Report NEP-CMP-2020-05-11

This is the archive for NEP-CMP, a report on new working papers in the area of Computational Economics. Stan Miles issued this report. It is usually issued weekly.

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Other reports in NEP-CMP

The following items were announced in this report:

• Brian Huge & Antoine Savine, 2020. "Differential Machine Learning," Papers 2005.02347, arXiv.org, revised Sep 2020.
• Alexander Arimond & Damian Borth & Andreas Hoepner & Michael Klawunn & Stefan Weisheit, 2020. "Neural Networks and Value at Risk," Papers 2005.01686, arXiv.org, revised May 2020.
• Lucio Fernandez-Arjona, 2020. "A neural network model for solvency calculations in life insurance," Papers 2005.02318, arXiv.org.
• Alessandro Gnoatto & Athena Picarelli & Christoph Reisinger, 2020. "Deep xVA solver -- A neural network based counterparty credit risk management framework," Papers 2005.02633, arXiv.org, revised Dec 2022.
• Lucio Fernandez Arjona & Damir Filipović, 2020. "A machine learning approach to portfolio pricing and risk management for high-dimensional problems," Swiss Finance Institute Research Paper Series 20-28, Swiss Finance Institute.
• Roy Gernhardt & Bjorn Persson, 2020. "On the Equivalence of Neural and Production Networks," Papers 2005.00510, arXiv.org, revised Mar 2021.
• Sidra Mehtab & Jaydip Sen, 2020. "A Time Series Analysis-Based Stock Price Prediction Using Machine Learning and Deep Learning Models," Papers 2004.11697, arXiv.org, revised May 2021.
• Johannes Ruf & Weiguan Wang, 2020. "Hedging with Linear Regressions and Neural Networks," Papers 2004.08891, arXiv.org, revised Jun 2021.
• Christa Cuchiero & Wahid Khosrawi & Josef Teichmann, 2020. "A generative adversarial network approach to calibration of local stochastic volatility models," Papers 2005.02505, arXiv.org, revised Sep 2020.
• Lucio Fernandez-Arjona & Damir Filipovi'c, 2020. "A machine learning approach to portfolio pricing and risk management for high-dimensional problems," Papers 2004.14149, arXiv.org, revised May 2022.
• Humayra Shoshi & Indranil SenGupta, 2020. "Hedging and machine learning driven crude oil data analysis using a refined Barndorff-Nielsen and Shephard model," Papers 2004.14862, arXiv.org, revised Feb 2021.
• Michael Roberts & Indranil SenGupta, 2020. "Sequential hypothesis testing in machine learning, and crude oil price jump size detection," Papers 2004.08889, arXiv.org, revised Dec 2020.
• Dimitris Korobilis & Davide Pettenuzzo, 2020. "Machine Learning Econometrics: Bayesian algorithms and methods," Papers 2004.11486, arXiv.org.
• Carlo Baldassi & Simone Cerreia-Vioglio & Fabio Maccheroni & Massimo Marinacci & Marco Pirazzini, 2020. "Multialternative Neural Decision Processes," Papers 2005.01081, arXiv.org, revised May 2021.
• Jager, Maximilian & Siemsen, Thomas & Vilsmeier, Johannes, 2020. "Interbank risk assessment: A simulation approach," Discussion Papers 23/2020, Deutsche Bundesbank.
• Gael M. Martin & David T. Frazier & Christian P. Robert, 2020. "Computing Bayes: Bayesian Computation from 1763 to the 21st Century," Monash Econometrics and Business Statistics Working Papers 14/20, Monash University, Department of Econometrics and Business Statistics.
• Misha van Beek, 2020. "Consistent Calibration of Economic Scenario Generators: The Case for Conditional Simulation," Papers 2004.09042, arXiv.org.
• Ruda Zhang & Patrick Wingo & Rodrigo Duran & Kelly Rose & Jennifer Bauer & Roger Ghanem, 2020. "Environmental Economics and Uncertainty: Review and a Machine Learning Outlook," Papers 2004.11780, arXiv.org.
• Lesly Cassin & Paolo Melindi-Ghidi & Fabien Prieur, 2020. "Confronting climate change: Adaptation vs. migration strategies in Small Island Developing States," CEE-M Working Papers hal-02515116, CEE-M, Universtiy of Montpellier, CNRS, INRA, Montpellier SupAgro.
• Manuel Nunes & Enrico Gerding & Frank McGroarty & Mahesan Niranjan, 2020. "Long short-term memory networks and laglasso for bond yield forecasting: Peeping inside the black box," Papers 2005.02217, arXiv.org.
• Jackie Jianhong Shen, 2020. "A Stochastic LQR Model for Child Order Placement in Algorithmic Trading," Papers 2004.13797, arXiv.org.
• Frederik Priem & Philip Stessens & Frank Canters, 2020. "Microsimulation of residential activity for alternative urban development scenarios: A case study on brussels and flemish brabant," ULB Institutional Repository 2013/305003, ULB -- Universite Libre de Bruxelles.
• Grogger, Jeffrey & Ivandic, Ria & Kirchmaier, Thomas, 2020. "Comparing conventional and machine-learning approaches to risk assessment in domestic abuse cases," LSE Research Online Documents on Economics 104159, London School of Economics and Political Science, LSE Library.
• Takuya Obara & Yoshitomo Ogawa, 2020. "Optimal Taxation in an Endogenous Fertility Model with Non-Cooperative Couples," Discussion Paper Series 211, School of Economics, Kwansei Gakuin University, revised Jan 2021.
• Makarov, Vladimir & Stouch, Terry & Allgood, Brandon & Willis, Christopher & Lynch, Nick, 2020. "Best Practices for Artificial Intelligence in Life Sciences Research," OSF Preprints eqm9j, Center for Open Science.
• Dang, Chuangyin & Herings, P. Jean-Jacques & Li, Peixuan, 2020. "An Interior-Point Path-Following Method to Compute Stationary Equilibria in Stochastic Games," Research Memorandum 001, Maastricht University, Graduate School of Business and Economics (GSBE).
• Agostinelli, Francesco & Doepke, Matthias & Sorrenti, Giuseppe & Zilibotti, Fabrizio, 2020. "It Takes a Village: The Economics of Parenting with Neighborhood and Peer Effects," IZA Discussion Papers 13161, Institute of Labor Economics (IZA).
• Eric Kemp-Benedict, 2020. "Macroeconomic impacts of the public health response to COVID-19," Working Papers PKWP2011, Post Keynesian Economics Society (PKES).
• Jean-Marie Dufour & Emmanuel Flachaire & Lynda Khalaf, 2019. "Permutation Tests for Comparing Inequality Measures," Post-Print hal-02172793, HAL.
• Adam Pigoñ & Micha³ Ramsza, 2019. "A comparison of Swiss, German and Polish fiscal rules using Monte Carlo simulations," IBS Working Papers 10/2019, Instytut Badan Strukturalnych.
• Elliot Anenberg & Daniel R. Ringo, 2019. "The Propagation of Demand Shocks Through Housing Markets," Finance and Economics Discussion Series 2019-084, Board of Governors of the Federal Reserve System (U.S.).
• Thomas von Brasch & Ådne Cappelen & Håvard Hungnes & Terje Skjerpen, 2020. "Modeling R&D spillovers to productivity. The effects of tax policy," Discussion Papers 927, Statistics Norway, Research Department.
• Tian Guo & Nicolas Jamet & Valentin Betrix & Louis-Alexandre Piquet & Emmanuel Hauptmann, 2020. "ESG2Risk: A Deep Learning Framework from ESG News to Stock Volatility Prediction," Papers 2005.02527, arXiv.org.
• Soete, Luc & Verspagen, Bart & Ziesemer, Thomas, 2020. "The economic impact of public R&D: an international perspective," MERIT Working Papers 2020-014, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
• Poppius, Hampus, 2020. "Multimarket Contact and Collusion in Online Retail," Working Papers 2020:5, Lund University, Department of Economics.
• Breda, Thomas & Grenet, Julien & Monnet, Marion & Van Effenterre, Clémentine, 2020. "Do Female Role Models Reduce the Gender Gap in Science? Evidence from French High Schools," IZA Discussion Papers 13163, Institute of Labor Economics (IZA).