Report NEP-CMP-2023-08-21

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:

• Robert Balkin & Hector D. Ceniceros & Ruimeng Hu, 2023, "Stochastic Delay Differential Games: Financial Modeling and Machine Learning Algorithms," Papers, arXiv.org, number 2307.06450, Jul.
• Serena Della Corte & Laurens Van Mieghem & Antonis Papapantoleon & Jonas Papazoglou-Hennig, 2023, "Machine learning for option pricing: an empirical investigation of network architectures," Papers, arXiv.org, number 2307.07657, Jul, revised Jan 2026.
• Valentin Lourme, 2023, "analysis of the predictor of a volatility surface by machine learning
  [Analyse de la prédiction d'une nappe de volatilité par Machine Learning]," Post-Print, HAL, number hal-04151604, Jul.
• Ali Lashgari, 2023, "Harnessing the Potential of Volatility: Advancing GDP Prediction," Papers, arXiv.org, number 2307.05391, Jun.
• Apostolos Ampountolas, 2023, "Comparative Analysis of Machine Learning, Hybrid, and Deep Learning Forecasting Models Evidence from European Financial Markets and Bitcoins," Papers, arXiv.org, number 2307.08853, Jul.
• Kosuke Tatsumura & Ryo Hidaka & Jun Nakayama & Tomoya Kashimata & Masaya Yamasaki, 2023, "Real-time Trading System based on Selections of Potentially Profitable, Uncorrelated, and Balanced Stocks by NP-hard Combinatorial Optimization," Papers, arXiv.org, number 2307.06339, Jul.
• Johanna Deperi & Ludovic Dibiaggio & Mohamed Keita & Lionel Nesta, 2023, "Ideas Without Scale in French Artificial Intelligence Innovations," Post-Print, HAL, number hal-04144817, Jun.
• Ross Williams & Niyousha Hosseinichimeh & Aritra Majumdar & Navid Ghaffarzadegan, 2023, "Epidemic Modeling with Generative Agents," Papers, arXiv.org, number 2307.04986, Jul.
• Zhu Bangyuan, 2023, "Critical comparisons on deep learning approaches for foreign exchange rate prediction," Papers, arXiv.org, number 2307.06600, Jul.
• Andrii Babii & Ryan T. Ball & Eric Ghysels & Jonas Striaukas, 2023, "Panel Data Nowcasting: The Case of Price-Earnings Ratios," Papers, arXiv.org, number 2307.02673, Jul.
• Item repec:bea:wpaper:0209 is not listed on IDEAS anymore

