Report NEP-BIG-2021-07-26

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:

• Juyong Lee & Youngsang Cho, 2021. "National-scale electricity peak load forecasting: Traditional, machine learning, or hybrid model?," Papers 2107.06174, arXiv.org.
• Angelo Garangau Menezes & Saulo Martiello Mastelini, 2021. "MegazordNet: combining statistical and machine learning standpoints for time series forecasting," Papers 2107.01017, arXiv.org.
• Sohrab Mokhtari & Kang K. Yen & Jin Liu, 2021. "Effectiveness of Artificial Intelligence in Stock Market Prediction based on Machine Learning," Papers 2107.01031, arXiv.org.
• Helmut Wasserbacher & Martin Spindler, 2021. "Machine Learning for Financial Forecasting, Planning and Analysis: Recent Developments and Pitfalls," Papers 2107.04851, arXiv.org.
• Priyank Sonkiya & Vikas Bajpai & Anukriti Bansal, 2021. "Stock price prediction using BERT and GAN," Papers 2107.09055, arXiv.org.
• Naudé, Wim & Bray, Amy & Lee, Celina, 2021. "Crowdsourcing Artificial Intelligence in Africa: Findings from a Machine Learning Contest," IZA Discussion Papers 14545, Institute of Labor Economics (IZA).
• Supriya Bajpai, 2021. "Application of deep reinforcement learning for Indian stock trading automation," Papers 2106.16088, arXiv.org.
• Dan Wang & Zhi Chen & Ionut Florescu, 2021. "A Sparsity Algorithm with Applications to Corporate Credit Rating," Papers 2107.10306, arXiv.org.
• Francesca Micocci & Armando Rungi, 2021. "Predicting Exporters with Machine Learning," Working Papers 03/2021, IMT School for Advanced Studies Lucca, revised Jul 2021.
• Cynthia Pagliaro & Dhagash Mehta & Han-Tai Shiao & Shaofei Wang & Luwei Xiong, 2021. "Investor Behavior Modeling by Analyzing Financial Advisor Notes: A Machine Learning Perspective," Papers 2107.05592, arXiv.org.
• Ren'e Carmona & Mathieu Lauri`ere, 2021. "Deep Learning for Mean Field Games and Mean Field Control with Applications to Finance," Papers 2107.04568, arXiv.org.
• Li, Wei & Paraschiv, Florentina & Sermpinis, Georgios, 2021. "A data-driven explainable case-based reasoning approach for financial risk detection," IRTG 1792 Discussion Papers 2021-010, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
• Kyle Colangelo & Ying-Ying Lee, 2019. "Double debiased machine learning nonparametric inference with continuous treatments," CeMMAP working papers CWP72/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
• Naftali Cohen & Srijan Sood & Zhen Zeng & Tucker Balch & Manuela Veloso, 2021. "Visual Time Series Forecasting: An Image-driven Approach," Papers 2107.01273, arXiv.org, revised Nov 2021.
• Orkun Saka & Barry Eichengreen & Cevat Giray Aksoy, 2021. "Epidemic Exposure, Fintech Adoption, and the Digital Divide," CESifo Working Paper Series 9173, CESifo.
• CHARISI Vasiliki & COMPANO Ramon & DUCH BROWN Nestor & GOMEZ GUTIERREZ Emilia & KLENERT David & LUTZ Michael & MARSCHINSKI Robert & TORRECILLA SALINAS Carlos, 2021. "What future for European robotics?," JRC Research Reports JRC125343, Joint Research Centre.
• Orkun Saka & Barry Eichengreen & Cevat Giray Aksoy, 2021. "Epidemic Exposure, Fintech Adoption, and the Digital Divide," NBER Working Papers 29006, National Bureau of Economic Research, Inc.
• Mohammad Rasouli & Michael I. Jordan, 2021. "Data Sharing Markets," Papers 2107.08630, arXiv.org, revised Jul 2021.
• Mathieu Rosenbaum & Jianfei Zhang, 2021. "Deep calibration of the quadratic rough Heston model," Papers 2107.01611, arXiv.org, revised May 2022.
• Claudia Noack & Tomasz Olma & Christoph Rothe, 2021. "Flexible Covariate Adjustments in Regression Discontinuity Designs," Papers 2107.07942, arXiv.org, revised Dec 2024.
• Hengxu Lin & Dong Zhou & Weiqing Liu & Jiang Bian, 2021. "Deep Risk Model: A Deep Learning Solution for Mining Latent Risk Factors to Improve Covariance Matrix Estimation," Papers 2107.05201, arXiv.org, revised Oct 2021.
• Jean-Franc{c}ois Chassagneux & Mohan Yang, 2021. "Numerical approximation of singular Forward-Backward SDEs," Papers 2106.15496, arXiv.org.
• FORTES, Roberta & Le Guenedal, Theo, 2020. "Tracking ECB's communication: Perspectives and Implications for Financial Markets," MPRA Paper 108746, University Library of Munich, Germany.
• Wing Fung Chong & Haoen Cui & Yuxuan Li, 2021. "Pseudo-Model-Free Hedging for Variable Annuities via Deep Reinforcement Learning," Papers 2107.03340, arXiv.org, revised Oct 2022.
• Sergio Consoli & Luca Tiozzo Pezzoli & Elisa Tosetti, 2021. "Emotions in Macroeconomic News and their Impact on the European Bond Market," Papers 2106.15698, arXiv.org.
• Stich, Christoph & Tranos, Emmanouil & Nathan, Max, 2021. "Modelling Clusters From The Ground Up: A Web Data Approach," SocArXiv j2w8v, Center for Open Science.
• Ziwei Cong & Jia Liu & Puneet Manchanda, 2021. "The Role of "Live" in Livestreaming Markets: Evidence Using Orthogonal Random Forest," Papers 2107.01629, arXiv.org, revised Sep 2022.