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Report NEP-CMP-2024-11-18
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:
- Jesús Fernández-Villaverde & Galo Nuno & Jesse Perla, 2024, "Taming the Curse of Dimensionality:Quantitative Economics with Deep Learning," PIER Working Paper Archive, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, number 24-034, Oct.
- Pulikandala Nithish Kumar & Nneka Umeorah & Alex Alochukwu, 2024, "Dynamic graph neural networks for enhanced volatility prediction in financial markets," Papers, arXiv.org, number 2410.16858, Oct.
- Daniel Albert & Stephan Billinger, 2024, "Reproducing and Extending Experiments in Behavioral Strategy with Large Language Models," Papers, arXiv.org, number 2410.06932, Oct.
- Sohyeon Kwon & Yongjae Lee, 2024, "Can GANs Learn the Stylized Facts of Financial Time Series?," Papers, arXiv.org, number 2410.09850, Oct.
- Queenie Sun & Nicholas Grablevsky & Huaizhang Deng & Pooya Azadi, 2024, "Quantum Computing for Multi Period Asset Allocation," Papers, arXiv.org, number 2410.11997, Oct.
- Sinha, Pankaj & Kumar, Amit & Biswas, Sumana & Gupta, Chirag, 2024, "Forecasting US Presidential Election 2024 using multiple machine learning algorithms," MPRA Paper, University Library of Munich, Germany, number 122490, Oct, revised 22 Oct 2024.
- Aivin V. Solatorio & Gabriel Stefanini Vicente & Holly Krambeck & Olivier Dupriez, 2024, "Double Jeopardy and Climate Impact in the Use of Large Language Models: Socio-economic Disparities and Reduced Utility for Non-English Speakers," Papers, arXiv.org, number 2410.10665, Oct.
- Ahmad Makinde, 2024, "Optimizing Time Series Forecasting: A Comparative Study of Adam and Nesterov Accelerated Gradient on LSTM and GRU networks Using Stock Market data," Papers, arXiv.org, number 2410.01843, Sep.
- Rodolfo Monfilier Peres & Onofre Alves Simões, 2024, "Hospital Admission Rates in São Paulo, Brazil - Lee-Carter model vs. neural networks," Working Papers REM, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa, number 2024/0349, Oct.
- Yuzhe Yang & Yifei Zhang & Yan Hu & Yilin Guo & Ruoli Gan & Yueru He & Mingcong Lei & Xiao Zhang & Haining Wang & Qianqian Xie & Jimin Huang & Honghai Yu & Benyou Wang, 2024, "UCFE: A User-Centric Financial Expertise Benchmark for Large Language Models," Papers, arXiv.org, number 2410.14059, Oct, revised Feb 2025.
- Mehdi Hosseini Chagahi & Niloufar Delfan & Saeed Mohammadi Dashtaki & Behzad Moshiri & Md. Jalil Piran, 2024, "Explainable AI for Fraud Detection: An Attention-Based Ensemble of CNNs, GNNs, and A Confidence-Driven Gating Mechanism," Papers, arXiv.org, number 2410.09069, Oct, revised Feb 2025.
- Julius Range & Benedikt Gloria & Albert Erasmus Grafe, 2024, "Living on the Highway: Addressing Germany's HGV Parking Crisis through Machine Learning Satellite Image Analysis," ERES, European Real Estate Society (ERES), number eres2024-164, Jan.
- Ashley Davey & Harry Zheng, 2024, "Deep Learning Methods for S Shaped Utility Maximisation with a Random Reference Point," Papers, arXiv.org, number 2410.05524, Oct.
- Luca Lalor & Anatoliy Swishchuk, 2024, "Reinforcement Learning in Non-Markov Market-Making," Papers, arXiv.org, number 2410.14504, Oct, revised Nov 2024.
- Francesco Audrino & Jessica Gentner & Simon Stalder, 2024, "Quantifying uncertainty: a new era of measurement through large language models," Working Papers, Swiss National Bank, number 2024-12.
- Chad Brown, 2024, "Statistical Properties of Deep Neural Networks with Dependent Data," Papers, arXiv.org, number 2410.11113, Oct, revised Jan 2025.
- Namid R. Stillman & Rory Baggott, 2024, "Neuro-Symbolic Traders: Assessing the Wisdom of AI Crowds in Markets," Papers, arXiv.org, number 2410.14587, Oct.
- M. Hashem Pesaran & Hayun Song, 2024, "Forecasting 2024 US Presidential Election by States Using County Level Data: Too Close to Call," CESifo Working Paper Series, CESifo, number 11415.
- Herbert Dawid & Domenico Delli Gatti & Luca Eduardo Fierro & Sebastian Poledna, 2024, "Implications of Behavioral Rules in Agent-Based Macroeconomics," CESifo Working Paper Series, CESifo, number 11411.