Report NEP-CMP-2024-06-24

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:

• Jingyang Wu & Xinyi Zhang & Fangyixuan Huang & Haochen Zhou & Rohtiash Chandra, 2024. "Review of deep learning models for crypto price prediction: implementation and evaluation," Papers 2405.11431, arXiv.org, revised Jun 2024.
• Tänzer, Alina, 2024. "Multivariate macroeconomic forecasting: From DSGE and BVAR to artificial neural networks," IMFS Working Paper Series 205, Goethe University Frankfurt, Institute for Monetary and Financial Stability (IMFS).
• Yu Xia & Sriram Narayanamoorthy & Zhengyuan Zhou & Joshua Mabry, 2024. "Simulation-Based Benchmarking of Reinforcement Learning Agents for Personalized Retail Promotions," Papers 2405.10469, arXiv.org.
• Yuji Sakurai & Zhuohui Chen, 2024. "Forecasting Tail Risk via Neural Networks with Asymptotic Expansions," IMF Working Papers 2024/099, International Monetary Fund.
• Wolff, Dominik & Echterling, Fabian, 2024. "Stock picking with machine learning," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 145491, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
• Despotovic, Miroslav & Glatschke, Matthias, 2024. "Challenges and Opportunities of Artificial Intelligence and Machine Learning in Circular Economy," SocArXiv 6qmhf, Center for Open Science.
• Yu Cheng & Qin Yang & Liyang Wang & Ao Xiang & Jingyu Zhang, 2024. "Research on Credit Risk Early Warning Model of Commercial Banks Based on Neural Network Algorithm," Papers 2405.10762, arXiv.org, revised May 2024.
• Hongyang Yang & Boyu Zhang & Neng Wang & Cheng Guo & Xiaoli Zhang & Likun Lin & Junlin Wang & Tianyu Zhou & Mao Guan & Runjia Zhang & Christina Dan Wang, 2024. "FinRobot: An Open-Source AI Agent Platform for Financial Applications using Large Language Models," Papers 2405.14767, arXiv.org, revised May 2024.
• Michael Lechner & Jana Mareckova, 2024. "Comprehensive Causal Machine Learning," Papers 2405.10198, arXiv.org.
• Gang Hu & Ming Gu, 2024. "Markowitz Meets Bellman: Knowledge-distilled Reinforcement Learning for Portfolio Management," Papers 2405.05449, arXiv.org.
• Theodoros Zafeiriou & Dimitris Kalles, 2024. "Off-the-Shelf Neural Network Architectures for Forex Time Series Prediction come at a Cost," Papers 2405.10679, arXiv.org.
• Buczak, Philip, 2024. "fabOF: A Novel Tree Ensemble Method for Ordinal Prediction," OSF Preprints h8t4p, Center for Open Science.
• Raeid Saqur & Ken Kato & Nicholas Vinden & Frank Rudzicz, 2024. "NIFTY Financial News Headlines Dataset," Papers 2405.09747, arXiv.org.
• Krist'of N'emeth & D'aniel Hadh'azi, 2024. "Generating density nowcasts for U.S. GDP growth with deep learning: Bayes by Backprop and Monte Carlo dropout," Papers 2405.15579, arXiv.org.
• Yunfei Peng & Pengyu Wei & Wei Wei, 2024. "Deep Penalty Methods: A Class of Deep Learning Algorithms for Solving High Dimensional Optimal Stopping Problems," Papers 2405.11392, arXiv.org.
• Kentaro Hoffman & Stephen Salerno & Jeff Leek & Tyler McCormick, 2024. "Some models are useful, but for how long?: A decision theoretic approach to choosing when to refit large-scale prediction models," Papers 2405.13926, arXiv.org, revised Jan 2025.
• Tom Suhr & Samira Samadi & Chiara Farronato, 2024. "A Dynamic Model of Performative Human-ML Collaboration: Theory and Empirical Evidence," Papers 2405.13753, arXiv.org, revised Oct 2024.
• Huiyu Li & Junhua Hu, 2024. "A Hybrid Deep Learning Framework for Stock Price Prediction Considering the Investor Sentiment of Online Forum Enhanced by Popularity," Papers 2405.10584, arXiv.org.
• Daniel Aromí & Daniel Heymann, 2024. "Talk to Fed: a Big Dive into FOMC Transcripts," Working Papers 323, Red Nacional de Investigadores en Economía (RedNIE).