Report NEP-CMP-2022-01-17

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:

• Andrew Butler & Roy Kwon, 2021, "Efficient differentiable quadratic programming layers: an ADMM approach," Papers, arXiv.org, number 2112.07464, Dec.
• Schmidt, Lorenz & Odening, Martin & Ritter, Matthias, , "Estimation of the weather-yield nexus with Artificial Neural Networks," Land, Farm & Agribusiness Management Department, Harper Adams University, Land, Farm & Agribusiness Management Department, number 316598, DOI: 10.22004/ag.econ.316598.
• Damir Filipović & Amir Khalilzadeh, 2021, "Machine Learning for Predicting Stock Return Volatility," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 21-95, Dec.
• Dafei Yin & Jing Li & Gaosheng Wu, 2021, "Solving the Data Sparsity Problem in Predicting the Success of the Startups with Machine Learning Methods," Papers, arXiv.org, number 2112.07985, Dec.
• Jiequn Han & Yucheng Yang & Weinan E, 2021, "DeepHAM: A Global Solution Method for Heterogeneous Agent Models with Aggregate Shocks," Papers, arXiv.org, number 2112.14377, Dec, revised Feb 2022.
• Oscar Claveria & Enric Monte & Petar Soric & Salvador Torra, 2022, ""An application of deep learning for exchange rate forecasting"," IREA Working Papers, University of Barcelona, Research Institute of Applied Economics, number 202201, Jan, revised Jan 2022.
• Bryan T. Kelly & Semyon Malamud & Kangying Zhou, 2021, "The Virtue of Complexity in Machine Learning Portfolios," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 21-90, Dec.
• Anthony Coache & Sebastian Jaimungal, 2021, "Reinforcement Learning with Dynamic Convex Risk Measures," Papers, arXiv.org, number 2112.13414, Dec, revised Nov 2022.
• Yuanlu Bai & Henry Lam & Svitlana Vyetrenko & Tucker Balch, 2021, "Efficient Calibration of Multi-Agent Simulation Models from Output Series with Bayesian Optimization," Papers, arXiv.org, number 2112.03874, Dec, revised Sep 2022.
• Linyi Yang & Jiazheng Li & Ruihai Dong & Yue Zhang & Barry Smyth, 2022, "NumHTML: Numeric-Oriented Hierarchical Transformer Model for Multi-task Financial Forecasting," Papers, arXiv.org, number 2201.01770, Jan.
• Xiao-Yang Liu & Jingyang Rui & Jiechao Gao & Liuqing Yang & Hongyang Yang & Zhaoran Wang & Christina Dan Wang & Jian Guo, 2021, "FinRL-Meta: A Universe of Near-Real Market Environments for Data-Driven Deep Reinforcement Learning in Quantitative Finance," Papers, arXiv.org, number 2112.06753, Dec, revised Mar 2022.
• Michele Azzone & Roberto Baviera, 2021, "A fast Monte Carlo scheme for additive processes and option pricing," Papers, arXiv.org, number 2112.08291, Dec, revised Jul 2023.
• Jiafeng Chen & Xiaohong Chen & Elie Tamer, 2021, "Efficient Estimation of Average Derivatives in NPIV Models: Simulation Comparisons of Neural Network Estimators," Cowles Foundation Discussion Papers, Cowles Foundation for Research in Economics, Yale University, number 2319, Dec.
• Igor Halperin & Jiayu Liu & Xiao Zhang, 2022, "Combining Reinforcement Learning and Inverse Reinforcement Learning for Asset Allocation Recommendations," Papers, arXiv.org, number 2201.01874, Jan.
• Wei Cao & Yun He & Wenjun Wang & Weidong Zhu & Yves Demazeau, 2021, "Ensemble methods for credit scoring of Chinese peer-to-peer loans," Post-Print, HAL, number hal-03434348, DOI: 10.21314/JCR.2021.005.
• Item repec:hal:wpaper:hal-03498263 is not listed on IDEAS anymore

• Draca, Mirko & Schwarz, Carlo, 2021, "How Polarized are Citizens? Measuring Ideology from the Ground-Up," QAPEC Discussion Papers, Quantitative and Analytical Political Economy Research Centre, number 07.
• Toru Kitagawa & Guanyi Wang, 2021, "Who should get vaccinated? Individualized allocation of vaccines over SIR network," CeMMAP working papers, Centre for Microdata Methods and Practice, Institute for Fiscal Studies, number CWP28/21, Jul.
• Yiheng Sun & Tian Lu & Cong Wang & Yuan Li & Huaiyu Fu & Jingran Dong & Yunjie Xu, 2021, "TransBoost: A Boosting-Tree Kernel Transfer Learning Algorithm for Improving Financial Inclusion," Papers, arXiv.org, number 2112.02365, Dec, revised Dec 2021.
• Henning Tarp Jensen & Marcus Keogh-Brown & Finn Tarp, 2021, "Labour market projections and time allocation in Myanmar: Application of a new computable general equilibrium (CGE) model," WIDER Working Paper Series, World Institute for Development Economic Research (UNU-WIDER), number wp-2021-180.
• Kieran Wood & Sven Giegerich & Stephen Roberts & Stefan Zohren, 2021, "Trading with the Momentum Transformer: An Intelligent and Interpretable Architecture," Papers, arXiv.org, number 2112.08534, Dec, revised Nov 2022.
• Qinkai Chen & Christian-Yann Robert, 2021, "Multivariate Realized Volatility Forecasting with Graph Neural Network," Papers, arXiv.org, number 2112.09015, Dec, revised Dec 2021.
• Pietro Emilio Spini, 2021, "Robustness, Heterogeneous Treatment Effects and Covariate Shifts," Papers, arXiv.org, number 2112.09259, Dec, revised Aug 2024.
• Le, Tuan Anh & Dao, Thi Thanh Binh, 2021, "Portfolio optimization under mean-CVaR simulation with copulas on the Vietnamese stock exchange," MPRA Paper, University Library of Munich, Germany, number 111105.
• Laine, Tatu & Korpinen, Kasperi, 2021, "Measuring counterparty risk in FMIs," BoF Economics Review, Bank of Finland, number 9/2021.
• Li, Shiyuan & Hao, Miao, 2021, "Can Artificial Intelligence Reduce Regional Inequality? Evidence from China," MPRA Paper, University Library of Munich, Germany, number 110973, Oct.

Report NEP-CMP-2022-01-17

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: