Report NEP-BIG-2022-08-15

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:

• Jeonggil Song, 2022, "Predicting Economic Welfare with Images on Wealth," Papers, arXiv.org, number 2206.14810, Jun.
• Yuta Kuroda & Takeru Sugasawa, 2022, "The value of scattered greenery in urban areas: A hedonic analysis in Japan," DSSR Discussion Papers, Graduate School of Economics and Management, Tohoku University, number 128, Jul.
• Nelson P. Rayl & Nitish R. Sinha, 2022, "Integrating Prediction and Attribution to Classify News," Finance and Economics Discussion Series, Board of Governors of the Federal Reserve System (U.S.), number 2022-042, Jul, DOI: 10.17016/FEDS.2022.042.
• Weilong Fu & Ali Hirsa, 2022, "Solving barrier options under stochastic volatility using deep learning," Papers, arXiv.org, number 2207.00524, Jul.
• Zöll, Anne & Eitle, Verena & Buxmann, Peter, 2022, "Machine Learning Adoption based on the TOE Framework: A Quantitative Study," Publications of Darmstadt Technical University, Institute for Business Studies (BWL), Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL), number 133079, Jul.
• Matthew F. Dixon & Nicholas G. Polson & Kemen Goicoechea, 2022, "Deep Partial Least Squares for Empirical Asset Pricing," Papers, arXiv.org, number 2206.10014, Jun.
• Eleanor Loh & Jalaj Khandelwal & Brian Regan & Duncan A. Little, 2022, "Promotheus: An End-to-End Machine Learning Framework for Optimizing Markdown in Online Fashion E-commerce," Papers, arXiv.org, number 2207.01137, Jul, revised Aug 2022.
• Marta Candeias & Nuno Boavida & António Brandão Moniz, 2022, "Automation trends in Portugal: implications in productivity and employment," GEE Papers, Gabinete de Estratégia e Estudos, Ministério da Economia, number 0165, Jun, revised Jun 2022.
• Duan, Dinglin & Gao, Zhifeng & Uddin, Md Azhar & Nian, Yefan & Nguyen, Ly, 2022, "Tracing the Trends in Consumer Preferences for Eco-labeled Food: A Text Mining and Topic Modeling Approach," 2022 Annual Meeting, July 31-August 2, Anaheim, California, Agricultural and Applied Economics Association, number 322419, Aug, DOI: 10.22004/ag.econ.322419.
• Sander Sõna & Jaan Masso & Shakshi Sharma & Priit Vahter & Rajesh Sharma, 2022, "Predicting Company Innovativeness By Analysing The Website Data Of Firms: A Comparison Across Different Types Of Innovation," University of Tartu - Faculty of Economics and Business Administration Working Paper Series, Faculty of Economics and Business Administration, University of Tartu (Estonia), number 143.
• Kailai Wang & Xize Wang, 2022, "Generational Differences in Automobility: Comparing America's Millennials and Gen Xers Using Gradient Boosting Decision Trees," Papers, arXiv.org, number 2206.11056, Jun.
• TANGI Luca & VAN NOORDT Colin & COMBETTO Marco & GATTWINKEL Dietmar & PIGNATELLI Francesco, 2022, "AI Watch. European landscape on the use of Artificial Intelligence by the Public Sector," JRC Research Reports, Joint Research Centre, number JRC129301, Jun.
• Anthony Coache & Sebastian Jaimungal & 'Alvaro Cartea, 2022, "Conditionally Elicitable Dynamic Risk Measures for Deep Reinforcement Learning," Papers, arXiv.org, number 2206.14666, Jun, revised May 2023.
• Yanwei Jia & Xun Yu Zhou, 2022, "q-Learning in Continuous Time," Papers, arXiv.org, number 2207.00713, Jul, revised May 2025.
• CHARISI Vasiliki & CHAUDRON Stephane & DI GIOIA Rosanna & VUORIKARI Riina & ESCOBAR PLANAS Marina & SANCHEZ MARTIN Jose Ignacio & GOMEZ GUTIERREZ Emilia, 2022, "Artificial Intelligence and the Rights of the Child: Towards an Integrated Agenda for Research and Policy," JRC Research Reports, Joint Research Centre, number JRC127564, Jun.
• Mark Joseph Bennett, 2022, "Accelerating Machine Learning Training Time for Limit Order Book Prediction," Papers, arXiv.org, number 2206.09041, Jun.
• MANZONI Marina & MEDAGLIA Rony & TANGI Luca & VAN NOORDT Colin & VACCARI Lorenzino & GATTWINKEL Dietmar, 2022, "AI Watch Road to the adoption of Artificial Intelligence by the Public Sector: A Handbook for Policymakers, Public Administrations and Relevant Stakeholders," JRC Research Reports, Joint Research Centre, number JRC129100, Jun.
• Cao, An N.Q. & Gebrekidan, Bisrat Haile & Heckelei, Thomas & Robe, Michel A., 2022, "County-level USDA Crop Progress and Condition data, machine learning, and commodity market surprises," 2022 Annual Meeting, July 31-August 2, Anaheim, California, Agricultural and Applied Economics Association, number 322281, Aug, DOI: 10.22004/ag.econ.322281.
• Jordan Vazquez & Cécile Godé & Jean-Fabrice Lebraty, 2022, "Situational awareness in big data environment: Insights from French Police decision makers," Post-Print, HAL, number hal-03678829, Jun.
• Weronika Ormaniec & Marcin Pitera & Sajad Safarveisi & Thorsten Schmidt, 2022, "Estimating value at risk: LSTM vs. GARCH," Papers, arXiv.org, number 2207.10539, Jul.
• Jonghun Kwak & Jungyu Ahn & Jinho Lee & Sungwoo Park, 2022, "Shai-am: A Machine Learning Platform for Investment Strategies," Papers, arXiv.org, number 2207.00436, Jul.
• Item repec:frz:wpmmos:wp2022_03.rdf is not listed on IDEAS anymore

• Rui OTA & Arata ITO & Masahiro SATO & Makoto YANO, 2022, "Social Learning and Behavioral Change When Faced with the COVID-19 Pandemic: A big data analysis," Discussion papers, Research Institute of Economy, Trade and Industry (RIETI), number 22065, Jul.
• Vetter, Oliver A. & Hoffmann, Felix & Pumplun, Luisa & Buxmann, Peter, 2022, "What constitutes a machine-learning-driven business model? A taxonomy of B2B start-ups with machine learning at their core," Publications of Darmstadt Technical University, Institute for Business Studies (BWL), Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL), number 133080, Jun.
• Thibaut Plassot & Isidro Soloaga & Pedro J. Torres, 2022, "A Random Forest approach of the Evolution of Inequality of Opportunity in Mexico," Working Papers, ECINEQ, Society for the Study of Economic Inequality, number 614, Jun.
• Rawal, Niyati & Stock-Homburg, Ruth, 2022, "Facial Emotion Expressions in Human–Robot Interaction: A Survey," Publications of Darmstadt Technical University, Institute for Business Studies (BWL), Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL), number 133073, Jun, DOI: 10.1007/s12369-022-00867-0.
• HRADEC Jiri & CRAGLIA Massimo & DI LEO Margherita & DE NIGRIS Sarah & OSTLAENDER Nicole & NICHOLSON Nicholas, 2022, "Multipurpose synthetic population for policy applications," JRC Research Reports, Joint Research Centre, number JRC128595, Jun.
• Item repec:cam:camjip:2213 is not listed on IDEAS anymore

• Jinho Lee & Sungwoo Park & Jungyu Ahn & Jonghun Kwak, 2022, "ETF Portfolio Construction via Neural Network trained on Financial Statement Data," Papers, arXiv.org, number 2207.01187, Jul.
• Villacis, Alexis & Badruddoza, Syed & Mayorga, Joaquin & Mishra, Ashok K., 2022, "Using Machine Learning to Test the Consistency of Food Insecurity Measures," 2022 Annual Meeting, July 31-August 2, Anaheim, California, Agricultural and Applied Economics Association, number 322472, Aug, DOI: 10.22004/ag.econ.322472.
• In-Koo Cho & Jonathan Libgober, 2022, "Learning Underspecified Models," Papers, arXiv.org, number 2207.10140, Jul.
• Alcántara Mata, Antonio & Ruiz Mora, Carlos, 2022, "On data-driven chance constraint learning for mixed-integer optimization problems," DES - Working Papers. Statistics and Econometrics. WS, Universidad Carlos III de Madrid. Departamento de Estadística, number 35425, Jul.
• Yichen Feng & Ming Min & Jean-Pierre Fouque, 2022, "Deep Learning for Systemic Risk Measures," Papers, arXiv.org, number 2207.00739, Jul.
• Syed Abul, Basher & Salim, Rashid & Mohammad Riad, Uddin, 2022, "Regional Convergence in Bangladesh using Night Lights," MPRA Paper, University Library of Munich, Germany, number 113394, Jun.
• Alessandro Danovi & Marzio Roma & Davide Meloni & Stefano Olgiati & Fernando Metelli, 2022, "Baseline validation of a bias-mitigated loan screening model based on the European Banking Authority's trust elements of Big Data & Advanced Analytics applications using Artificial Intelligence," Papers, arXiv.org, number 2206.08938, Jun.
• Zhijie Zhang, 2022, "Identify Arbitrage Using Machine Learning on Multi-stock Pair Trading Price Forecasting," DSSR Discussion Papers, Graduate School of Economics and Management, Tohoku University, number 127, Jul.
• Chopard, Bertrand & Musy, Olivier, 2022, "Market for Artificial Intelligence in Health Care and Compensation for Medical Errors," MPRA Paper, University Library of Munich, Germany, number 113328, Jun.
• Francis X. Diebold & Maximilian Goebel & 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," Papers, arXiv.org, number 2206.10721, Jun, revised Jun 2023.
• Jun-Cheng Chen & Cong-Xiao Chen & Li-Juan Duan & Zhi Cai, 2022, "DDPG based on multi-scale strokes for financial time series trading strategy," Papers, arXiv.org, number 2207.10071, Jun.
• Jyldyz Djumalieva & Stef Garasto & Cath Sleeman, 2020, "Evaluating a new earnings indicator. Can we improve the timeliness of existing statistics on earnings by using salary information from online job adverts?," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers, Economic Statistics Centre of Excellence (ESCoE), number ESCoE DP-2020-19, Dec.
• Item repec:hal:wpaper:hal-03716692 is not listed on IDEAS anymore

Report NEP-BIG-2022-08-15

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: