Report NEP-CMP-2024-07-15

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.

Subscribe to this report: email, RSS, or Mastodon.

Other reports in NEP-CMP

The following items were announced in this report:

• Askitas, Nikos, 2024. "A Hands-on Machine Learning Primer for Social Scientists: Math, Algorithms and Code," IZA Discussion Papers 17014, Institute of Labor Economics (IZA).
• Alexander Bakumenko & Katev{r}ina Hlav'av{c}kov'a-Schindler & Claudia Plant & Nina C. Hubig, 2024. "Advancing Anomaly Detection: Non-Semantic Financial Data Encoding with LLMs," Papers 2406.03614, arXiv.org.
• Bivas Dinda, 2024. "Gated recurrent neural network with TPE Bayesian optimization for enhancing stock index prediction accuracy," Papers 2406.02604, arXiv.org.
• Mark E. Schaffer, 2023. "pystacked and ddml: Machine learning for prediction and causal inference in Stata," Economics Virtual Symposium 2023 04, Stata Users Group.
• Tohid Atashbar, 2024. "Reinforcement Learning from Experience Feedback: Application to Economic Policy," IMF Working Papers 2024/114, International Monetary Fund.
• Milen Arro-Cannarsa & Dr. Rolf Scheufele, 2024. "Nowcasting GDP: what are the gains from machine learning algorithms?," Working Papers 2024-06, Swiss National Bank.
• Francesco Audrino & Jonathan Chassot, 2024. "HARd to Beat: The Overlooked Impact of Rolling Windows in the Era of Machine Learning," Papers 2406.08041, arXiv.org.
• Buxmann, Peter & Hess, Thomas & Thatcher, Jason Bennett, 2024. "AI-Based Information Systems," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 146094, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
• Sugarbayar Enkhbayar & Robert Ślepaczuk, 2024. "Predictive modeling of foreign exchange trading signals using machine learning techniques," Working Papers 2024-10, Faculty of Economic Sciences, University of Warsaw.
• Kumar, Pradeep & Nicodemo, Catia & Oreffice, Sonia & Quintana-Domeque, Climent, 2024. "Machine Learning and Multiple Abortions," IZA Discussion Papers 17046, Institute of Labor Economics (IZA).
• Adam Korniejczuk & Robert Ślepaczuk, 2024. "Statistical arbitrage in multi-pair trading strategy based on graph clustering algorithms in US equities market," Working Papers 2024-09, Faculty of Economic Sciences, University of Warsaw.
• Seulki Chung, 2024. "Modelling and Forecasting Energy Market Volatility Using GARCH and Machine Learning Approach," Papers 2405.19849, arXiv.org.
• Ayush Singh & Anshu K. Jha & Amit N. Kumar, 2024. "Prediction of Cryptocurrency Prices through a Path Dependent Monte Carlo Simulation," Papers 2405.12988, arXiv.org.
• Kase, Hanno & Melosi, Leonardo & Rottner, Matthias, 2024. "Estimating Nonlinear Heterogeneous Agent Models with Neural Networks," The Warwick Economics Research Paper Series (TWERPS) 1499, University of Warwick, Department of Economics.
• Junquera, Álvaro F. & Kern, Christoph, 2024. "From rules to forests: rule-based versus statistical models for jobseeker profiling," SocArXiv c7ps3, Center for Open Science.
• Sven Goluv{z}a & Tomislav Kovav{c}evi'c & Tessa Bauman & Zvonko Kostanjv{c}ar, 2024. "Deep reinforcement learning with positional context for intraday trading," Papers 2406.08013, arXiv.org.
• Simon D Angus & Lachlan O'Neill, 2024. "Paired completion: quantifying issue-framing at scale with LLMs," SoDa Laboratories Working Paper Series 2024-02, Monash University, SoDa Laboratories.
• Edward Sharkey & Philip Treleaven, 2024. "BERT vs GPT for financial engineering," Papers 2405.12990, arXiv.org.
• Bernhard Kasberger & Simon Martin & Hans-Theo Normann & Tobias Werner, 2024. "Algorithmic Cooperation," CESifo Working Paper Series 11124, CESifo.
• Fabrice Murtin & Max Salomon-Ermel, 2024. "Nowcasting subjective well-being with Google Trends: A meta-learning approach," OECD Papers on Well-being and Inequalities 27, OECD Publishing.
• Emily Silcock & Abhishek Arora & Luca D'Amico-Wong & Melissa Dell, 2024. "Newswire: A Large-Scale Structured Database of a Century of Historical News," Papers 2406.09490, arXiv.org.
• Nicole Immorlica & Brendan Lucier & Aleksandrs Slivkins, 2024. "Generative AI as Economic Agents," Papers 2406.00477, arXiv.org.
• Raeid Saqur & Anastasis Kratsios & Florian Krach & Yannick Limmer & Jacob-Junqi Tian & John Willes & Blanka Horvath & Frank Rudzicz, 2024. "Filtered not Mixed: Stochastic Filtering-Based Online Gating for Mixture of Large Language Models," Papers 2406.02969, arXiv.org.
• Nicolás Forteza & Elvira Prades & Marc Roca, 2024. "Analysing the VAT cut pass-through in Spain using web-scraped supermarket data and machine learning," Working Papers 2417, Banco de España.
• Can Celebi & Stefan Penczynski, 2024. "Using Large Language Models for Text Classification in Experimental Economics," Working Paper series, University of East Anglia, Centre for Behavioural and Experimental Social Science (CBESS) 24-01, School of Economics, University of East Anglia, Norwich, UK..
• Daniel Vebman, 2024. "Quantifying the Reliance of Black-Box Decision-Makers on Variables of Interest," Papers 2405.17225, arXiv.org.
• Pablo Alvarez-Campana & Felix Villafanez & Fernando Acebes & David Poza, 2024. "Simulation-based approach for Multiproject Scheduling based on composite priority rules," Papers 2406.02102, arXiv.org.
• Joel Ong & Dorien Herremans, 2024. "DeepUnifiedMom: Unified Time-series Momentum Portfolio Construction via Multi-Task Learning with Multi-Gate Mixture of Experts," Papers 2406.08742, arXiv.org.
• Guido Gazzani & Julien Guyon, 2024. "Pricing and calibration in the 4-factor path-dependent volatility model," Papers 2406.02319, arXiv.org.
• Jingru Jia & Zehua Yuan & Junhao Pan & Paul E. McNamara & Deming Chen, 2024. "Decision-Making Behavior Evaluation Framework for LLMs under Uncertain Context," Papers 2406.05972, arXiv.org, revised Oct 2024.
• Mengfei Chen & Mohamed Kharbeche & Mohamed Haouari & Weihong Grace Guo, 2024. "A simulation-optimization framework for food supply chain network design to ensure food accessibility under uncertainty," Papers 2406.04439, arXiv.org, revised Jun 2024.