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Report NEP-CMP-2024-06-17
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:
- Simone Brusatin & Tommaso Padoan & Andrea Coletta & Domenico Delli Gatti & Aldo Glielmo, 2024, "Simulating the Economic Impact of Rationality through Reinforcement Learning and Agent-Based Modelling," Papers, arXiv.org, number 2405.02161, May, revised Oct 2024.
- Xiaowei Chen & Hong Li & Yufan Lu & Rui Zhou, 2024, "Unveiling Nonlinear Dynamics in Catastrophe Bond Pricing: A Machine Learning Perspective," Papers, arXiv.org, number 2405.00697, Apr, revised Aug 2024.
- Reilly Pickard & F. Wredenhagen & Y. Lawryshyn, 2024, "Optimizing Deep Reinforcement Learning for American Put Option Hedging," Papers, arXiv.org, number 2405.08602, May.
- Tänzer, Alina, 2024, "The effectiveness of central bank purchases of long-term treasury securities: A neural network approach," IMFS Working Paper Series, Goethe University Frankfurt, Institute for Monetary and Financial Stability (IMFS), number 204.
- Theodoros Zafeiriou & Dimitris Kalles, 2024, "Comparative analysis of neural network architectures for short-term FOREX forecasting," Papers, arXiv.org, number 2405.08045, May.
- Tomaz Cajner & Leland D. Crane & Christopher J. Kurz & Norman J. Morin & Paul E. Soto & Betsy Vrankovich, 2024, "Manufacturing Sentiment: Forecasting Industrial Production with Text Analysis," Finance and Economics Discussion Series, Board of Governors of the Federal Reserve System (U.S.), number 2024-026, May, DOI: 10.17016/FEDS.2024.026.
- Tian Tian & Jiahao Deng, 2024, "Unleashing the Power of AI: Transforming Marketing Decision-Making in Heavy Machinery with Machine Learning, Radar Chart Simulation, and Markov Chain Analysis," Papers, arXiv.org, number 2405.01913, May.
- Daniel de Souza Santos & Tiago Alessandro Espinola Ferreira, 2024, "Neural Network Learning of Black-Scholes Equation for Option Pricing," Papers, arXiv.org, number 2405.05780, May.
- G. Ibikunle & B. Moews & D. Muravyev & K. Rzayev, 2024, "Data-driven measures of high-frequency trading," Papers, arXiv.org, number 2405.08101, May, revised Mar 2025.
- Reilly Pickard & Finn Wredenhagen & Julio DeJesus & Mario Schlener & Yuri Lawryshyn, 2024, "Hedging American Put Options with Deep Reinforcement Learning," Papers, arXiv.org, number 2405.06774, May.
- Ashish Anil Pawar & Vishnureddy Prashant Muskawar & Ritesh Tiku, 2024, "Portfolio Management using Deep Reinforcement Learning," Papers, arXiv.org, number 2405.01604, May.
- Ajit Desai & Anneke Kosse & Jacob Sharples, 2024, "Finding a needle in a haystack: a machine learning framework for anomaly detection in payment systems," BIS Working Papers, Bank for International Settlements, number 1188, May.
- Joaquin Vespignani & Russell Smyth, 2024, "Artificial Intelligence Investments Reduce Risks to Critical Mineral Supply," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2024-30, May.
- Yusuke Narita & Kohei Yata, 2024, "Algorithm as Experiment: Machine Learning, Market Design, and Policy Eligibility Rules," Cowles Foundation Discussion Papers, Cowles Foundation for Research in Economics, Yale University, number 2391, May.
- Kea Baret & Amélie Barbier-Gauchard & Theophilos Papadimitriou, 2023, "Forecasting the Stability and Growth Pact compliance using Machine Learning," Post-Print, HAL, number hal-03121966, Oct, DOI: 10.1111/twec.13518.
- Zhiyu Cao & Zachary Feinstein, 2024, "Large Language Model in Financial Regulatory Interpretation," Papers, arXiv.org, number 2405.06808, May, revised Jul 2024.
- Felix Haag & Carlo Stingl & Katrin Zerfass & Konstantin Hopf & Thorsten Staake, 2024, "Overcoming Anchoring Bias: The Potential of AI and XAI-based Decision Support," Papers, arXiv.org, number 2405.04972, May.
- Attila Sarkany & Lukas Janasek & Jozef Barunik, 2024, "Quantile Preferences in Portfolio Choice: A Q-DRL Approach to Dynamic Diversification," Working Papers IES, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, number 2024/21, May, revised May 2024.
- Christian Peukert & Florian Abeillon & Jérémie Haese & Franziska Kaiser & Alexander Staub, 2024, "Strategic Behavior and AI Training Data," CESifo Working Paper Series, CESifo, number 11099.
- Maria S. Mavillonio, 2024, "Textual Representation of Business Plans and Firm Success," Discussion Papers, Dipartimento di Economia e Management (DEM), University of Pisa, Pisa, Italy, number 2024/308, May.
- Jack Birner & Marco Mazzoli & Eleonora Priori & Pietro Terna, 2024, "Breaking open the black box of the production function: an agent-based model accounting for time in production processes," Papers, arXiv.org, number 2405.07103, May.
- Jiri Kukacka & Erik Zila, 2024, "Wealth, Cost, and Misperception: Empirical Estimation of Three Interaction Channels in a Financial-Macroeconomic Agent-Based Model," Working Papers IES, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, number 2024/22, May, revised May 2024.
- Chuanhao Li & Runhan Yang & Tiankai Li & Milad Bafarassat & Kourosh Sharifi & Dirk Bergemann & Zhuoran Yang, 2024, "STRIDE: A Tool-Assisted LLM Agent Framework for Strategic and Interactive Decision-Making," Cowles Foundation Discussion Papers, Cowles Foundation for Research in Economics, Yale University, number 2393, May.
- Nicholas Tenev, 2024, "De-Biasing Models of Biased Decisions: A Comparison of Methods Using Mortgage Application Data," Papers, arXiv.org, number 2405.00910, May.
- S. Borağan Aruoba & Thomas Drechsel, 2024, "Identifying Monetary Policy Shocks: A Natural Language Approach," NBER Working Papers, National Bureau of Economic Research, Inc, number 32417, May.
- Eric Ghysels & Jack Morgan, 2024, "On Quantum Ambiguity and Potential Exponential Computational Speed-Ups to Solving Dynamic Asset Pricing Models," Papers, arXiv.org, number 2405.01479, May, revised Aug 2025.
- Sylvain BARTHÉLÉMY & Virginie GAUTIER & Fabien RONDEAU, 2024, "Convolutional Neural Networks to signal currency crises: from the Asian financial crisis to the Covid crisis," Economics Working Paper Archive (University of Rennes & University of Caen), Center for Research in Economics and Management (CREM), University of Rennes, University of Caen and CNRS, number 2024-01, Mar.
- Thorsten Hens & Trine Nordlie, 2024, "How good are LLMs in risk profiling?," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 24-30, Apr.
- Adam Hallengreen & Thomas H. Joergensen & Annasofie M. Olesen, 2024, "Household Bargaining with Limited Commitment: A Practitioners Guide," CEBI working paper series, University of Copenhagen. Department of Economics. The Center for Economic Behavior and Inequality (CEBI), number 24-09, May.