor Learners," Papers, arXiv.org, number 2305.10693, May.
- Michael Allan Ribers & Hannes Ullrich, 2023, "Machine learning and physician prescribing: a path to reduced antibiotic use," Berlin School of Economics Discussion Papers, Berlin School of Economics, number 0019, Jun, DOI: 10.48462/opus4-4976.
- 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, Center for Open Science, number r35bz, May, DOI: 10.31219/osf.io/r35bz.
- 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, Hans-Böckler-Stiftung, Düsseldorf, number 278.
- Pletcher, Scott Nicholas, 2023, "Practical and Ethical Perspectives on AI-Based Employee Performance Evaluation," OSF Preprints, Center for Open Science, number 29yej, Apr, DOI: 10.31219/osf.io/29yej.
- Maximilian Ahrens & Deniz Erdemlioglu & Michael McMahon & Christopher J. Neely & Xiye Yang, 2023, "Mind Your Language: Market Responses to Central Bank Speeches," Working Papers, Federal Reserve Bank of St. Louis, number 2023-013, May, revised 28 Sep 2024, DOI: 10.20955/wp.2023.013.
- Ludovic Gouden`ege & Andrea Molent & Antonino Zanette, 2023, "Backward Hedging for American Options with Transaction Costs," Papers, arXiv.org, number 2305.06805, May, revised Jun 2023.
- Carpenter, Jeffrey P. & Lyford, Alex & Zhang, Mingfang, 2023, "A Behaviorally-Validated Warm Glow Questionnaire," IZA Discussion Papers, IZA Network @ LISER, number 16205, Jun.
- Petar Soric & Enric Monte & Salvador Torra & Oscar Claveria, 2022, "“Density forecasts of inflation using Gaussian process regression models”," AQR Working Papers, University of Barcelona, Regional Quantitative Analysis Group, number 202207, Jul, revised Jul 2022.
- Lavko, Matus & Klein, Tony & Walther, Thomas, 2023, "Reinforcement Learning and Portfolio Allocation: Challenging Traditional Allocation Methods," QBS Working Paper Series, Queen's University Belfast, Queen's Business School, number 2023/01, DOI: 10.2139/ssrn.4346043.
- Marcin Chlebus & Artur Nowak, 2023, "From Alchemy to Analytics: Unleashing the Potential of Technical Analysis in Predicting Noble Metal Price Movement," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2023-13.
- 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, Board of Governors of the Federal Reserve System (U.S.), number 2023-035, May, DOI: 10.17016/FEDS.2023.035.
- Kai Gehring & Matteo Grigoletto, 2023, "Analyzing Climate Change Policy Narratives with the Character-Role Narrative Framework," CESifo Working Paper Series, CESifo, number 10429.
- Occhini, Giulia & Tranos, Emmanouil & Wolf, Levi John, 2023, "Occupational segregation in the digital economy? A Natural Language Processing approach using UK Web Data," SocArXiv, Center for Open Science, number z8xta, May, DOI: 10.31219/osf.io/z8xta.
- Masanori Hirano & Kentaro Imajo & Kentaro Minami & Takuya Shimada, 2023, "Efficient Learning of Nested Deep Hedging using Multiple Options," Papers, arXiv.org, number 2305.12264, May.
- 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, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung), number 202314.
- Hasan, Sacha & Yuan, Yingfang, 2023, "Minority Ethnic Vulnerabilities in the Use of Digital Housing Services Across Age Groups," SocArXiv, Center for Open Science, number jtc8k, Jun, DOI: 10.31219/osf.io/jtc8k.