Report NEP-BIG-2024-09-02

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:

• Bonelli, Maxime, 2023. "Data-driven Investors," HEC Research Papers Series 1470, HEC Paris.
• Felix Drinkall & Janet B. Pierrehumbert & Stefan Zohren, 2024. "Forecasting Credit Ratings: A Case Study where Traditional Methods Outperform Generative LLMs," Papers 2407.17624, arXiv.org, revised Jan 2025.
• Melissa Dell, 2024. "Deep Learning for Economists," Papers 2407.15339, arXiv.org, revised Nov 2024.
• Xiaohui Victor Li & Francesco Sanna Passino, 2024. "FinDKG: Dynamic Knowledge Graphs with Large Language Models for Detecting Global Trends in Financial Markets," Papers 2407.10909, arXiv.org, revised Oct 2024.
• Liyang Wang & Yu Cheng & Xingxin Gu & Zhizhong Wu, 2024. "Design and Optimization of Big Data and Machine Learning-Based Risk Monitoring System in Financial Markets," Papers 2407.19352, arXiv.org.
• Patrick Rehill, 2024. "Distilling interpretable causal trees from causal forests," Papers 2408.01023, arXiv.org.
• Fernando Berzal & Alberto Garcia, 2024. "Beyond Trend Following: Deep Learning for Market Trend Prediction," Papers 2407.13685, arXiv.org.
• Han Gui, 2024. "Machine learning in weekly movement prediction," Papers 2407.09831, arXiv.org.
• Hurlin, Christophe & Pérignon, Christophe, 2023. "Machine Learning and IRB Capital Requirements: Advantages, Risks, and Recommendations," HEC Research Papers Series 1480, HEC Paris.
• Chunhui Qiao & Xiangwei Wan, 2024. "Enhancing Black-Scholes Delta Hedging via Deep Learning," Papers 2407.19367, arXiv.org, revised Aug 2024.
• Chen Zhang & Giovanni Amici & Marco Morandotti, 2024. "Calibrating the Heston model with deep differential networks," Papers 2407.15536, arXiv.org, revised Jan 2025.
• Siqiao Zhao & Zhikang Dong & Zeyu Cao & Raphael Douady, 2024. "Hedge Fund Portfolio Construction Using PolyModel Theory and iTransformer," Papers 2408.03320, arXiv.org, revised Aug 2024.
• Atin Aboutorabi & Ga'etan de Rassenfosse, 2024. "Nowcasting R&D Expenditures: A Machine Learning Approach," Papers 2407.11765, arXiv.org.
• A Samuel Pottinger & Lawson Connor & Brookie Guzder-Williams & Maya Weltman-Fahs & Nick Gondek & Timothy Bowles, 2024. "Climate-Driven Doubling of U.S. Maize Loss Probability: Interactive Simulation with Neural Network Monte Carlo," Papers 2408.02217, arXiv.org, revised Dec 2024.
• Nacira Agram & Bernt {O}ksendal & Jan Rems, 2024. "Deep learning for quadratic hedging in incomplete jump market," Papers 2407.13688, arXiv.org.
• Yuxin Liu & Jimin Lin & Achintya Gopal, 2024. "NeuralBeta: Estimating Beta Using Deep Learning," Papers 2408.01387, arXiv.org, revised Oct 2024.
• Zijie Pan & Stepan Gordeev & Jiahui Zhao & Ziyi Meng & Caiwen Ding & Sandro Steinbach & Dongjin Song, 2024. "International Trade Flow Prediction with Bilateral Trade Provisions," Papers 2407.13698, arXiv.org.
• Flora Lutz & Yuanchen Yang & Chengyu Huang, 2024. "Public Perceptions of Canada’s Investment Climate," IMF Working Papers 2024/165, International Monetary Fund.
• Adam Bahelka & Harmen de Weerd, 2024. "Comparative analysis of Mixed-Data Sampling (MIDAS) model compared to Lag-Llama model for inflation nowcasting," Papers 2407.08510, arXiv.org.
• Aditya Saxena & Dr Parizad Dungore, 2024. "Credit Risk Assessment Model for UAE Commercial Banks: A Machine Learning Approach," Papers 2407.12044, arXiv.org.
• Lionel Fontagn'e & Francesca Micocci & Armando Rungi, 2024. "The heterogeneous impact of the EU-Canada agreement with causal machine learning," Papers 2407.07652, arXiv.org, revised Jul 2024.
• Alireza Mohammadshafie & Akram Mirzaeinia & Haseebullah Jumakhan & Amir Mirzaeinia, 2024. "Deep Reinforcement Learning Strategies in Finance: Insights into Asset Holding, Trading Behavior, and Purchase Diversity," Papers 2407.09557, arXiv.org.
• C'esar Pedrosa Soares, 2024. "Leveraging Natural Language and Item Response Theory Models for ESG Scoring," Papers 2407.20377, arXiv.org.
• Yuan Li & Bingqiao Luo & Qian Wang & Nuo Chen & Xu Liu & Bingsheng He, 2024. "A Reflective LLM-based Agent to Guide Zero-shot Cryptocurrency Trading," Papers 2407.09546, arXiv.org.
• Qiqin Zhou, 2024. "Explainable AI in Request-for-Quote," Papers 2407.15038, arXiv.org.
• Andres, Raphaela & Niebel, Thomas & Sack, Robin, 2024. "Big data and firm-level productivity: A cross-country comparison," ZEW Discussion Papers 24-053, ZEW - Leibniz Centre for European Economic Research.
• Mingshu Li & Bhaskarjit Sarmah & Dhruv Desai & Joshua Rosaler & Snigdha Bhagat & Philip Sommer & Dhagash Mehta, 2024. "Quantile Regression using Random Forest Proximities," Papers 2408.02355, arXiv.org.
• Preetha Saha & Jingrao Lyu & Dhruv Desai & Rishab Chauhan & Jerinsh Jeyapaulraj & Philip Sommer & Dhagash Mehta, 2024. "Machine Learning-based Relative Valuation of Municipal Bonds," Papers 2408.02273, arXiv.org.