Report NEP-CMP-2024-12-30

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.

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Other reports in NEP-CMP

The following items were announced in this report:

• Jian Guo & Saizhuo Wang & Yiyan Qi, 2024, "Guided Learning: Lubricating End-to-End Modeling for Multi-stage Decision-making," Papers, arXiv.org, number 2411.10496, Nov.
• Ananya Unnikrishnan, 2024, "Financial News-Driven LLM Reinforcement Learning for Portfolio Management," Papers, arXiv.org, number 2411.11059, Nov.
• Joshua Aslett & Stuart Hamilton & Ignacio Gonzalez & David Hadwick & Michael A Hardy & Azael Pérez, 2024, "Understanding Artificial Intelligence in Tax and Customs Administration," IMF Technical Notes and Manuals, International Monetary Fund, number 2024/006, Nov.
• Xin Zhang & Zhen Xu & Yue Liu & Mengfang Sun & Tong Zhou & Wenying Sun, 2024, "Robust Graph Neural Networks for Stability Analysis in Dynamic Networks," Papers, arXiv.org, number 2411.11848, Oct.
• Tsogt-Ochir Enkhbayar, 2024, "A New Way: Kronecker-Factored Approximate Curvature Deep Hedging and its Benefits," Papers, arXiv.org, number 2411.15002, Nov.
• Sorouralsadat Fatemi & Yuheng Hu, 2024, "FinVision: A Multi-Agent Framework for Stock Market Prediction," Papers, arXiv.org, number 2411.08899, Oct.
• Marco Hening Tallarico & Pablo Olivares, 2024, "Neural and Time-Series Approaches for Pricing Weather Derivatives: Performance and Regime Adaptation Using Satellite Data," Papers, arXiv.org, number 2411.12013, Nov, revised May 2025.
• Junjie Guo, 2024, "Deep Learning in Long-Short Stock Portfolio Allocation: An Empirical Study," Papers, arXiv.org, number 2411.13555, Oct, revised Nov 2024.
• Jue Xiao & Tingting Deng & Shuochen Bi, 2024, "Comparative Analysis of LSTM, GRU, and Transformer Models for Stock Price Prediction," Papers, arXiv.org, number 2411.05790, Oct.
• Bartosz Bieganowski & Robert 'Slepaczuk, 2024, "Supervised Autoencoders with Fractionally Differentiated Features and Triple Barrier Labelling Enhance Predictions on Noisy Data," Papers, arXiv.org, number 2411.12753, Nov, revised Nov 2024.
• Shuochen Bi & Tingting Deng & Jue Xiao, 2024, "The Role of AI in Financial Forecasting: ChatGPT's Potential and Challenges," Papers, arXiv.org, number 2411.13562, Nov.
• Mabsur Fatin Bin Hossain & Lubna Zahan Lamia & Md Mahmudur Rahman & Md Mosaddek Khan, 2024, "FinBERT-BiLSTM: A Deep Learning Model for Predicting Volatile Cryptocurrency Market Prices Using Market Sentiment Dynamics," Papers, arXiv.org, number 2411.12748, Nov.
• Karel Janda & Mathieu Petit, 2024, "Analyzing Decision-Making in Deep-Q Reinforcement Learning for Trading: A Case Study on Tesla Company and its Supply Chain," Working Papers IES, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, number 2024/40, Nov, revised Nov 2024.
• Simon D Angus, 2024, "Tracking Policy-relevant Narratives of Democratic Resilience at Scale: from experts and machines, to AI & the transformer revolution," SoDa Laboratories Working Paper Series, Monash University, SoDa Laboratories, number 2024-07, Dec.
• Claudia Biancotti & Carolina Camassa & Andrea Coletta & Oliver Giudice & Aldo Glielmo, 2024, "Chat Bankman-Fried: an Exploration of LLM Alignment in Finance," Papers, arXiv.org, number 2411.11853, Nov, revised Feb 2025.
• Peter Dixon & Michael Jerie & Dean Mustakinov & Maureen T. Rimmer & Nicholas Sheard & Florian Schiffmann & Glyn Wittwer, 2024, "Constructing a Destructive Events Tool using Small Rectangular Areas, Computable General Equilibrium Modelling and Neural Networks," Centre of Policy Studies/IMPACT Centre Working Papers, Victoria University, Centre of Policy Studies/IMPACT Centre, number g-349, Dec.
• Lars Fluri & A. Ege Yilmaz & Denis Bieri & Thomas Ankenbrand & Aurelio Perucca, 2024, "Simulating Liquidity: Agent-Based Modeling of Illiquid Markets for Fractional Ownership," Papers, arXiv.org, number 2411.13381, Nov, revised Dec 2024.
• Yahui Bai & Yuhe Gao & Runzhe Wan & Sheng Zhang & Rui Song, 2024, "A Review of Reinforcement Learning in Financial Applications," Papers, arXiv.org, number 2411.12746, Oct.
• Sahand Hassanizorgabad, 2024, "Composing Ensembles of Instrument-Model Pairs for Optimizing Profitability in Algorithmic Trading," Papers, arXiv.org, number 2411.13559, Nov.
• James B. Glattfelder & Thomas Houweling, 2024, "Calculating Profits and Losses for Algorithmic Trading Strategies: A Short Guide," Papers, arXiv.org, number 2411.14068, Nov.
• Junhua Liu, 2024, "A Survey of Financial AI: Architectures, Advances and Open Challenges," Papers, arXiv.org, number 2411.12747, Nov.
• Martin Arnaiz Iglesias & Adil Rengim Cetingoz & Noufel Frikha, 2024, "Mirror Descent Algorithms for Risk Budgeting Portfolios," Papers, arXiv.org, number 2411.12323, Nov.