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Report NEP-CMP-2023-09-25
This is the archive for NEP-CMP, a report on new working papers in the area of Computational Economics. Stanley Miles issued this report. It is usually issued weekly.Subscribe to this report: email, RSS, or Mastodon, or Bluesky.
Other reports in NEP-CMP
The following items were announced in this report:
- Kristoffer Andersson & Cornelis W. Oosterlee, 2023, "D-TIPO: Deep time-inconsistent portfolio optimization with stocks and options," Papers, arXiv.org, number 2308.10556, Aug, revised Sep 2023.
- Kian Tehranian, 2023, "Can Machine Learning Catch Economic Recessions Using Economic and Market Sentiments?," Papers, arXiv.org, number 2308.16200, Aug.
- Joao Felix & Michel Alexandre & Gilberto Tadeu Lima, 2023, "Applying Machine Learning Algorithms to Predict the Size of the Informal Economy," Working Papers, Department of Economics, University of São Paulo (FEA-USP), number 2023_10, Aug, revised 11 Sep 2023.
- Xingyue Pu & Stefan Zohren & Stephen Roberts & Xiaowen Dong, 2023, "Learning to Learn Financial Networks for Optimising Momentum Strategies," Papers, arXiv.org, number 2308.12212, Aug.
- Hansen, Sakina & Loftus, Joshua, 2023, "Model-agnostic auditing: a lost cause?," LSE Research Online Documents on Economics, London School of Economics and Political Science, LSE Library, number 120114, Jul.
- Gilberto Boaretto & Marcelo C. Medeiros, 2023, "Forecasting inflation using disaggregates and machine learning," Papers, arXiv.org, number 2308.11173, Aug.
- Sascha Frey & Kang Li & Peer Nagy & Silvia Sapora & Chris Lu & Stefan Zohren & Jakob Foerster & Anisoara Calinescu, 2023, "JAX-LOB: A GPU-Accelerated limit order book simulator to unlock large scale reinforcement learning for trading," Papers, arXiv.org, number 2308.13289, Aug.
- Naman S & Gaurang B & Neel S & Aswath Babu H, 2023, "The Potential of Quantum Techniques for Stock Price Prediction," Papers, arXiv.org, number 2308.13642, Aug.
- Xu Han & Zengqing Wu & Chuan Xiao, 2023, ""Guinea Pig Trials" Utilizing GPT: A Novel Smart Agent-Based Modeling Approach for Studying Firm Competition and Collusion," Papers, arXiv.org, number 2308.10974, Aug, revised Jan 2024.
- Tyrel Stokes & Ian Shrier & Russell Steele, 2023, "Simulation Experiments as a Causal Problem," Papers, arXiv.org, number 2308.10823, Aug.
- A. Ege Yilmaz & Stefan Stettler & Thomas Ankenbrand & Urs Rhyner, 2023, "Grover Search for Portfolio Selection," Papers, arXiv.org, number 2308.13063, Aug.
- Md Sabbirul Haque & Md Shahedul Amin & Jonayet Miah, 2023, "Retail Demand Forecasting: A Comparative Study for Multivariate Time Series," Papers, arXiv.org, number 2308.11939, Aug.
- Reinking, Ernst & Becker, Marco, 2023, "Opportunities for business use of today's AI models - Rapidly achievable personalization of Large Language Models (like ChatGPT) in times of Industry 5.0," EconStor Preprints, ZBW - Leibniz Information Centre for Economics, number 275738.
- Rick Steinert & Saskia Altmann, 2023, "Linking microblogging sentiments to stock price movement: An application of GPT-4," Papers, arXiv.org, number 2308.16771, Aug.
- Andres Alonso-Robisco & Jose Manuel Carbo, 2023, "Analysis of CBDC Narrative OF Central Banks using Large Language Models," Working Papers, Banco de España, number 2321, Aug, DOI: https://doi.org/10.53479/33412.
- Andrés Azqueta-Gavaldón & Marina Diakonova & Corinna Ghirelli & Javier J. Pérez, 2023, "Sources of economic policy uncertainty in the euro area: a ready-to-use database," Occasional Papers, Banco de España, number 2315, Jul, DOI: https://doi.org/10.53479/33155.
- Melissa Dell & Jacob Carlson & Tom Bryan & Emily Silcock & Abhishek Arora & Zejiang Shen & Luca D'Amico-Wong & Quan Le & Pablo Querubin & Leander Heldring, 2023, "American Stories: A Large-Scale Structured Text Dataset of Historical U.S. Newspapers," Papers, arXiv.org, number 2308.12477, Aug.
- S. Srinivas & R. Gadela & R. Sabu & A. Das & G. Nath & V. Datla, 2023, "Effects of Daily News Sentiment on Stock Price Forecasting," Papers, arXiv.org, number 2308.08549, Aug.