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Report NEP-CMP-2021-04-05
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:
- Ariel Neufeld & Julian Sester, 2021, "A deep learning approach to data-driven model-free pricing and to martingale optimal transport," Papers, arXiv.org, number 2103.11435, Mar, revised Dec 2022.
- Huanming Zhang & Zhengyong Jiang & Jionglong Su, 2021, "A Deep Deterministic Policy Gradient-based Strategy for Stocks Portfolio Management," Papers, arXiv.org, number 2103.11455, Mar.
- Kollár, Aladár, 2021, "Betting models using AI: a review on ANN, SVM, and Markov chain," MPRA Paper, University Library of Munich, Germany, number 106821, Mar.
- Mohammadreza Ghanbari & Mahdi Goldani, 2021, "Support Vector Regression Parameters Optimization using Golden Sine Algorithm and its application in stock market," Papers, arXiv.org, number 2103.11459, Mar.
- Yiyan Huang & Cheuk Hang Leung & Qi Wu & Xing Yan, 2021, "Robust Orthogonal Machine Learning of Treatment Effects," Papers, arXiv.org, number 2103.11869, Mar, revised Dec 2022.
- Steve J. Bickley & Ho Fai Chan & Sascha L. Schmidt & Benno Torgler, 2021, "Quantum-Sapiens: The Quantum Bases for Human Expertise, Knowledge, and Problem-Solving (Extended Version with Applications)," CREMA Working Paper Series, Center for Research in Economics, Management and the Arts (CREMA), number 2021-14, Mar.
- Tomasz Antczak & Bartosz Skorupa & Mikolaj Szurlej & Rafal Weron & Jacek Zabawa, 2021, "Simulation modeling of epidemic risk in supermarkets: Investigating the impact of social distancing and checkout zone design," WORking papers in Management Science (WORMS), Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology, number WORMS/21/05, Mar.
- Aleksy Klimowicz & Krzysztof Spirzewski, 2021, "Concept of peer-to-peer lending and application of machine learning in credit scoring," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2021-04.
- Karush Suri & Xiao Qi Shi & Konstantinos Plataniotis & Yuri Lawryshyn, 2021, "TradeR: Practical Deep Hierarchical Reinforcement Learning for Trade Execution," Papers, arXiv.org, number 2104.00620, Feb.
- Mukul Jaggi & Priyanka Mandal & Shreya Narang & Usman Naseem & Matloob Khushi, 2021, "Text Mining of Stocktwits Data for Predicting Stock Prices," Papers, arXiv.org, number 2103.16388, Mar.
- Hamid Bekamiri & Daniel S. Hain & Roman Jurowetzki, 2021, "PatentSBERTa: A Deep NLP based Hybrid Model for Patent Distance and Classification using Augmented SBERT," Papers, arXiv.org, number 2103.11933, Mar, revised Oct 2021.
- Hans Genberg & Özer Karagedikli, 2021, "Machine Learning and Central Banks: Ready for Prime Time?," Working Papers, South East Asian Central Banks (SEACEN) Research and Training Centre, number wp43, Mar.
- Jay Cao & Jacky Chen & John Hull & Zissis Poulos, 2021, "Deep Learning for Exotic Option Valuation," Papers, arXiv.org, number 2103.12551, Mar, revised Sep 2021.
- Olivier Durand-Lasserve, 2021, "Policies to Nationalize the Private Sector Labor Force in a Matching Model with Public Jobs and Quotas," Discussion Papers, King Abdullah Petroleum Studies and Research Center, number ks--2021-dp05, Mar, DOI: 10.30573/KS--2021-DP05.
- Walid Matar, 2021, "Long-run Effects of Real-time Electricity Pricing in the Saudi Power Sector," Discussion Papers, King Abdullah Petroleum Studies and Research Center, number ks--2021-dp03, Mar, DOI: 10.30573/KS--2021-DP03.
- Q. Wang & Y. Zhou & J. Shen, 2021, "Intraday trading strategy based on time series and machine learning for Chinese stock market," Papers, arXiv.org, number 2103.13507, Mar.
- Hannes Mueller, 2021, "The Hard Problem of Prediction for Conflict Prevention," Working Papers, Barcelona School of Economics, number 1244, Mar.
- Seema Jayachandran & Monica Biradavolu & Jan Cooper, 2021, "Using Machine Learning and Qualitative Interviews to Design a Five-Question Women's Agency Index," NBER Working Papers, National Bureau of Economic Research, Inc, number 28626, Mar.
- Dave Cliff, 2021, "Parameterised-Response Zero-Intelligence Traders," Papers, arXiv.org, number 2103.11341, Mar, revised Apr 2023.
- Artur Sokolovsky & Luca Arnaboldi & Jaume Bacardit & Thomas Gross, 2021, "Volume-Centred Range Bars: Novel Interpretable Representation of Financial Markets Designed for Machine Learning Applications," Papers, arXiv.org, number 2103.12419, Mar, revised May 2022.
- Jay Cao & Jacky Chen & John Hull & Zissis Poulos, 2021, "Deep Hedging of Derivatives Using Reinforcement Learning," Papers, arXiv.org, number 2103.16409, Mar.
- Jon Ellingsen & Vegard H. Larsen & Leif Anders Thorsrud, 2020, "News media vs. FRED-MD for macroeconomic forecasting," Working Paper, Norges Bank, number 2020/14, Oct.
- Szekeres, Szabolcs, 2021, "Should CBA use descriptive or prescriptive discount rates? It should use both!," MPRA Paper, University Library of Munich, Germany, number 106029, Feb.
- Item repec:bge:wpaper:1245 is not listed on IDEAS anymore
- Victor DeMiguel & Javier Gil-Bazo & Francisco J. Nogales & André A. P. Santos, 2021, "Can machine learning help to select portfolios of mutual funds?," Economics Working Papers, Department of Economics and Business, Universitat Pompeu Fabra, number 1772, Mar.
- Hanjo Odendaal, 2021, "A machine learning approach to domain specific dictionary generation. An economic time series framework," Working Papers, Stellenbosch University, Department of Economics, number 06/2021.
- Shan Huang & Michael Allan Ribers & Hannes Ullrich, 2021, "The Value of Data for Prediction Policy Problems: Evidence from Antibiotic Prescribing," Discussion Papers of DIW Berlin, DIW Berlin, German Institute for Economic Research, number 1939.
- Jørgen Vitting Andersen & Andrzej Nowak, 2020, "Symmetry and financial Markets," Post-Print, HAL, number halshs-03048686, Jul.