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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. 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:
- 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, arXiv.org, number 2307.13501, Jul.
- 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, arXiv.org, number 2307.13807, Jul.
- Park, Youngjun & Han, Sumin, 2023, "Encoding Urban Trajectory As A Language: Deep Learning Insights For Human Mobility Pattern," OSF Preprints, Center for Open Science, number guf3z, Jun, DOI: 10.31219/osf.io/guf3z.
- Chinn, Menzie D. & Meunier, Baptiste & Stumpner, Sebastian, 2023, "Nowcasting world trade with machine learning: a three-step approach," Working Paper Series, European Central Bank, number 2836, Aug.
- Bryan T. Kelly & Dacheng Xiu, 2023, "Financial Machine Learning," NBER Working Papers, National Bureau of Economic Research, Inc, number 31502, Jul.
- Josef Teichmann & Hanna Wutte, 2023, "Machine Learning-powered Pricing of the Multidimensional Passport Option," Papers, arXiv.org, number 2307.14887, Jul.
- Paolo Andreini & Cosimo Izzo & Giovanni Ricco, 2023, "Deep Dynamic Factor Models," Working Papers, Center for Research in Economics and Statistics, number 2023-08, May.
- Ivan Letteri, 2023, "VolTS: A Volatility-based Trading System to forecast Stock Markets Trend using Statistics and Machine Learning," Papers, arXiv.org, number 2307.13422, Jul, revised Aug 2023.
- Zhiyu Cao & Zihan Chen & Prerna Mishra & Hamed Amini & Zachary Feinstein, 2023, "Modeling Inverse Demand Function with Explainable Dual Neural Networks," Papers, arXiv.org, number 2307.14322, Jul, revised Oct 2023.
- Masanori Hirano & Kentaro Minami & Kentaro Imajo, 2023, "Adversarial Deep Hedging: Learning to Hedge without Price Process Modeling," Papers, arXiv.org, number 2307.13217, Jul.
- Chuheng Zhang & Yitong Duan & Xiaoyu Chen & Jianyu Chen & Jian Li & Li Zhao, 2023, "Towards Generalizable Reinforcement Learning for Trade Execution," Papers, arXiv.org, number 2307.11685, May.
- Soohan Kim & Jimyeong Kim & Hong Kee Sul & Youngjoon Hong, 2023, "An Adaptive Dual-level Reinforcement Learning Approach for Optimal Trade Execution," Papers, arXiv.org, number 2307.10649, Jul.
- 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, European Investment Fund (EIF), number 2023/91.
- Ryohei NAKAMURA & Takeshi NAGAMUNE & Syuusei HAYASHI, 2023, "Aggregation of Information and Communications Industry and Self-organization Simulation Using an Agent-based Model (Japanese)," Discussion Papers (Japanese), Research Institute of Economy, Trade and Industry (RIETI), number 23027, Aug.
- Francesco Mandelli & Marco Pinciroli & Michele Trapletti & Edoardo Vittori, 2023, "Reinforcement Learning for Credit Index Option Hedging," Papers, arXiv.org, number 2307.09844, Jul.
- Damian Ślusarczyk & Robert Ślepaczuk, 2023, "Optimal Markowitz Portfolio Using Returns Forecasted with Time Series and Machine Learning Models," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2023-17.
- Yuanhao Gong, 2023, "Dynamic Large Language Models on Blockchains," Papers, arXiv.org, number 2307.10549, Jul.
- Xiao-Yang Liu & Guoxuan Wang & Hongyang Yang & Daochen Zha, 2023, "FinGPT: Democratizing Internet-scale Data for Financial Large Language Models," Papers, arXiv.org, number 2307.10485, Jul, revised Nov 2023.
- Koefer, Franziska & Lemken, Ivo & Pauls, Jan, 2023, "Fairness in algorithmic decision systems: A microfinance perspective," EIF Working Paper Series, European Investment Fund (EIF), number 2023/88.
- 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, arXiv.org, number 2307.12776, Jul, 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, arXiv.org, number 2307.11137, Jul, 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, Institute of Transportation Studies, UC Davis, number qt5f78h654, Jul.