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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 (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:
- 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, International Monetary Fund, number 2021/295, Dec.
- 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, International Monetary Fund, number 2021/293, Dec.
- 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, arXiv.org, number 2201.01163, Jan, revised Feb 2022.
- Martin, Ian W.R. & Nagel, Stefan, 2022, "Market efficiency in the age of big data," LSE Research Online Documents on Economics, London School of Economics and Political Science, LSE Library, number 112960, Jul.
- Luis Delgado & G'erald Gurtner & Tatjana Boli'c & Lorenzo Castelli, 2021, "Estimating economic severity of Air Traffic Flow Management regulations," Papers, arXiv.org, number 2112.11263, Dec.
- Yi Liang & James Unwin, 2021, "COVID-19 Forecasts via Stock Market Indicators," Papers, arXiv.org, number 2112.06393, Dec.
- 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, arXiv.org, number 2112.11059, Dec, revised Nov 2022.
- Guijin Son & Joocheol Kim, 2021, "Neural Networks for Delta Hedging," Papers, arXiv.org, number 2112.10084, Dec.
- Emerson Melo, 2021, "Learning in Random Utility Models Via Online Decision Problems," Papers, arXiv.org, number 2112.10993, Dec, revised Aug 2022.
- Miglo, Anton, 2022, "FinTech Development in Greater Manchester: An Overview," MPRA Paper, University Library of Munich, Germany, number 111348, Jan.
- Mohammad Mirbagherijam, 2021, "Housing Price Prediction Model Selection Based on Lorenz and Concentration Curves: Empirical Evidence from Tehran Housing Market," Papers, arXiv.org, number 2112.06192, Dec.
- Thibault Jaisson, 2021, "Deep differentiable reinforcement learning and optimal trading," Papers, arXiv.org, number 2112.02944, Dec, revised Apr 2022.
- Imryoung Jeong & Hyunjoo Yang, 2021, "Using maps to predict economic activity," Papers, arXiv.org, number 2112.13850, Dec, 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, Faculty of Economics, University of Cambridge, number 2202, Jan.
- Isaac Meza & Rahul Singh, 2021, "Nested Nonparametric Instrumental Variable Regression," Papers, arXiv.org, number 2112.14249, Dec, revised May 2025.
- Tobias Fissler & Michael Merz & Mario V. Wuthrich, 2021, "Deep Quantile and Deep Composite Model Regression," Papers, arXiv.org, number 2112.03075, Dec.
- Yanqing Ma & Carmine Ventre & Maria Polukarov, 2021, "Denoised Labels for Financial Time-Series Data via Self-Supervised Learning," Papers, arXiv.org, number 2112.10139, Dec.
- 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, arXiv.org, number 2112.02607, Dec.
- 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, Athens University of Economics and Business, number 2202, Jan.
- Thomas Mitterling & Katharina Fenz & Arturo Martinez Jr & Joseph Bulan & Mildred Addawe & Ron Lester Durante & Marymell Martillan, 2021, "Compiling Granular Population Data Using Geospatial Information," ADB Economics Working Paper Series, Asian Development Bank, number 643, Dec.
- Aleksandar Arandjelovi'c & Thorsten Rheinlander & Pavel V. Shevchenko, 2021, "Importance sampling for option pricing with feedforward neural networks," Papers, arXiv.org, number 2112.14247, Dec, revised Jun 2023.
- Laureti, Lucio & Costantiello, Alberto & Matarrese, Marco Maria & Leogrande, Angelo, 2022, "The Employment in Innovative Enterprises in Europe," MPRA Paper, University Library of Munich, Germany, number 111335, Jan.
- 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, National Bureau of Economic Research, Inc, number 29569, Dec.
- Andrew Butler & Roy H. Kwon, 2021, "Data-driven integration of norm-penalized mean-variance portfolios," Papers, arXiv.org, number 2112.07016, Dec, 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, Bank of Canada, number 22-1, Jan, DOI: 10.34989/swp-2022-1.
- Oscar Claveria & Enric Monte & Petar Soric & Salvador Torra, 2022, "“An application of deep learning for exchange rate forecasting”," AQR Working Papers, University of Barcelona, Regional Quantitative Analysis Group, number 202201, Jan, revised Jan 2022.