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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. 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:
- 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, arXiv.org, number 2208.08300, Aug.
- 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, London School of Economics and Political Science, LSE Library, number 115672, May.
- Caio Almeida & Jianqing Fan & Gustavo Freire & Francesca Tang, 2022, "Can a Machine Correct Option Pricing Models?," Working Papers, Princeton University. Economics Department., number 2022-9, Jul.
- Sullivan Hué, 2022, "GAM(L)A: An econometric model for interpretable machine learning," French Stata Users' Group Meetings 2022, Stata Users Group, number 19, Aug.
- 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, arXiv.org, number 2207.07467, Jul.
- Shuo Sun & Rundong Wang & Bo An, 2022, "Quantitative Stock Investment by Routing Uncertainty-Aware Trading Experts: A Multi-Task Learning Approach," Papers, arXiv.org, number 2207.07578, Jun.
- Leogrande, Angelo & Costantiello, Alberto & Laureti, Lucio, 2022, "k-Means Clusterization and Machine Learning Prediction of European Most Cited Scientific Publications," MPRA Paper, University Library of Munich, Germany, number 114273, Aug.
- Benedikt Geuchen & Katharina Oberpriller & Thorsten Schmidt, 2022, "Affine models with path-dependence under parameter uncertainty and their application in finance," Papers, arXiv.org, number 2207.13350, Jul, 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, Monash University, Department of Econometrics and Business Statistics, number 14/22.
- 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 simulation via les modèles EGC]," Post-Print, HAL, number hal-03740975, Jul, DOI: 10.5281/zenodo.