Report NEP-BIG-2022-12-05

This is the archive for NEP-BIG, a report on new working papers in the area of Big Data. Tom Coupé (Tom Coupe) issued this report. It is usually issued weekly.

Subscribe to this report: email, RSS, or Mastodon, or Bluesky.

Other reports in NEP-BIG

The following items were announced in this report:

• Lockwood, Ben & Porcelli, Francesco & Redoano, Michela & Schiavone, Antonio, 2022, "Does Data Disclosure Improve Local Government Performance? Evidence from Italian Municipalities," QAPEC Discussion Papers, Quantitative and Analytical Political Economy Research Centre, number 17.
• 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, National Bureau of Economic Research, Inc, number 30633, Nov.
• Dominik Peters & Lan Yu & Hau Chan & Edith Elkind, 2022, "Preferences Single-Peaked on a Tree: Multiwinner Elections and Structural Results," Post-Print, HAL, number hal-03834509, Jan, DOI: 10.1613/jair.1.12332.
• Wang, Kailai & Wang, Xize, 2021, "Generational Differences in Automobility: Comparing America's Millennials and Gen Xers Using Gradient Boosting Decision Trees," SocArXiv, Center for Open Science, number n3a9e, May, DOI: 10.31219/osf.io/n3a9e.
• Metz-Peeters, Maike, 2023, "The Effects of Mandatory Speed Limits on Crash Frequency - A Causal Machine Learning Approach," Ruhr Economic Papers, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen, number 982, revised 2023, DOI: 10.4419/96973147.
• Louis Geiler & Séverine Affeldt & Mohamed Nadif, 2022, "A survey on machine learning methods for churn prediction," Post-Print, HAL, number hal-03824873, DOI: 10.1007/s41060-022-00312-5.
• 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, arXiv.org, number 2210.16547, Oct, revised Jul 2023.
• Yugo Fujimoto & Kei Nakagawa & Kentaro Imajo & Kentaro Minami, 2022, "Uncertainty Aware Trader-Company Method: Interpretable Stock Price Prediction Capturing Uncertainty," Papers, arXiv.org, number 2210.17030, Oct, revised Nov 2022.
• Ziyu Wang & Yucen Luo & Yueru Li & Jun Zhu & Bernhard Scholkopf, 2022, "Spectral Representation Learning for Conditional Moment Models," Papers, arXiv.org, number 2210.16525, Oct, revised Dec 2022.
• Ruibo Chen & Wei Li & Zhiyuan Zhang & Ruihan Bao & Keiko Harimoto & Xu Sun, 2022, "Stock Trading Volume Prediction with Dual-Process Meta-Learning," Papers, arXiv.org, number 2211.01762, Oct.
• Tristan Lim, 2022, "Predictive Crypto-Asset Automated Market Making Architecture for Decentralized Finance using Deep Reinforcement Learning," Papers, arXiv.org, number 2211.01346, Sep, revised Jan 2023.
• 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, Leibniz Institute for Financial Research SAFE, number 363, revised 2022.
• Dennis Kant & Andreas Pick & Jasper de Winter, 2022, "Nowcasting GDP using machine learning methods," Working Papers, DNB, number 754, Nov.
• Cameron Gordon, 2022, "The Information Bottleneck Principle in Corporate Hierarchies," Papers, arXiv.org, number 2210.14861, Oct.
• Juhász, Réka & Lane, Nathaniel & Oehlsen, Emily & Pérez, Verónica C., 2022, "The Who, What, When, and How of Industrial Policy: A Text-Based Approach," SocArXiv, Center for Open Science, number uyxh9, Aug, DOI: 10.31219/osf.io/uyxh9.
• 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, arXiv.org, number 2211.02196, Nov.
• Wei Li & Wolfgang Karl Hardle & Stefan Lessmann, 2022, "A Data-driven Case-based Reasoning in Bankruptcy Prediction," Papers, arXiv.org, number 2211.00921, Nov.
• 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, CESifo, number 10024.
• Anubhav Sarkar & Swagata Chakraborty & Sohom Ghosh & Sudip Kumar Naskar, 2022, "Evaluating Impact of Social Media Posts by Executives on Stock Prices," Papers, arXiv.org, number 2211.01287, Oct, revised Dec 2022.
• Julia Bachtrögler-Unger & Mathias Dolls & Carla Krolage & Paul Schüle & Hannes Taubenböck & Matthias Weigand, 2022, "EU Cohesion Policy on the Ground: Analyzing Small-Scale Effects Using Satellite Data," CESifo Working Paper Series, CESifo, number 10056.
• Alcántara Mata, Antonio & Ruiz Mora, Carlos, 2022, "A Neural Network-Based Distributional Constraint Learning Methodology for Mixed-Integer Stochastic Optimization," DES - Working Papers. Statistics and Econometrics. WS, Universidad Carlos III de Madrid. Departamento de Estadística, number 36072, Nov.
• Illia Baranochnikov & Robert Ślepaczuk, 2022, "A comparison of LSTM and GRU architectures with novel walk-forward approach to algorithmic investment strategy," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2022-21.
• Miriam Hortas-Rico & Vicente Rios, 2022, "Does women´s political empowerment matter for income inequality?," Working Papers. Collection A: Public economics, governance and decentralization, Universidade de Vigo, GEN - Governance and Economics research Network, number 2206, Nov.
• Rian Dolphin & Barry Smyth & Ruihai Dong, 2022, "A Multimodal Embedding-Based Approach to Industry Classification in Financial Markets," Papers, arXiv.org, number 2211.06378, Nov.
• , SHANIMON S Dr & Mathew, Seena Mary, 2022, "Application Of Artificial Intelligence In Banking: A Study Based On Sbi-Sia Virtual Assistant," SocArXiv, Center for Open Science, number gkxh8, Jul, DOI: 10.31219/osf.io/gkxh8.
• Alvaro J. Riascos Villegas & Julian Chitiva & Carlos Salazar, 2022, "Detección de Anomalías y Poder de Mercado en el Sector Eléctrico Colombiano," Borradores de Economia, Banco de la Republica de Colombia, number 1217, Nov, DOI: 10.32468/be.1217.
• John, Otumu, 2022, "Hybrid Convolutional Neural Network Components," OSF Preprints, Center for Open Science, number 9xntm, Oct, DOI: 10.31219/osf.io/9xntm.
• Maciej Wysocki & Paweł Sakowski, 2022, "Investment Portfolio Optimization Based on Modern Portfolio Theory and Deep Learning Models," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2022-12.
• Victo José da Silva Neto & Tulio Chiarini & Leonardo Costa Ribeiro & Igor Santos Tupy, 2022, "The global geography of digital platforms: towards platforms international locational determinants," Textos para Discussão Cedeplar-UFMG, Cedeplar, Universidade Federal de Minas Gerais, number 650, Nov.
• Anders Christensen & Joel Ferguson & Sim'on Ram'irez Amaya, 2022, "Incorporating High-Frequency Weather Data into Consumption Expenditure Predictions," Papers, arXiv.org, number 2211.01406, Oct.
• 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, Center for Open Science, number hp259, Oct, DOI: 10.31219/osf.io/hp259.
• Reza Bradrania & Davood Pirayesh Neghab, 2022, "State-dependent Asset Allocation Using Neural Networks," Papers, arXiv.org, number 2211.00871, Nov.
• Kai Gehring & Joop Age Harm Adema & Panu Poutvaara, 2022, "Immigrant Narratives," CESifo Working Paper Series, CESifo, number 10026.
• 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, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, number 22-028, Jun.
• 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, number hal-03498263.
• Ruochen Xiao & Qiaochu Feng & Ruxin Deng, 2022, "Inflexible Multi-Asset Hedging of incomplete market," Papers, arXiv.org, number 2211.00948, Nov, revised May 2023.
• 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, Faculty of Economic Sciences, University of Warsaw, number 2022-25.
• International Monetary Fund, 2022, "Peru: Technical Assistance Report-Consumer Price Index Mission," IMF Staff Country Reports, International Monetary Fund, number 2022/332, Oct.

Report NEP-BIG-2022-12-05

This is the archive for NEP-BIG, a report on new working papers in the area of Big Data. Tom Coupé (Tom Coupe) issued this report. It is usually issued weekly.

Subscribe to this report: email, RSS, or Mastodon, or Bluesky.

Other reports in NEP-BIG

The following items were announced in this report: