Report NEP-BIG-2024-06-17

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:

• Rachel Soloveichik, 2024. "Studies on the Value of Data," BEA Papers 0124, Bureau of Economic Analysis.
• Kea Baret & Amélie Barbier-Gauchard & Theophilos Papadimitriou, 2023. "Forecasting the Stability and Growth Pact compliance using Machine Learning," Post-Print hal-03121966, HAL.
• Daniel de Souza Santos & Tiago Alessandro Espinola Ferreira, 2024. "Neural Network Learning of Black-Scholes Equation for Option Pricing," Papers 2405.05780, arXiv.org.
• Ariel Neufeld & Philipp Schmocker & Sizhou Wu, 2024. "Full error analysis of the random deep splitting method for nonlinear parabolic PDEs and PIDEs," Papers 2405.05192, arXiv.org, revised Sep 2024.
• G. Ibikunle & B. Moews & K. Rzayev, 2024. "Can machine learning unlock new insights into high-frequency trading?," Papers 2405.08101, arXiv.org.
• S. Borağan Aruoba & Thomas Drechsel, 2024. "Identifying Monetary Policy Shocks: A Natural Language Approach," NBER Working Papers 32417, National Bureau of Economic Research, Inc.
• Simone Brusatin & Tommaso Padoan & Andrea Coletta & Domenico Delli Gatti & Aldo Glielmo, 2024. "Simulating the Economic Impact of Rationality through Reinforcement Learning and Agent-Based Modelling," Papers 2405.02161, arXiv.org, revised Oct 2024.
• Rehse, Dominik & Valet, Sebastian & Walter, Johannes, 2024. "Using market design to improve red teaming of generative AI models," ZEW policy briefs 06/2024, ZEW - Leibniz Centre for European Economic Research.
• Xiaowei Chen & Hong Li & Yufan Lu & Rui Zhou, 2024. "Unveiling Nonlinear Dynamics in Catastrophe Bond Pricing: A Machine Learning Perspective," Papers 2405.00697, arXiv.org, revised Aug 2024.
• Tomaz Cajner & Leland D. Crane & Christopher J. Kurz & Norman J. Morin & Paul E. Soto & Betsy Vrankovich, 2024. "Manufacturing Sentiment: Forecasting Industrial Production with Text Analysis," Finance and Economics Discussion Series 2024-026, Board of Governors of the Federal Reserve System (U.S.).
• Tänzer, Alina, 2024. "The effectiveness of central bank purchases of long-term treasury securities: A neural network approach," IMFS Working Paper Series 204, Goethe University Frankfurt, Institute for Monetary and Financial Stability (IMFS).
• W. Benedikt Schmal, 2024. "Quantitative Tools for Time Series Analysis in Natural Language Processing: A Practitioners Guide," Papers 2404.18499, arXiv.org.
• Tian Tian & Liu Ze hui & Huang Zichen & Yubing Tang, 2024. "Enhancing Organizational Performance: Harnessing AI and NLP for User Feedback Analysis in Product Development," Papers 2405.04692, arXiv.org.
• Maria S. Mavillonio, 2024. "Textual Representation of Business Plans and Firm Success," Discussion Papers 2024/308, Dipartimento di Economia e Management (DEM), University of Pisa, Pisa, Italy.
• Chuanhao Li & Runhan Yang & Tiankai Li & Milad Bafarassat & Kourosh Sharifi & Dirk Bergemann & Zhuoran Yang, 2024. "STRIDE: A Tool-Assisted LLM Agent Framework for Strategic and Interactive Decision-Making," Cowles Foundation Discussion Papers 2393, Cowles Foundation for Research in Economics, Yale University.
• Xue Wen Tan & Stanley Kok, 2024. "Explainable Risk Classification in Financial Reports," Papers 2405.01881, arXiv.org, revised May 2024.
• Christian Peukert & Florian Abeillon & Jérémie Haese & Franziska Kaiser & Alexander Staub, 2024. "Strategic Behavior and AI Training Data," CESifo Working Paper Series 11099, CESifo.
• Sendhil Mullainathan & Ashesh Rambachan, 2024. "From Predictive Algorithms to Automatic Generation of Anomalies," NBER Working Papers 32422, National Bureau of Economic Research, Inc.
• Attila Sarkany & Lukas Janasek & Jozef Barunik, 2024. "Quantile Preferences in Portfolio Choice: A Q-DRL Approach to Dynamic Diversification," Working Papers IES 2024/21, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised May 2024.
