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Report NEP-CMP-2024-12-16
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:
- Jésus Fernández-Villaverde & Galo Nuño & Jesse Perla & Jesús Fernández-Villaverde, 2024, "Taming the Curse of Dimensionality: Quantitative Economics with Deep Learning," CESifo Working Paper Series, CESifo, number 11448.
- Yaacov Kopeliovich & Michael Pokojovy, 2024, "Portfolio Optimization with Feedback Strategies Based on Artificial Neural Networks," Papers, arXiv.org, number 2411.09899, Nov.
- Asef Yelghi & Aref Yelghi & Shirmohammad Tavangari, 2024, "Artificial Intelligence in Financial Forecasting: Analyzing the Suitability of AI Models for Dollar/TL Exchange Rate Predictions," Papers, arXiv.org, number 2411.04259, Nov, revised Nov 2024.
- Yadh Hafsi & Edoardo Vittori, 2024, "Optimal Execution with Reinforcement Learning," Papers, arXiv.org, number 2411.06389, Nov, revised Nov 2025.
- Haowen Bao & Yongmiao Hong & Yuying Sun & Shouyang Wang, 2024, "Sparse Interval-valued Time Series Modeling with Machine Learning," Papers, arXiv.org, number 2411.09452, Nov.
- Shamima Nasrin Tumpa & Kehelwala Dewage Gayan Maduranga, 2024, "Utilizing RNN for Real-time Cryptocurrency Price Prediction and Trading Strategy Optimization," Papers, arXiv.org, number 2411.05829, Nov.
- Sven Goluv{z}a & Tomislav Kovav{c}evi'c & Stjepan Beguv{s}i'c & Zvonko Kostanjv{c}ar, 2024, "Robot See, Robot Do: Imitation Reward for Noisy Financial Environments," Papers, arXiv.org, number 2411.08637, Nov.
- Luo, Nanyu & Ji, Feng & Han, Yuting & He, Jinbo & Zhang, Xiaoya, 2024, "Fitting item response theory models using deep learning computational frameworks," OSF Preprints, Center for Open Science, number tjxab, Oct, DOI: 10.31219/osf.io/tjxab.
- Xianhua Peng & Xiang Zhou & Bo Xiao & Yi Wu, 2024, "A Risk Sensitive Contract-unified Reinforcement Learning Approach for Option Hedging," Papers, arXiv.org, number 2411.09659, Nov.
- Anton Korinek & Jai Vipra, 2024, "Concentrating Intelligence: Scaling and Market Structure in Artificial Intelligence," NBER Working Papers, National Bureau of Economic Research, Inc, number 33139, Nov.
- Augusto Cerqua & Marco Letta & Gabriele Pinto, 2024, "On the (Mis)Use of Machine Learning with Panel Data," Papers, arXiv.org, number 2411.09218, Nov, revised May 2025.
- Peng Zhu & Yuante Li & Yifan Hu & Sheng Xiang & Qinyuan Liu & Dawei Cheng & Yuqi Liang, 2024, "MCI-GRU: Stock Prediction Model Based on Multi-Head Cross-Attention and Improved GRU," Papers, arXiv.org, number 2410.20679, Sep, revised Aug 2025.
- Rui Liu & Jiayou Liang & Haolong Chen & Yujia Hu, 2024, "Analyst Reports and Stock Performance: Evidence from the Chinese Market," Papers, arXiv.org, number 2411.08726, Nov, revised Mar 2025.
- Abdul Rahman & Neelesh Upadhye, 2024, "Hybrid Vector Auto Regression and Neural Network Model for Order Flow Imbalance Prediction in High Frequency Trading," Papers, arXiv.org, number 2411.08382, Nov.
- Amilcar Velez, 2024, "On the Asymptotic Properties of Debiased Machine Learning Estimators," Papers, arXiv.org, number 2411.01864, Nov.
- Alhassan S. Yasin & Prabdeep S. Gill, 2024, "Reinforcement Learning Framework for Quantitative Trading," Papers, arXiv.org, number 2411.07585, Nov.
- Tianyu Zhou & Pinqiao Wang & Yilin Wu & Hongyang Yang, 2024, "FinRobot: AI Agent for Equity Research and Valuation with Large Language Models," Papers, arXiv.org, number 2411.08804, Nov.
- Hoyoung Lee & Youngsoo Choi & Yuhee Kwon, 2024, "Quantifying Qualitative Insights: Leveraging LLMs to Market Predict," Papers, arXiv.org, number 2411.08404, Nov.
- Souhir Ben Amor & Thomas Mobius & Felix Musgens, 2024, "Bridging an energy system model with an ensemble deep-learning approach for electricity price forecasting," Papers, arXiv.org, number 2411.04880, Nov.
- James S. Cummins & Natalia G. Berloff, 2024, "A Fully Analog Pipeline for Portfolio Optimization," Papers, arXiv.org, number 2411.06566, Nov.
- Daniele Ballinari & Alexander Wehrli, 2024, "Semiparametric inference for impulse response functions using double/debiased machine learning," Papers, arXiv.org, number 2411.10009, Nov, revised Dec 2025.
- Hisham I. Al-Shuwaikhat, 2024, "Harnessing Artificial Intelligence (AI) for Smarter Decisions: Shaping the Future of Contemporary Management for Modern Business," SBS Swiss Business School Research Conference (SBS-RC), SBS Swiss Business School, number 002, Oct.
- Hugo Schnoering & Michalis Vazirgiannis, 2024, "Bitcoin Research with a Transaction Graph Dataset," Papers, arXiv.org, number 2411.10325, Nov.
- Achintya Gopal, 2024, "Filling in Missing FX Implied Volatilities with Uncertainties: Improving VAE-Based Volatility Imputation," Papers, arXiv.org, number 2411.05998, Nov.
- Masahiro Suzuki & Hiroki Sakaji, 2024, "Refined and Segmented Price Sentiment Indices from Survey Comments," Papers, arXiv.org, number 2411.09937, Nov, revised Nov 2024.
- Davide Lauria & JiHo Park & Yuan Hu & W. Brent Lindquist & Svetlozar T. Rachev & Frank J. Fabozzi, 2024, "An Empirical Implementation of the Shadow Riskless Rate," Papers, arXiv.org, number 2411.07421, Nov.