Report NEP-BIG-2023-09-04

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.

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Other reports in NEP-BIG

The following items were announced in this report:

• Jens Foerderer, 2023. "Should we trust web-scraped data?," Papers 2308.02231, arXiv.org.
• Oleksandr Romanko & Akhilesh Narayan & Roy H. Kwon, 2023. "ChatGPT-based Investment Portfolio Selection," Papers 2308.06260, arXiv.org.
• Denis Koshelev & Alexey Ponomarenko & Sergei Seleznev, 2023. "Amortized neural networks for agent-based model forecasting," Papers 2308.05753, arXiv.org.
• Nouhaila Innan & Muhammad Al-Zafar Khan & Mohamed Bennai, 2023. "Financial Fraud Detection: A Comparative Study of Quantum Machine Learning Models," Papers 2308.05237, arXiv.org.
• Khezr, Peyman & Pourkhanali, Armin, 2023. "An investigation of auctions in the Regional Greenhouse Gas Initiative," MPRA Paper 118120, University Library of Munich, Germany.
• Matteo Prata & Giuseppe Masi & Leonardo Berti & Viviana Arrigoni & Andrea Coletta & Irene Cannistraci & Svitlana Vyetrenko & Paola Velardi & Novella Bartolini, 2023. "LOB-Based Deep Learning Models for Stock Price Trend Prediction: A Benchmark Study," Papers 2308.01915, arXiv.org, revised Sep 2023.
• Liu, Yirui & Qiao, Xinghao & Wang, Liying & Lam, Jessica, 2023. "EEGNN: edge enhanced graph neural network with a Bayesian nonparametric graph model," LSE Research Online Documents on Economics 119918, London School of Economics and Political Science, LSE Library.
• Camilo R. Contreras & Pierre Valette-Florence, 2021. "Brands And Chatbots: An Overview Using Machine Learning," Post-Print hal-04153038, HAL.
• Jonas Hanetho, 2023. "Deep Policy Gradient Methods in Commodity Markets," Papers 2308.01910, arXiv.org.
• Magnus Wiese & Phillip Murray & Ralf Korn, 2023. "Sig-Splines: universal approximation and convex calibration of time series generative models," Papers 2307.09767, arXiv.org.
• Jsowd, Kyldo, 2023. "Evaluating Chatbot Performance: A Meta-Analysis Approach with Deep Learning," OSF Preprints 593tq, Center for Open Science.
• Cordier, J.; & Salvi, I.; & Steinbeck, V.; & Geissler, A.; & Vogel, J.;, 2023. "Is rapid recovery always the best recovery? - Developing a machine learning approach for optimal assignment rules under capacity constraints for knee replacement patients," Health, Econometrics and Data Group (HEDG) Working Papers 23/08, HEDG, c/o Department of Economics, University of York.
• Eduardo C. Garrido-Merch'an & Sol Mora-Figueroa-Cruz-Guzm'an & Mar'ia Coronado-Vaca, 2023. "Deep Reinforcement Learning for ESG financial portfolio management," Papers 2307.09631, arXiv.org.
• Teona Shugliashvili, 2023. "The words have power: the impact of news on exchange rates," FFA Working Papers 5.006, Prague University of Economics and Business, revised 31 Jul 2023.
• Lillo, Fabrizio & Livieri, Giulia & Marmi, Stefano & Solomko, Anton & Vaienti, Sandro, 2023. "Analysis of bank leverage via dynamical systems and deep neural networks," LSE Research Online Documents on Economics 119917, London School of Economics and Political Science, LSE Library.
• Fengler, Matthias & Phan, Minh Tri, 2023. "A Topic Model for 10-K Management Disclosures," Economics Working Paper Series 2307, University of St. Gallen, School of Economics and Political Science.
• Yuwei Yin & Yazheng Yang & Jian Yang & Qi Liu, 2023. "FinPT: Financial Risk Prediction with Profile Tuning on Pretrained Foundation Models," Papers 2308.00065, arXiv.org.
• Seidel, Claudia & Shang, Linmei & Britz, Wolfgang, 2023. "A critical assessment of neural networks as meta-model of a farm optimization model," Discussion Papers 338200, University of Bonn, Institute for Food and Resource Economics.
• Supawich Puengdang & Worawate Ausawalaithong & Phiratath Nopratanawong & Narongdech Keeratipranon & Chayut Wongkamthong, 2023. "Thailand Asset Value Estimation Using Aerial or Satellite Imagery," Papers 2307.08650, arXiv.org, revised Aug 2023.