Report NEP-CMP-2022-12-05

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:

• John, Otumu, 2022. "Hybrid Convolutional Neural Network Components," OSF Preprints 9xntm, Center for Open Science.
• Item repec:cte:wsrepe:36072 is not listed on IDEAS anymore

• Maciej Wysocki & Paweł Sakowski, 2022. "Investment Portfolio Optimization Based on Modern Portfolio Theory and Deep Learning Models," Working Papers 2022-12, Faculty of Economic Sciences, University of Warsaw.
• Dennis Kant & Andreas Pick & Jasper de Winter, 2022. "Nowcasting GDP using machine learning methods," Working Papers 754, DNB.
• Illia Baranochnikov & Robert Ślepaczuk, 2022. "A comparison of LSTM and GRU architectures with novel walk-forward approach to algorithmic investment strategy," Working Papers 2022-21, Faculty of Economic Sciences, University of Warsaw.
• von Zahn, Moritz & Bauer, Kevin & Mihale-Wilson, Cristina & Jagow, Johanna & Speicher, Max & Hinz, Oliver, 2022. "The smart green nudge: Reducing product returns through enriched digital footprints & causal machine learning," SAFE Working Paper Series 363, Leibniz Institute for Financial Research SAFE, revised 2022.
• Louis Geiler & Séverine Affeldt & Mohamed Nadif, 2022. "A survey on machine learning methods for churn prediction," Post-Print hal-03824873, HAL.
• Shang, Dawei, 2022. "Examining the influence of user engagement on tourist virtual reality behavioral response from the human-computer interaction perspective: A PLSSEM-IMP-NN hybrid machine learning approach," OSF Preprints hp259, Center for Open Science.
• Maximilian Andres & Lisa Bruttel & Jana Friedrichsen, 2022. "How Communication Makes the Difference between a Cartel and Tacit Collusion: A Machine Learning Approach," CESifo Working Paper Series 10024, CESifo.
• Francis X. Diebold & Maximilian Gobel & Philippe Goulet Coulombe, 2022. "Assessing and Comparing Fixed-Target Forecasts of Arctic Sea Ice:Glide Charts for Feature-Engineered Linear Regression and Machine Learning Models," PIER Working Paper Archive 22-028, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
• Wei Li & Wolfgang Karl Hardle & Stefan Lessmann, 2022. "A Data-driven Case-based Reasoning in Bankruptcy Prediction," Papers 2211.00921, arXiv.org.
• Yugo Fujimoto & Kei Nakagawa & Kentaro Imajo & Kentaro Minami, 2022. "Uncertainty Aware Trader-Company Method: Interpretable Stock Price Prediction Capturing Uncertainty," Papers 2210.17030, arXiv.org, revised Nov 2022.
• Katarzyna Kryńska & Robert Ślepaczuk, 2022. "Daily and intraday application of various architectures of the LSTM model in algorithmic investment strategies on Bitcoin and the S&P 500 Index," Working Papers 2022-25, Faculty of Economic Sciences, University of Warsaw.
• Metz-Peeters, Maike, 2023. "The Effects of Mandatory Speed Limits on Crash Frequency - A Causal Machine Learning Approach," Ruhr Economic Papers 982, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen, revised 2023.
• Susan Athey & Dean Karlan & Emil Palikot & Yuan Yuan, 2022. "Smiles in Profiles: Improving Fairness and Efficiency Using Estimates of User Preferences in Online Marketplaces," NBER Working Papers 30633, National Bureau of Economic Research, Inc.
• Reza Bradrania & Davood Pirayesh Neghab, 2022. "State-dependent Asset Allocation Using Neural Networks," Papers 2211.00871, arXiv.org.
• Maximilien Germain & Huyên Pham & Xavier Warin, 2022. "A level-set approach to the control of state-constrained McKean-Vlasov equations: application to renewable energy storage and portfolio selection," Post-Print hal-03498263, HAL.
• Tristan Lim, 2022. "Predictive Crypto-Asset Automated Market Making Architecture for Decentralized Finance using Deep Reinforcement Learning," Papers 2211.01346, arXiv.org, revised Jan 2023.
• Richard Post & Isabel van den Heuvel & Marko Petkovic & Edwin van den Heuvel, 2022. "Flexible machine learning estimation of conditional average treatment effects: a blessing and a curse," Papers 2210.16547, arXiv.org, revised Jul 2023.
• Christoph Graf & Federico Quaglia & Frank A. Wolak, 2022. "(Machine) Learning from the COVID-19 Lockdown about Electricity Market Performance with a Large Share of Renewables," Papers 2211.02196, arXiv.org.
• Ruochen Xiao & Qiaochu Feng & Ruxin Deng, 2022. "Inflexible Multi-Asset Hedging of incomplete market," Papers 2211.00948, arXiv.org, revised May 2023.
• Juhász, Réka & Lane, Nathaniel & Oehlsen, Emily & Pérez, Verónica C., 2022. "The Who, What, When, and How of Industrial Policy: A Text-Based Approach," SocArXiv uyxh9, Center for Open Science.
• , SHANIMON S Dr & Mathew, Seena Mary, 2022. "Application Of Artificial Intelligence In Banking: A Study Based On Sbi-Sia Virtual Assistant," SocArXiv gkxh8, Center for Open Science.
• Bingyan Han, 2022. "Can maker-taker fees prevent algorithmic cooperation in market making?," Papers 2211.00496, arXiv.org.
• Ala-Mantila, Sanna & Kurvinen, Antti & Karhula, Aleksi, 2022. "Measuring sustainable urban development using novel neighborhood classification," SocArXiv vw9pb, Center for Open Science.
• Imed Boughzala & Nesrine Ben Yahia & Narjès Bellamine Ben Saoud & Wissem Eljaoued, 2022. "Shape it better than skip it: mapping the territory of quantum computing and its transformative potential," Post-Print hal-03825319, HAL.