• Chung I Lu, 2023, "Evaluation of Deep Reinforcement Learning Algorithms for Portfolio Optimisation," Papers, arXiv.org, number 2307.07694, Jul, revised Aug 2025.
• Lucas Potin & Rosa Figueiredo & Vincent Labatut & Christine Largeron, 2023, "Pattern Mining for Anomaly Detection in Graphs: Application to Fraud in Public Procurement," Post-Print, HAL, number hal-04131485, Sep, DOI: 10.1007/978-3-031-43427-3_5.
• Zhou Fang & Haiqing Xu, 2023, "Over-the-Counter Market Making via Reinforcement Learning," Papers, arXiv.org, number 2307.01816, Jul.
• Tom Liu & Stephen Roberts & Stefan Zohren, 2023, "Deep Inception Networks: A General End-to-End Framework for Multi-asset Quantitative Strategies," Papers, arXiv.org, number 2307.05522, Jul.
• Lilit Popoyan & Mauro Napoletano & Andrea Roventini, 2023, "Systemically important banks - emerging risk and policy responses: An agent-based investigation," LEM Papers Series, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy, number 2023/30, Jul.
• Shuo Yu & Hongyan Xue & Xiang Ao & Feiyang Pan & Jia He & Dandan Tu & Qing He, 2023, "Generating Synergistic Formulaic Alpha Collections via Reinforcement Learning," Papers, arXiv.org, number 2306.12964, May.
• Francesco Cordoni & Alessio Sancetta, 2023, "Action-State Dependent Dynamic Model Selection," Papers, arXiv.org, number 2307.04754, Jul, revised Oct 2023.
• Christian Fieberg & Lars Hornuf & David J. Streich, 2023, "Using GPT-4 for Financial Advice," CESifo Working Paper Series, CESifo, number 10529.
• Zhou Fang & Haiqing Xu, 2023, "Option Market Making via Reinforcement Learning," Papers, arXiv.org, number 2307.01814, Jul, revised Mar 2025.
• Viet Hoang Dinh & Didier Nibbering & Benjamin Wong, 2023, "Random Subspace Local Projections," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2023-34, Jul.
• Marta Serra-Garcia & Uri Gneezy, 2023, "Improving Human Deception Detection Using Algorithmic Feedback," CESifo Working Paper Series, CESifo, number 10518.
• Kamer Ali Yuksel, 2023, "Generative Meta-Learning Robust Quality-Diversity Portfolio," Papers, arXiv.org, number 2307.07811, Jul.
• Aditya Gupta & Vijay K. Tayal, 2023, "Using Monte Carlo Methods for Retirement Simulations," Papers, arXiv.org, number 2306.16563, Jun, revised Nov 2023.
• Hacker, Bernd, 2023, "Will ChatGPT revolutionize accounting? The benefits of Artificial Intelligence (AI) in accounting
  [Analysis of the significance of employer branding in generations Y and Z]," Rosenheim Papers in Applied Economics and Business Sciences, Rosenheim Technical University of Applied Sciences, number 6/2023.
• Cappelli, Peter, & Rogovsky, Nikolai,, 2023, "Artificial intelligence in human resource management a challenge for the human-centred agenda?," ILO Working Papers, International Labour Organization, number 995320592902676, DOI: 10.54394/OHVV4382.
• Bauer, Kevin & von Zahn, Moritz & Hinz, Oliver, 2023, "Please take over: XAI, delegation of authority, and domain knowledge," SAFE Working Paper Series, Leibniz Institute for Financial Research SAFE, number 394.
• L. Galiana & L. Wilner, 2023, "Private Wealth over the Life-Cycle: A Meeting between Microsimulation and Structural Approaches," Documents de Travail de l'Insee - INSEE Working Papers, Institut National de la Statistique et des Etudes Economiques, number 2023-04.
• Sedar Olmez & Akhil Ahmed & Keith Kam & Zhe Feng & Alan Tua, 2023, "Exploring the Dynamics of the Specialty Insurance Market Using a Novel Discrete Event Simulation Framework: a Lloyd's of London Case Study," Papers, arXiv.org, number 2307.05581, Jul.
• Zhou, Yunzhe & Shi, Chengchun & Li, Lexin & Yao, Qiwei, 2023, "Testing for the Markov property in time series via deep conditional generative learning," LSE Research Online Documents on Economics, London School of Economics and Political Science, LSE Library, number 119352, Sep.
• Guillaume Chevalier & Guillaume Coqueret & Thomas Raffinot, 2022, "Supervised portfolios," Post-Print, HAL, number hal-04144588, Dec, DOI: 10.1080/14697688.2022.2122543.
• Daouda Diakité & Michel Paul & Valentin Morin, 2023, "Newts microsimulation model for an informative and co-creative public-decision making," Post-Print, HAL, number hal-04147771, May.
• León, C. & Moreno, Jose & Soramaki, Kimmo, 2023, "Simulating the Adoption of a Retail CBDC," Discussion Paper, Tilburg University, Center for Economic Research, number 2023-018.
• Li, Xiaofei & Mieno, Taro & Bullock, David S, , "The Economic Performances of Different Trial Designs in OnFarm Precision Experimentation: A Monte Carlo Evaluation," Agri-Tech Economics Papers, Harper Adams University, Land, Farm & Agribusiness Management Department, number 337136, DOI: 10.22004/ag.econ.337136.
• Angelov, Nikolay & Waldenström, Daniel, 2023, "The Economic Effects of COVID-19 in Sweden: A Report on Income, Taxes, Distribution, and Government Support Policies," IZA Policy Papers, Institute of Labor Economics (IZA), number 200, Jul.

Report NEP-CMP-2023-08-21

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: