Report NEP-BIG-2022-01-10

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

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Other reports in NEP-BIG

The following items were announced in this report:

• Chris Redl & Sandile Hlatshwayo, 2021. "Forecasting Social Unrest: A Machine Learning Approach," IMF Working Papers 2021/263, International Monetary Fund.
• Leogrande, Angelo & Costantiello, Alberto & Laureti, Lucio & Leogrande, Domenico, 2021. "The Determinants of Design Applications in Europe," MPRA Paper 110836, University Library of Munich, Germany.
• Paolo Brunori & Apostolos Davillas & Andrew Jones & Giovanna Scarchilli, 2021. "Model-based Recursive Partitioning to Estimate Unfair Health Inequalities in the United Kingdom Household Longitudinal Study," Working Papers 596, ECINEQ, Society for the Study of Economic Inequality.
• Ashish Kumar & Abeer Alsadoon & P. W. C. Prasad & Salma Abdullah & Tarik A. Rashid & Duong Thu Hang Pham & Tran Quoc Vinh Nguyen, 2021. "Generative Adversarial Network (GAN) and Enhanced Root Mean Square Error (ERMSE): Deep Learning for Stock Price Movement Prediction," Papers 2112.03946, arXiv.org.
• Carl Remlinger & Bri`ere Marie & Alasseur Cl'emence & Joseph Mikael, 2021. "Expert Aggregation for Financial Forecasting," Papers 2111.15365, arXiv.org, revised Jul 2023.
• Shujian Liao & Jian Chen & Hao Ni, 2021. "Forex Trading Volatility Prediction using Neural Network Models," Papers 2112.01166, arXiv.org, revised Dec 2021.
• Leonardo Perotti & Lech A. Grzelak, 2021. "Fast Sampling from Time-Integrated Bridges using Deep Learning," Papers 2111.13901, arXiv.org.
• Peng Zhou & Jingling Tang, 2021. "Improved Method of Stock Trading under Reinforcement Learning Based on DRQN and Sentiment Indicators ARBR," Papers 2111.15356, arXiv.org.
• Adam N. Smith & Stephan Seiler & Ishant Aggarwal, 2021. "Optimal Price Targeting," CESifo Working Paper Series 9439, CESifo.
• Easaw, Joshy & Fang, Yongmei & Heravi, Saeed, 2021. "Using Polls to Forecast Popular Vote Share for US Presidential Elections 2016 and 2020: An Optimal Forecast Combination Based on Ensemble Empirical Model," Cardiff Economics Working Papers E2021/34, Cardiff University, Cardiff Business School, Economics Section.
• Louis Abraham, 2021. "Competition analysis on the over-the-counter credit default swap market," Working Papers hal-03454808, HAL.
• Kitova, Olga & Savinova, Victoria, 2021. "Development of an Ensemble of Models for Predicting Socio-Economic Indicators of the Russian Federation using IRT-Theory and Bagging Methods," MPRA Paper 110824, University Library of Munich, Germany.
• Ben Hambly & Renyuan Xu & Huining Yang, 2021. "Recent Advances in Reinforcement Learning in Finance," Papers 2112.04553, arXiv.org, revised Feb 2023.
• Tomás Marinozzi & Leandro Nallar & Sergio Pernice, 2021. "Intuitive Mathematical Economics Series. General Equilibrium Models and the Gradient Field Method," CEMA Working Papers: Serie Documentos de Trabajo. 820, Universidad del CEMA.
• Jianian Wang & Sheng Zhang & Yanghua Xiao & Rui Song, 2021. "A Review on Graph Neural Network Methods in Financial Applications," Papers 2111.15367, arXiv.org, revised Apr 2022.
• Ake-Kob, Alin & Blazeviciene, Aurelija & Colonna, Liane & Cartolovni, Anto & Dantas, Carina & Fedosov, Anton & Florez-Revuelta, Francisco & Fosch-Villaronga, Eduard & He, Zhicheng & Klimczuk, Andrzej , 2021. "State of the art on ethical, legal, and social issues linked to audio- and video-based AAL solutions," EconStor Research Reports 248470, ZBW - Leibniz Information Centre for Economics.
• Victor Duarte & Julia Fonseca & Aaron S. Goodman & Jonathan A. Parker, 2021. "Simple Allocation Rules and Optimal Portfolio Choice Over the Lifecycle," NBER Working Papers 29559, National Bureau of Economic Research, Inc.
• Rangan Gupta & Sayar Karmakar & Christian Pierdzioch, 2022. "Safe Havens, Machine Learning, and the Sources of Geopolitical Risk: A Forecasting Analysis Using Over a Century of Data," Working Papers 202201, University of Pretoria, Department of Economics.
• Uta Pigorsch & Sebastian Schafer, 2021. "High-Dimensional Stock Portfolio Trading with Deep Reinforcement Learning," Papers 2112.04755, arXiv.org.
• Emmanuel Okamba, 2022. "Travailleur du savoir et risque d'intolérance sensorielle lié à l'interaction homme-machine intelligente," Working Papers hal-03453843, HAL.
• Timothy Holt & Mitsuru Igami & Simon Scheidegger, 2021. "Detecting Edgeworth Cycles," Cahiers de Recherches Economiques du Département d'économie 21.16, Université de Lausanne, Faculté des HEC, Département d’économie.
• Fabio Montobbio & Jacopo Staccioli & Maria Enrica Virgillito & Marco Vivarelli, 2021. "Labour-saving automation and occupational exposure: a text-similarity measure," DISCE - Quaderni del Dipartimento di Politica Economica dipe0021, Università Cattolica del Sacro Cuore, Dipartimenti e Istituti di Scienze Economiche (DISCE).
• Victor Chernozhukov & Carlos Cinelli & Whitney Newey & Amit Sharma & Vasilis Syrgkanis, 2021. "Long Story Short: Omitted Variable Bias in Causal Machine Learning," Papers 2112.13398, arXiv.org, revised May 2024.
• Item repec:bre:wpaper:46376 is not listed on IDEAS anymore

• Lorenz, Max & Reinhard, Patrick & Spring, Thomas, 2021. "Digitalization in MedTech: Understanding the Impact on Total Knee Arthroplasty," Working Paper Series in Health Economics, Management and Policy 2021-02, University of St.Gallen, School of Medicine, Chair of Health Economics, Policy and Management.
• Konrad Menzel, 2021. "Structural Sieves," Papers 2112.01377, arXiv.org, revised Apr 2022.
• Jean-David Fermanian & Dominique Guégan, 2021. "Fair learning with bagging," Documents de travail du Centre d'Economie de la Sorbonne 21034, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
• Shwai He & Shi Gu, 2021. "Multi-modal Attention Network for Stock Movements Prediction," Papers 2112.13593, arXiv.org, revised Oct 2022.
• Jelnov, Artyom & Jelnov, Pavel, 2021. "Vaccination Policy and Trust," GLO Discussion Paper Series 1003, Global Labor Organization (GLO).
• Mehmet Canayaz & Ilja Kantorovitch & Roxana Mihet, 2021. "Privacy Laws and Value of Personal Data," Swiss Finance Institute Research Paper Series 21-92, Swiss Finance Institute.