Report NEP-CMP-2023-08-28

This is the archive for NEP-CMP, a report on new working papers in the area of Computational Economics. Stan Miles issued this report. It is usually issued weekly.

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Other reports in NEP-CMP

The following items were announced in this report:

• Tessa Bauman & Bruno Gav{s}perov & Stjepan Beguv{s}i'c & Zvonko Kostanjv{c}ar, 2023. "Deep Reinforcement Learning for Robust Goal-Based Wealth Management," Papers 2307.13501, arXiv.org.
• V'elez Jim'enez & Rom'an Alberto & Lecuanda Ontiveros & Jos'e Manuel & Edgar Possani, 2023. "Sports Betting: an application of neural networks and modern portfolio theory to the English Premier League," Papers 2307.13807, arXiv.org.
• Park, Youngjun & Han, Sumin, 2023. "Encoding Urban Trajectory As A Language: Deep Learning Insights For Human Mobility Pattern," OSF Preprints guf3z, Center for Open Science.
• Chinn, Menzie D. & Meunier, Baptiste & Stumpner, Sebastian, 2023. "Nowcasting world trade with machine learning: a three-step approach," Working Paper Series 2836, European Central Bank.
• Bryan T. Kelly & Dacheng Xiu, 2023. "Financial Machine Learning," NBER Working Papers 31502, National Bureau of Economic Research, Inc.
• Josef Teichmann & Hanna Wutte, 2023. "Machine Learning-powered Pricing of the Multidimensional Passport Option," Papers 2307.14887, arXiv.org.
• Paolo Andreini & Cosimo Izzo & Giovanni Ricco, 2023. "Deep Dynamic Factor Models," Working Papers 2023-08, Center for Research in Economics and Statistics.
• Ivan Letteri, 2023. "VolTS: A Volatility-based Trading System to forecast Stock Markets Trend using Statistics and Machine Learning," Papers 2307.13422, arXiv.org, revised Aug 2023.
• Zhiyu Cao & Zihan Chen & Prerna Mishra & Hamed Amini & Zachary Feinstein, 2023. "Modeling Inverse Demand Function with Explainable Dual Neural Networks," Papers 2307.14322, arXiv.org, revised Oct 2023.
• Masanori Hirano & Kentaro Minami & Kentaro Imajo, 2023. "Adversarial Deep Hedging: Learning to Hedge without Price Process Modeling," Papers 2307.13217, arXiv.org.
• Chuheng Zhang & Yitong Duan & Xiaoyu Chen & Jianyu Chen & Jian Li & Li Zhao, 2023. "Towards Generalizable Reinforcement Learning for Trade Execution," Papers 2307.11685, arXiv.org.
• Soohan Kim & Jimyeong Kim & Hong Kee Sul & Youngjoon Hong, 2023. "An Adaptive Dual-level Reinforcement Learning Approach for Optimal Trade Execution," Papers 2307.10649, arXiv.org.
• Ambrois, Matteo & Butticè, Vincenzo & Caviggioli, Federico & Cerulli, Giovanni & Croce, Annalisa & De Marco, Antonio & Giordano, Andrea & Resce, Giuliano & Toschi, Laura & Ughetto, Elisa & Zinilli, An, 2023. "Using machine learning to map the European cleantech sector," EIF Working Paper Series 2023/91, European Investment Fund (EIF).
• NAKAMURA Ryohei & NAGAMUNE Takeshi & HAYASHI Syuusei, 2023. "Aggregation of Information and Communications Industry and Self-organization Simulation Using an Agent-based Model (Japanese)," Discussion Papers (Japanese) 23027, Research Institute of Economy, Trade and Industry (RIETI).
• Francesco Mandelli & Marco Pinciroli & Michele Trapletti & Edoardo Vittori, 2023. "Reinforcement Learning for Credit Index Option Hedging," Papers 2307.09844, arXiv.org.
• Damian Ślusarczyk & Robert Ślepaczuk, 2023. "Optimal Markowitz Portfolio Using Returns Forecasted with Time Series and Machine Learning Models," Working Papers 2023-17, Faculty of Economic Sciences, University of Warsaw.
• Yuanhao Gong, 2023. "Dynamic Large Language Models on Blockchains," Papers 2307.10549, arXiv.org.
• Xiao-Yang Liu & Guoxuan Wang & Hongyang Yang & Daochen Zha, 2023. "FinGPT: Democratizing Internet-scale Data for Financial Large Language Models," Papers 2307.10485, arXiv.org, revised Nov 2023.
• Koefer, Franziska & Lemken, Ivo & Pauls, Jan, 2023. "Fairness in algorithmic decision systems: A microfinance perspective," EIF Working Paper Series 2023/88, European Investment Fund (EIF).
• Valerio Capraro & Roberto Di Paolo & Veronica Pizziol, 2023. "Assessing Large Language Models' ability to predict how humans balance self-interest and the interest of others," Papers 2307.12776, arXiv.org, revised Feb 2024.
• Steve Phelps & Rebecca Ranson, 2023. "Of Models and Tin Men: A Behavioural Economics Study of Principal-Agent Problems in AI Alignment using Large-Language Models," Papers 2307.11137, arXiv.org, revised Sep 2023.
• Rodier, Caroline PhD & Horn, Abigail PhD & Zhang, Yunwan MSc & Kaddoura, Ihab PhD & Müller, Sebastian MSc, 2023. "Effectiveness of Nonpharmaceutical Interventions to Avert the Second COVID-19 Surge in Los Angeles County: A Simulation Study," Institute of Transportation Studies, Working Paper Series qt5f78h654, Institute of Transportation Studies, UC Davis.