Report NEP-BIG-2022-01-17

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:

• Gabriel Loumeau & Christian Stettler, 2021, "Fiscal Autonomy and Self-Determination," CESifo Working Paper Series, CESifo, number 9445.
• Dafei Yin & Jing Li & Gaosheng Wu, 2021, "Solving the Data Sparsity Problem in Predicting the Success of the Startups with Machine Learning Methods," Papers, arXiv.org, number 2112.07985, Dec.
• Benjamin Gardner & Chiara Scotti & Clara Vega, 2021, "Words Speak as Loudly as Actions: Central Bank Communication and the Response of Equity Prices to Macroeconomic Announcements," Finance and Economics Discussion Series, Board of Governors of the Federal Reserve System (U.S.), number 2021-074, Nov, DOI: 10.17016/FEDS.2021.074.
• Qinkai Chen & Christian-Yann Robert, 2021, "Multivariate Realized Volatility Forecasting with Graph Neural Network," Papers, arXiv.org, number 2112.09015, Dec, revised Dec 2021.
• Carlo Perroni & Kimberley Ann Scharf & Oleksandr Talavera & Linh Vi, 2021, "Does Online Salience Predict Charitable Giving? Evidence from SMS Text Donations," CESifo Working Paper Series, CESifo, number 9436.
• Jean-Sébastien Lacam & David Salvetat, 2021, "Big data and Smart data: two interdependent and synergistic digital policies within a virtuous data exploitation loop," Post-Print, HAL, number hal-03434863, DOI: 10.1016/j.hitech.2021.100406.
• Draca, Mirko & Schwarz, Carlo, 2021, "How Polarized are Citizens? Measuring Ideology from the Ground-Up," QAPEC Discussion Papers, Quantitative and Analytical Political Economy Research Centre, number 07.
• Lai Xinglin, 2021, "Modelling hetegeneous treatment effects by quantitle local polynomial decision tree and forest," Papers, arXiv.org, number 2111.15320, Nov, revised Mar 2022.
• Jiafeng Chen & Xiaohong Chen & Elie Tamer, 2021, "Efficient Estimation of Average Derivatives in NPIV Models: Simulation Comparisons of Neural Network Estimators," Cowles Foundation Discussion Papers, Cowles Foundation for Research in Economics, Yale University, number 2319, Dec.
• Montobbio, Fabio & Staccioli, Jacopo & Virgillito, Maria Enrica & Vivarelli, Marco, 2021, "Labour-Saving Automation and Occupational Exposure: A Text-Similarity Measure," IZA Discussion Papers, IZA Network @ LISER, number 14879, Dec.
• Aparna Keshaviah & Cindy Hu & Robert P. Lennon & Robbie Fraleigh & Lauren J. Van Scoy & Bethany L. Snyder & Erin L. Miller & William A. Calo & Aleksandra E. Zgierska & Christopher Griffin, , "Developing and Testing an Automated Qualitative Assistant (AQUA) to Support Qualitative Analysis," Mathematica Policy Research Reports, Mathematica Policy Research, number 27c5dbf3e4a04466902d35724.
• Bryan T. Kelly & Semyon Malamud & Kangying Zhou, 2021, "The Virtue of Complexity in Machine Learning Portfolios," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 21-90, Dec.
• Pietro Emilio Spini, 2021, "Robustness, Heterogeneous Treatment Effects and Covariate Shifts," Papers, arXiv.org, number 2112.09259, Dec, revised Aug 2024.
• Wei Cao & Yun He & Wenjun Wang & Weidong Zhu & Yves Demazeau, 2021, "Ensemble methods for credit scoring of Chinese peer-to-peer loans," Post-Print, HAL, number hal-03434348, DOI: 10.21314/JCR.2021.005.
• Schmidt, Lorenz & Odening, Martin & Ritter, Matthias, , "Estimation of the weather-yield nexus with Artificial Neural Networks," Land, Farm & Agribusiness Management Department, Harper Adams University, Land, Farm & Agribusiness Management Department, number 316598, DOI: 10.22004/ag.econ.316598.
• Hu, Junjie & Härdle, Wolfgang, 2021, "Networks of news and cross-sectional returns," IRTG 1792 Discussion Papers, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series", number 2021-023.
• Domonkos F. Vamossy & Rolf Skog, 2021, "EmTract: Extracting Emotions from Social Media," Papers, arXiv.org, number 2112.03868, Dec, revised Jun 2023.
• Item repec:hal:wpaper:hal-03498263 is not listed on IDEAS anymore

• Linyi Yang & Jiazheng Li & Ruihai Dong & Yue Zhang & Barry Smyth, 2022, "NumHTML: Numeric-Oriented Hierarchical Transformer Model for Multi-task Financial Forecasting," Papers, arXiv.org, number 2201.01770, Jan.
• Xiao-Yang Liu & Jingyang Rui & Jiechao Gao & Liuqing Yang & Hongyang Yang & Zhaoran Wang & Christina Dan Wang & Jian Guo, 2021, "FinRL-Meta: A Universe of Near-Real Market Environments for Data-Driven Deep Reinforcement Learning in Quantitative Finance," Papers, arXiv.org, number 2112.06753, Dec, revised Mar 2022.
• Jiequn Han & Yucheng Yang & Weinan E, 2021, "DeepHAM: A Global Solution Method for Heterogeneous Agent Models with Aggregate Shocks," Papers, arXiv.org, number 2112.14377, Dec, revised Feb 2022.
• Anthony Coache & Sebastian Jaimungal, 2021, "Reinforcement Learning with Dynamic Convex Risk Measures," Papers, arXiv.org, number 2112.13414, Dec, revised Nov 2022.
• Igor Halperin & Jiayu Liu & Xiao Zhang, 2022, "Combining Reinforcement Learning and Inverse Reinforcement Learning for Asset Allocation Recommendations," Papers, arXiv.org, number 2201.01874, Jan.
• Yiheng Sun & Tian Lu & Cong Wang & Yuan Li & Huaiyu Fu & Jingran Dong & Yunjie Xu, 2021, "TransBoost: A Boosting-Tree Kernel Transfer Learning Algorithm for Improving Financial Inclusion," Papers, arXiv.org, number 2112.02365, Dec, revised Dec 2021.
• Schmidt, Lorenz & Odening, Martin & Ritter, Matthias, , "Estimation of the weather-yield nexus with Artificial Neural Networks," Agri-Tech Economics Papers, Harper Adams University, Land, Farm & Agribusiness Management Department, number 316598, DOI: 10.22004/ag.econ.316598.
• Andrew Butler & Roy Kwon, 2021, "Efficient differentiable quadratic programming layers: an ADMM approach," Papers, arXiv.org, number 2112.07464, Dec.
• Anas Aboutaoufik, 2021, "Big data in Morocco's transport and logistics sector," Post-Print, HAL, number halshs-03266969, May, DOI: 10.21172/ijiet.192.03.
• Damir Filipović & Amir Khalilzadeh, 2021, "Machine Learning for Predicting Stock Return Volatility," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 21-95, Dec.
• Xiao Huang, 2021, "Lassoed Boosting and Linear Prediction in the Equities Market," Papers, arXiv.org, number 2112.08934, Dec, revised May 2024.
• Du, Qianqian & Mieno, Taro & Bullock, David & Edge, Brittani, , "Economically Optimal Nitrogen Side-dressing Based on Vegetation Indices from Satellite Images Through On-farm Experiments," Land, Farm & Agribusiness Management Department, Harper Adams University, Land, Farm & Agribusiness Management Department, number 316596, DOI: 10.22004/ag.econ.316596.
• Li, Shiyuan & Hao, Miao, 2021, "Can Artificial Intelligence Reduce Regional Inequality? Evidence from China," MPRA Paper, University Library of Munich, Germany, number 110973, Oct.
• Rangel González Erick & Llamosas-Rosas Irving, 2021, "Observing the Evolution of the Informal Sector from Space: A Municipal Approach 2013-2020," Working Papers, Banco de México, number 2021-18, Dec.
• Kieran Wood & Sven Giegerich & Stephen Roberts & Stefan Zohren, 2021, "Trading with the Momentum Transformer: An Intelligent and Interpretable Architecture," Papers, arXiv.org, number 2112.08534, Dec, revised Nov 2022.
• Oscar Claveria & Enric Monte & Petar Soric & Salvador Torra, 2022, ""An application of deep learning for exchange rate forecasting"," IREA Working Papers, University of Barcelona, Research Institute of Applied Economics, number 202201, Jan, revised Jan 2022.

Report NEP-BIG-2022-01-17

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: