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Report NEP-CMP-2023-06-26
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:
- Sinan Deng & John Inekwe & Vladimir Smirnov & Andrew Wait & Chao Wang, 2023, "Machine Learning and Deep Learning Forecasts of Electricity Imbalance Prices," Working Papers, University of Sydney, School of Economics, number 2023-03, Jun.
- Jingjing Guo, 2023, "Gated Deeper Models are Effective Factor Learners," Papers, arXiv.org, number 2305.10693, May.
- Ludovic Gouden`ege & Andrea Molent & Antonino Zanette, 2023, "Backward Hedging for American Options with Transaction Costs," Papers, arXiv.org, number 2305.06805, May, revised Jun 2023.
- Khuc, Quy Van & Tran, Duc-Trung, 2023, "Contingent valuation machine learning (CVML): A novel method for estimating citizens’ willingness- to- pay for safer and cleaner environment," OSF Preprints, Center for Open Science, number r35bz, May, DOI: 10.31219/osf.io/r35bz.
- Masanori Hirano & Kentaro Imajo & Kentaro Minami & Takuya Shimada, 2023, "Efficient Learning of Nested Deep Hedging using Multiple Options," Papers, arXiv.org, number 2305.12264, May.
- Benjamin Fan & Edward Qiao & Anran Jiao & Zhouzhou Gu & Wenhao Li & Lu Lu, 2023, "Deep Learning for Solving and Estimating Dynamic Macro-Finance Models," Papers, arXiv.org, number 2305.09783, May.
- Michael Allan Ribers & Hannes Ullrich, 2023, "Machine learning and physician prescribing: a path to reduced antibiotic use," Berlin School of Economics Discussion Papers, Berlin School of Economics, number 0019, Jun, DOI: 10.48462/opus4-4976.
- Mollen, Anne & Hondrich, Lukas, 2023, "From risk mitigation to employee action along the machine learning pipeline: A paradigm shift in European regulatory perspectives on automated decision-making systems in the workplace," Working Paper Forschungsförderung, Hans-Böckler-Stiftung, Düsseldorf, number 278.
- Lavko, Matus & Klein, Tony & Walther, Thomas, 2023, "Reinforcement Learning and Portfolio Allocation: Challenging Traditional Allocation Methods," QBS Working Paper Series, Queen's University Belfast, Queen's Business School, number 2023/01, DOI: 10.2139/ssrn.4346043.
- Marcin Chlebus & Artur Nowak, 2023, "From Alchemy to Analytics: Unleashing the Potential of Technical Analysis in Predicting Noble Metal Price Movement," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2023-13.
- Pletcher, Scott Nicholas, 2023, "Practical and Ethical Perspectives on AI-Based Employee Performance Evaluation," OSF Preprints, Center for Open Science, number 29yej, Apr, DOI: 10.31219/osf.io/29yej.
- Petar Soric & Enric Monte & Salvador Torra & Oscar Claveria, 2022, "“Density forecasts of inflation using Gaussian process regression models”," AQR Working Papers, University of Barcelona, Regional Quantitative Analysis Group, number 202207, Jul, revised Jul 2022.
- Zacharia Issa & Blanka Horvath & Maud Lemercier & Cristopher Salvi, 2023, "Non-adversarial training of Neural SDEs with signature kernel scores," Papers, arXiv.org, number 2305.16274, May.
- Maximilian Ahrens & Deniz Erdemlioglu & Michael McMahon & Christopher J. Neely & Xiye Yang, 2023, "Mind Your Language: Market Responses to Central Bank Speeches," Working Papers, Federal Reserve Bank of St. Louis, number 2023-013, May, revised 28 Sep 2024, DOI: 10.20955/wp.2023.013.
- Aurélien Alfonsi & Bernard Lapeyre & Jérôme Lelong, 2023, "How many inner simulations to compute conditional expectations with least-square Monte Carlo?," Post-Print, HAL, number hal-03770051, Jun, DOI: 10.1007/s11009-023-10038-x.
- Liu, Weilong & Zhang, Yong & Liu, Kailong & Quinn, Barry & Yang, Xingyu & Peng, Qiao, 2023, "Evolutionary multi-objective optimisation for large-scale portfolio selection with both random and uncertain returns," QBS Working Paper Series, Queen's University Belfast, Queen's Business School, number 2023/02, DOI: 10.2139/ssrn.4376779.
- Abdulnasser Hatemi-J & Alan Mustafa, 2023, "A Simulation Package in VBA to Support Finance Students for Constructing Optimal Portfolios," Papers, arXiv.org, number 2305.12826, May.