• Nicholas Tenev, 2024. "De-Biasing Models of Biased Decisions: A Comparison of Methods Using Mortgage Application Data," Papers 2405.00910, arXiv.org.
• Sugat Chaturvedi & Kanika Mahajan & Zahra Siddique, 2023. "Using Domain-Specific Word Embeddings to Examine the Demand for Skills," Working Papers 107, Ashoka University, Department of Economics.
• Reilly Pickard & F. Wredenhagen & Y. Lawryshyn, 2024. "Optimizing Deep Reinforcement Learning for American Put Option Hedging," Papers 2405.08602, arXiv.org.
• Tian Tian & Jiahao Deng, 2024. "Unleashing the Power of AI: Transforming Marketing Decision-Making in Heavy Machinery with Machine Learning, Radar Chart Simulation, and Markov Chain Analysis," Papers 2405.01913, arXiv.org.
• Xiaoxuan Zhang & John Gibson, 2024. "Local economic effects of connecting to China's high-speed rail network: Evidence from spatial econometric models," Working Papers in Economics 24/03, University of Waikato.
• Ajit Desai & Anneke Kosse & Jacob Sharples, 2024. "Finding a Needle in a Haystack: A Machine Learning Framework for Anomaly Detection in Payment Systems," Staff Working Papers 24-15, Bank of Canada.
• Ali Mohammadjafari, 2024. "Comparative Study of Bitcoin Price Prediction," Papers 2405.08089, arXiv.org.
• Sylvain BARTHÉLÉMY & Virginie GAUTIER & Fabien RONDEAU, 2024. "Convolutional Neural Networks to signal currency crises: from the Asian financial crisis to the Covid crisis," Economics Working Paper Archive (University of Rennes & University of Caen) 2024-01, Center for Research in Economics and Management (CREM), University of Rennes, University of Caen and CNRS.
• Zhiyu Cao & Zachary Feinstein, 2024. "Large Language Model in Financial Regulatory Interpretation," Papers 2405.06808, arXiv.org, revised Jul 2024.
• Ashish Anil Pawar & Vishnureddy Prashant Muskawar & Ritesh Tiku, 2024. "Portfolio Management using Deep Reinforcement Learning," Papers 2405.01604, arXiv.org.
• Ajit Desai & Anneke Kosse & Jacob Sharples, 2024. "Finding a needle in a haystack: a machine learning framework for anomaly detection in payment systems," BIS Working Papers 1188, Bank for International Settlements.
• Vansh Murad Kalia, 2024. "Packing Peanuts: The Role Synthetic Data Can Play in Enhancing Conventional Economic Prediction Models," Papers 2405.07431, arXiv.org.
• Ge, S. & Li, S. & Linton, O. B. & Liu, W. & Su, W., 2024. "Should We Augment Large Covariance Matrix Estimation with Auxiliary Network Information?," Janeway Institute Working Papers 2416, Faculty of Economics, University of Cambridge.
• Reilly Pickard & Finn Wredenhagen & Julio DeJesus & Mario Schlener & Yuri Lawryshyn, 2024. "Hedging American Put Options with Deep Reinforcement Learning," Papers 2405.06774, arXiv.org.
• Disa M. Hynsjö & Luca Perdoni, 2024. "Mapping Out Institutional Discrimination: The Economic Effects of Federal “Redlining”," CESifo Working Paper Series 11098, CESifo.
• Theodoros Zafeiriou & Dimitris Kalles, 2024. "Comparative analysis of neural network architectures for short-term FOREX forecasting," Papers 2405.08045, arXiv.org.
• Serguei Maliar & Bernard Salanie, 2024. "Testing for Asymmetric Information in Insurance with Deep Learning," Papers 2404.18207, arXiv.org.
• Yusuke Narita & Kohei Yata, 2024. "Algorithm as Experiment: Machine Learning, Market Design, and Policy Eligibility Rules," Cowles Foundation Discussion Papers 2391, Cowles Foundation for Research in Economics, Yale University.
• Wang, Tengyao & Dobriban, Edgar & Gataric, Milana & Samworth, Richard J., 2024. "Sharp-SSL: selective high-dimensional axis-aligned random projections for semi-supervised learning," LSE Research Online Documents on Economics 122552, London School of Economics and Political Science, LSE Library.
• Lonjezo Sithole, 2024. "A Locally Robust Semiparametric Approach to Examiner IV Designs," Papers 2404.19144, arXiv.org.