Report NEP-BIG-2022-01-24

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.

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

Other reports in NEP-BIG

The following items were announced in this report:

• Mr. Paul A Austin & Mr. Marco Marini & Alberto Sanchez & Chima Simpson-Bell & James Tebrake, 2021. "Using the Google Places API and Google Trends Data to Develop High Frequency Indicators of Economic Activity," IMF Working Papers 2021/295, International Monetary Fund.
• Narek Ghazaryan & Mr. Alexei Goumilevski & Mr. Joannes Mongardini & Aneta Radzikowski, 2021. "Another Piece of the Puzzle: Adding Swift Data on Documentary Collections to the Short-Term Forecast of World Trade," IMF Working Papers 2021/293, International Monetary Fund.
• Michael Curry & Alexander Trott & Soham Phade & Yu Bai & Stephan Zheng, 2022. "Analyzing Micro-Founded General Equilibrium Models with Many Agents using Deep Reinforcement Learning," Papers 2201.01163, arXiv.org, revised Feb 2022.
• Martin, Ian W.R. & Nagel, Stefan, 2022. "Market efficiency in the age of big data," LSE Research Online Documents on Economics 112960, London School of Economics and Political Science, LSE Library.
• Luis Delgado & G'erald Gurtner & Tatjana Boli'c & Lorenzo Castelli, 2021. "Estimating economic severity of Air Traffic Flow Management regulations," Papers 2112.11263, arXiv.org.
• Yi Liang & James Unwin, 2021. "COVID-19 Forecasts via Stock Market Indicators," Papers 2112.06393, arXiv.org.
• Maximilien Germain & Huy^en Pham & Xavier Warin, 2021. "A level-set approach to the control of state-constrained McKean-Vlasov equations: application to renewable energy storage and portfolio selection," Papers 2112.11059, arXiv.org, revised Nov 2022.
• Guijin Son & Joocheol Kim, 2021. "Neural Networks for Delta Hedging," Papers 2112.10084, arXiv.org.
• Emerson Melo, 2021. "Learning in Random Utility Models Via Online Decision Problems," Papers 2112.10993, arXiv.org, revised Aug 2022.
• Miglo, Anton, 2022. "FinTech Development in Greater Manchester: An Overview," MPRA Paper 111348, University Library of Munich, Germany.
• Mohammad Mirbagherijam, 2021. "Housing Price Prediction Model Selection Based on Lorenz and Concentration Curves: Empirical Evidence from Tehran Housing Market," Papers 2112.06192, arXiv.org.
• Thibault Jaisson, 2021. "Deep differentiable reinforcement learning and optimal trading," Papers 2112.02944, arXiv.org, revised Apr 2022.
• Imryoung Jeong & Hyunjoo Yang, 2021. "Using maps to predict economic activity," Papers 2112.13850, arXiv.org, revised Apr 2022.
• Debnath, R. & Bardhan, R. & Mohaddes, K. & Shah, D. U. & Ramage, M. H. & Alvarez, R. M., 2022. "People-centric Emission Reduction in Buildings: A Data-driven and Network Topology-based Investigation," Cambridge Working Papers in Economics 2202, Faculty of Economics, University of Cambridge.
• Isaac Meza & Rahul Singh, 2021. "Nested Nonparametric Instrumental Variable Regression: Long Term, Mediated, and Time Varying Treatment Effects," Papers 2112.14249, arXiv.org, revised Mar 2024.
• Tobias Fissler & Michael Merz & Mario V. Wuthrich, 2021. "Deep Quantile and Deep Composite Model Regression," Papers 2112.03075, arXiv.org.
• Yanqing Ma & Carmine Ventre & Maria Polukarov, 2021. "Denoised Labels for Financial Time-Series Data via Self-Supervised Learning," Papers 2112.10139, arXiv.org.
• Jacob Turton & Ali Kabiri & David Tuckett & Robert Elliott Smith & David P. Vinson, 2021. "Differentiating Approach and Avoidance from Traditional Notions of Sentiment in Economic Contexts," Papers 2112.02607, arXiv.org.
• Phoebe Koundouri & Nicolaos Theodossiou & Charalampos Stavridis & Stathis Devves & Angelos Plataniotis, 2022. "A methodology for linking the Energy-related Policies of the European Green Deal to the 17 SDGs using Machine Learning," DEOS Working Papers 2202, Athens University of Economics and Business.
• Mitterling, Thomas & Fenz, Katharina & Martinez Jr, Arturo & Bulan, Joseph & Addawe, Mildred & Durante, Ron Lester & Martillan, Marymell, 2021. "Compiling Granular Population Data Using Geospatial Information," ADB Economics Working Paper Series 643, Asian Development Bank.
• Aleksandar Arandjelovi'c & Thorsten Rheinlander & Pavel V. Shevchenko, 2021. "Importance sampling for option pricing with feedforward neural networks," Papers 2112.14247, arXiv.org, revised Jun 2023.
• Laureti, Lucio & Costantiello, Alberto & Matarrese, Marco Maria & Leogrande, Angelo, 2022. "The Employment in Innovative Enterprises in Europe," MPRA Paper 111335, University Library of Munich, Germany.
• Arman Khachiyan & Anthony Thomas & Huye Zhou & Gordon H. Hanson & Alex Cloninger & Tajana Rosing & Amit Khandelwal, 2021. "Using Neural Networks to Predict Micro-Spatial Economic Growth," NBER Working Papers 29569, National Bureau of Economic Research, Inc.
• Andrew Butler & Roy H. Kwon, 2021. "Data-driven integration of norm-penalized mean-variance portfolios," Papers 2112.07016, arXiv.org, revised Nov 2022.
• Thibaut Duprey & Daniel E. Rigobon & Philip Schnattinger & Artur Kotlicki & Soheil Baharian & T. R. Hurd, 2022. "Business Closures and (Re)Openings in Real Time Using Google Places," Staff Working Papers 22-1, Bank of Canada.
• Oscar Claveria & Enric Monte & Petar Soric & Salvador Torra, 2022. "“An application of deep learning for exchange rate forecasting”," AQR Working Papers 202201, University of Barcelona, Regional Quantitative Analysis Group, revised Jan 2022.