Report NEP-CMP-2019-07-22

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:

• Jacobo Roa-Vicens & Cyrine Chtourou & Angelos Filos & Francisco Rullan & Yarin Gal & Ricardo Silva, 2019, "Towards Inverse Reinforcement Learning for Limit Order Book Dynamics," Papers, arXiv.org, number 1906.04813, Jun.
• Francois Belletti & Davis King & Kun Yang & Roland Nelet & Yusef Shafi & Yi-Fan Chen & John Anderson, 2019, "Tensor Processing Units for Financial Monte Carlo," Papers, arXiv.org, number 1906.02818, Jun, revised Jan 2020.
• A Itkin, 2019, "Deep learning calibration of option pricing models: some pitfalls and solutions," Papers, arXiv.org, number 1906.03507, Jun.
• Donovan Platt, 2019, "Bayesian Estimation of Economic Simulation Models using Neural Networks," Papers, arXiv.org, number 1906.04522, Jun.
• Hyungjun Park & Min Kyu Sim & Dong Gu Choi, 2019, "An intelligent financial portfolio trading strategy using deep Q-learning," Papers, arXiv.org, number 1907.03665, Jul, revised Nov 2019.
• Jeremy D. Turiel & Tomaso Aste, 2019, "P2P Loan acceptance and default prediction with Artificial Intelligence," Papers, arXiv.org, number 1907.01800, Jul.
• Michael A. Kouritzin & Anne MacKay, 2019, "Branching Particle Pricers with Heston Examples," Papers, arXiv.org, number 1907.00219, Jun, revised Nov 2019.
• Yuxuan Huang & Luiz Fernando Capretz & Danny Ho, 2019, "Neural Network Models for Stock Selection Based on Fundamental Analysis," Papers, arXiv.org, number 1906.05327, Jun.
• Laliotis, Dimitrios & Buesa, Alejandro & Leber, Miha & Población García, Francisco Javier, 2019, "An agent-based model for the assessment of LTV caps," Working Paper Series, European Central Bank, number 2294, Jul.
• Soybilgen, Baris, 2018, "Identifying US business cycle regimes using dynamic factors and neural network models," MPRA Paper, University Library of Munich, Germany, number 94715, Jul.
• Maarten Buis, 2019, "Agent based models in Mata," German Stata Users' Group Meetings 2019, Stata Users Group, number 04, Jul.
• Lotfi Boudabsa & Damir Filipovic, 2019, "Machine learning with kernels for portfolio valuation and risk management," Papers, arXiv.org, number 1906.03726, Jun, revised May 2021.
• Damien Ackerer & Natasa Tagasovska & Thibault Vatter, 2019, "Deep Smoothing of the Implied Volatility Surface," Papers, arXiv.org, number 1906.05065, Jun, revised Oct 2020.
• Michael Allan Ribers & Hannes Ullrich, 2019, "Battling Antibiotic Resistance: Can Machine Learning Improve Prescribing?," Papers, arXiv.org, number 1906.03044, Jun.
• Hung Ba, 2019, "Improving Detection of Credit Card Fraudulent Transactions using Generative Adversarial Networks," Papers, arXiv.org, number 1907.03355, Jul.
• Brandon Da Silva & Sylvie Shang Shi, 2019, "Style Transfer with Time Series: Generating Synthetic Financial Data," Papers, arXiv.org, number 1906.03232, May, revised Dec 2019.
• Item repec:ipt:decwpa:2018-08 is not listed on IDEAS anymore

• Xinyi Li & Yinchuan Li & Yuancheng Zhan & Xiao-Yang Liu, 2019, "Optimistic Bull or Pessimistic Bear: Adaptive Deep Reinforcement Learning for Stock Portfolio Allocation," Papers, arXiv.org, number 1907.01503, Jun.
• Emir Hrnjic & Nikodem Tomczak, 2019, "Machine learning and behavioral economics for personalized choice architecture," Papers, arXiv.org, number 1907.02100, Jul.
• Istemi Berk & Eren √áam, 2019, "The Shift in Global Crude Oil Market Structure: A model-based analysis of the period 2013‚Äì2017," EWI Working Papers, Energiewirtschaftliches Institut an der Universitaet zu Koeln (EWI), number 2019-5, Jul.
• Rukmal Weerawarana & Yiyi Zhu & Yuzhen He, 2019, "Learned Sectors: A fundamentals-driven sector reclassification project," Papers, arXiv.org, number 1906.03935, May.
• Item repec:bof:bofrdp:2019_011 is not listed on IDEAS anymore

• Rémy Le Boennec & Fouad Hadj Selem & Ghazaleh Khodabandelou, 2019, "La mobilité individuelle motorisée dans les déplacements domicile-travail : préférence modale ou choix contraint ? Une approche par le machine learning," Post-Print, HAL, number hal-02160862, Jun.
• Karen Turner & Gioele Figus & Kim Swales & L. (Lisa B.) Ryan & et al., 2019, "Can the composition of energy use in an expanding economy be altered by consumers’ responses to technological change?," Open Access publications, School of Economics, University College Dublin, number 10197/10840, Jul.
• Xin Qian & Yudong Chen & Andreea Minca, 2019, "Clustering Degree-Corrected Stochastic Block Model with Outliers," Papers, arXiv.org, number 1906.03305, Jun.
• Clement Gastaud & Theophile Carniel & Jean-Michel Dalle, 2019, "The varying importance of extrinsic factors in the success of startup fundraising: competition at early-stage and networks at growth-stage," Papers, arXiv.org, number 1906.03210, Jun.
• Tianyao Chen & Xue Cheng & Jingping Yang, 2019, "Common Decomposition of Correlated Brownian Motions and its Financial Applications," Papers, arXiv.org, number 1907.03295, Jul, revised Nov 2020.
• Imad Chahboun & Nathaniel Hoover, 2019, "Variable Annuities: Underlying Risks and Sensitivities," Supervisory Research and Analysis Working Papers, Federal Reserve Bank of Boston, number RPA 19-1, Apr.
• Jose Luis Montiel Olea & Pietro Ortoleva & Mallesh M Pai & Andrea Prat, 2019, "Competing Models," Papers, arXiv.org, number 1907.03809, Jul, revised Nov 2021.
• Catherine D'Hondt & Rudy De Winne & Eric Ghysels & Steve Raymond, 2019, "Artificial Intelligence Alter Egos: Who benefits from Robo-investing?," Papers, arXiv.org, number 1907.03370, Jul.
• Zihao Zhang & Stefan Zohren & Stephen Roberts, 2019, "Extending Deep Learning Models for Limit Order Books to Quantile Regression," Papers, arXiv.org, number 1906.04404, Jun.
• Michael Lechner & Gabriel Okasa, 2019, "Random Forest Estimation of the Ordered Choice Model," Papers, arXiv.org, number 1907.02436, Jul, revised Sep 2022.
• Item repec:ipt:decwpa:2018-09 is not listed on IDEAS anymore

• Fabrice Daniel, 2019, "Financial Time Series Data Processing for Machine Learning," Papers, arXiv.org, number 1907.03010, Jul.
• Matias Barenstein, 2019, "ProPublica's COMPAS Data Revisited," Papers, arXiv.org, number 1906.04711, Jun, revised Jul 2019.

Report NEP-CMP-2019-07-22

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: