Report NEP-CMP-2022-09-12

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.

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Other reports in NEP-CMP

The following items were announced in this report:

• Tashreef Muhammad & Anika Bintee Aftab & Md. Mainul Ahsan & Maishameem Meherin Muhu & Muhammad Ibrahim & Shahidul Islam Khan & Mohammad Shafiul Alam, 2022. "Transformer-Based Deep Learning Model for Stock Price Prediction: A Case Study on Bangladesh Stock Market," Papers 2208.08300, arXiv.org.
• Djenontin, Ida N.S. & Ligmann-Zielinska, Arika & Zulu, Leo C., 2022. "Landscape-scale effects of farmers’ restoration decision making and investments in central Malawi: an agent-based modeling approach," LSE Research Online Documents on Economics 115672, London School of Economics and Political Science, LSE Library.
• Caio Almeida & Jianqing Fan & Gustavo Freire & Francesca Tang, 2022. "Can a Machine Correct Option Pricing Models?," Working Papers 2022-9, Princeton University. Economics Department..
• Sullivan Hué, 2022. "GAM(L)A: An econometric model for interpretable machine learning," French Stata Users' Group Meetings 2022 19, Stata Users Group.
• Phillip Murray & Ben Wood & Hans Buehler & Magnus Wiese & Mikko S. Pakkanen, 2022. "Deep Hedging: Continuous Reinforcement Learning for Hedging of General Portfolios across Multiple Risk Aversions," Papers 2207.07467, arXiv.org.
• Shuo Sun & Rundong Wang & Bo An, 2022. "Quantitative Stock Investment by Routing Uncertainty-Aware Trading Experts: A Multi-Task Learning Approach," Papers 2207.07578, arXiv.org.
• Leogrande, Angelo & Costantiello, Alberto & Laureti, Lucio, 2022. "k-Means Clusterization and Machine Learning Prediction of European Most Cited Scientific Publications," MPRA Paper 114273, University Library of Munich, Germany.
• Benedikt Geuchen & Katharina Oberpriller & Thorsten Schmidt, 2022. "Affine models with path-dependence under parameter uncertainty and their application in finance," Papers 2207.13350, arXiv.org, revised Jun 2024.
• Gael M. Martin & David T. Frazier & Christian P. Robert, 2022. "Computing Bayes: From Then `Til Now," Monash Econometrics and Business Statistics Working Papers 14/22, Monash University, Department of Econometrics and Business Statistics.
• Chtouki Zakaria & Deriouch Kaoutar, 2022. "Reducing Socio-Economic Inequality Policies: Exploring the Possibilities of Simulation Using CGE Modelling [Politiques de réductions des inégalités socioéconomiques : Analyse des possibilités de la," Post-Print hal-03740975, HAL.