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Report NEP-CMP-2021-07-26
This is the archive for NEP-CMP, a report on new working papers in the area of Computational Economics. Stanley Miles issued this report. It is usually issued weekly.Subscribe to this report: email, RSS, or Mastodon, or Bluesky.
Other reports in NEP-CMP
The following items were announced in this report:
- Helmut Wasserbacher & Martin Spindler, 2021, "Machine Learning for Financial Forecasting, Planning and Analysis: Recent Developments and Pitfalls," Papers, arXiv.org, number 2107.04851, Jul.
- Supriya Bajpai, 2021, "Application of deep reinforcement learning for Indian stock trading automation," Papers, arXiv.org, number 2106.16088, May.
- Juyong Lee & Youngsang Cho, 2021, "National-scale electricity peak load forecasting: Traditional, machine learning, or hybrid model?," Papers, arXiv.org, number 2107.06174, Jun.
- Angelo Garangau Menezes & Saulo Martiello Mastelini, 2021, "MegazordNet: combining statistical and machine learning standpoints for time series forecasting," Papers, arXiv.org, number 2107.01017, Jun.
- Sohrab Mokhtari & Kang K. Yen & Jin Liu, 2021, "Effectiveness of Artificial Intelligence in Stock Market Prediction based on Machine Learning," Papers, arXiv.org, number 2107.01031, Jun.
- Priyank Sonkiya & Vikas Bajpai & Anukriti Bansal, 2021, "Stock price prediction using BERT and GAN," Papers, arXiv.org, number 2107.09055, Jul.
- Francesca Micocci & Armando Rungi, 2021, "Predicting Exporters with Machine Learning," Working Papers, IMT School for Advanced Studies Lucca, number 03/2021, Jul, revised Jul 2021.
- Wing Fung Chong & Haoen Cui & Yuxuan Li, 2021, "Pseudo-Model-Free Hedging for Variable Annuities via Deep Reinforcement Learning," Papers, arXiv.org, number 2107.03340, Jul, revised Oct 2022.
- Kyle Colangelo & Ying-Ying Lee, 2019, "Double debiased machine learning nonparametric inference with continuous treatments," CeMMAP working papers, Centre for Microdata Methods and Practice, Institute for Fiscal Studies, number CWP72/19, Dec.
- Naudé, Wim & Bray, Amy & Lee, Celina, 2021, "Crowdsourcing Artificial Intelligence in Africa: Findings from a Machine Learning Contest," IZA Discussion Papers, Institute of Labor Economics (IZA), number 14545, Jul.
- Dan Wang & Zhi Chen & Ionut Florescu, 2021, "A Sparsity Algorithm with Applications to Corporate Credit Rating," Papers, arXiv.org, number 2107.10306, Jul.
- 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, arXiv.org, number 2107.05592, Jul.
- Ren'e Carmona & Mathieu Lauri`ere, 2021, "Deep Learning for Mean Field Games and Mean Field Control with Applications to Finance," Papers, arXiv.org, number 2107.04568, Jul.
- 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, arXiv.org, number 2107.05201, Jul, revised Oct 2021.
- Gautier Marti & Victor Goubet & Frank Nielsen, 2021, "cCorrGAN: Conditional Correlation GAN for Learning Empirical Conditional Distributions in the Elliptope," Papers, arXiv.org, number 2107.10606, Jul.
- Jean-Franc{c}ois Chassagneux & Mohan Yang, 2021, "Numerical approximation of singular Forward-Backward SDEs," Papers, arXiv.org, number 2106.15496, Jun.
- Orkun Saka & Barry Eichengreen & Cevat Giray Aksoy, 2021, "Epidemic Exposure, Fintech Adoption, and the Digital Divide," NBER Working Papers, National Bureau of Economic Research, Inc, number 29006, Jul.
- Li, Wei & Paraschiv, Florentina & Sermpinis, Georgios, 2021, "A data-driven explainable case-based reasoning approach for financial risk detection," IRTG 1792 Discussion Papers, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series", number 2021-010.
- Naftali Cohen & Srijan Sood & Zhen Zeng & Tucker Balch & Manuela Veloso, 2021, "Visual Time Series Forecasting: An Image-driven Approach," Papers, arXiv.org, number 2107.01273, Jul, revised Nov 2021.
- Claudia Noack & Tomasz Olma & Christoph Rothe, 2021, "Flexible Covariate Adjustments in Regression Discontinuity Designs," Papers, arXiv.org, number 2107.07942, Jul, revised Apr 2025.
- Khalid El-Awady, 2021, "Adaptive Stress Testing for Adversarial Learning in a Financial Environment," Papers, arXiv.org, number 2107.03577, Jul.
- González-Bustamante, Bastián & Astete Olmos, Matías Ignacio & Orvenes, Berenice Issabella, 2021, "Senior Public Managers: A Novel Dataset on Members of the Chilean Civil Service," SocArXiv, Center for Open Science, number vshcz, Jul, DOI: 10.31219/osf.io/vshcz.
- Christian Meier & Lingfei Li & Gongqiu Zhang, 2021, "Simulation of Multidimensional Diffusions with Sticky Boundaries via Markov Chain Approximation," Papers, arXiv.org, number 2107.04260, Jul.
- SAKKAS Stylianos & CRUCITTI Francesca & CONTE Andrea & SALOTTI Simone, 2021, "The 2020 territorial impact of COVID-19 in the EU: A RHOMOLO update," JRC Research Reports, Joint Research Centre, number JRC125536, Jul.
- James Hebden & Fabian Winkler, 2021, "Computation of Policy Counterfactuals in Sequence Space," Finance and Economics Discussion Series, Board of Governors of the Federal Reserve System (U.S.), number 2021-042r1, Jul, revised 01 Sep 2024, DOI: 10.17016/FEDS.2021.042r1.
- Shaojun Ma & Pengcheng Li, 2021, "Predicting Daily Trading Volume via Various Hidden States," Papers, arXiv.org, number 2107.07678, Jul.
- Wynnona Steyn & Alexius Sithole & Winile Ngobeni & Eva Muwanga-Zake & Helen Barnes & Michael Noble & David McLennan & Gemma Wright & Katrin Gasior, 2021, "Simulating personal income tax in South Africa using administrative data and survey data: A comparison of PITMOD and SAMOD for tax year 2018," WIDER Working Paper Series, World Institute for Development Economic Research (UNU-WIDER), number wp-2021-120.