Report NEP-CMP-2020-10-26

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:

• Kyle Steinhauer & Takahisa Fukadai & Sho Yoshida, 2020. "Solving the Optimal Trading Trajectory Problem Using Simulated Bifurcation," Papers 2009.08412, arXiv.org.
• Hamed Vaheb, 2020. "Asset Price Forecasting using Recurrent Neural Networks," Papers 2010.06417, arXiv.org, revised Oct 2020.
• Saeed Nosratabadi & Amir Mosavi & Ramin Keivani & Sina Ardabili & Farshid Aram, 2020. "State of the Art Survey of Deep Learning and Machine Learning Models for Smart Cities and Urban Sustainability," Papers 2010.02670, arXiv.org.
• Cosimo Magazzino & Marco Mele & Nicolas Schneider & Guillaume Vallet, 2020. "The relationship between nuclear energy consumption and economic growth: evidence from Switzerland," Post-Print halshs-02951860, HAL.
• Iro Ren'e Kouarfate & Michael A. Kouritzin & Anne MacKay, 2020. "Explicit solution simulation method for the 3/2 model," Papers 2009.09058, arXiv.org, revised Jan 2021.
• Sidra Mehtab & Jaydip Sen & Abhishek Dutta, 2020. "Stock Price Prediction Using Machine Learning and LSTM-Based Deep Learning Models," Papers 2009.10819, arXiv.org.
• Arno Botha & Conrad Beyers & Pieter de Villiers, 2020. "Simulation-based optimisation of the timing of loan recovery across different portfolios," Papers 2009.11064, arXiv.org, revised Apr 2021.
• Sina Ardabili & Amir Mosavi & Asghar Mahmoudi & Tarahom Mesri Gundoshmian & Saeed Nosratabadi & Annamaria R. Varkonyi-Koczy, 2020. "Modelling Temperature Variation of Mushroom Growing Hall Using Artificial Neural Networks," Papers 2010.02673, arXiv.org.
• Artur Sokolovsky & Luca Arnaboldi, 2020. "A Generic Methodology for the Statistically Uniform & Comparable Evaluation of Automated Trading Platform Components," Papers 2009.09993, arXiv.org, revised Jun 2022.
• Guido de Blasio & Alessio D'Ignazio & Marco Letta, 2020. "Predicting Corruption Crimes with Machine Learning. A Study for the Italian Municipalities," Working Papers 16/20, Sapienza University of Rome, DISS.
• Bernhardt, Lea, 2020. "Common factors of withdrawn and prohibited mergers in the European Union," Working Paper 184/2020, Helmut Schmidt University, Hamburg.
• Sanguinet, Eduardo & Alvim, Augusto, 2020. "Effects of EU-Mercosur trade agreement on bilateral trade: the role of Brexit," MPRA Paper 103010, University Library of Munich, Germany.
• Kluge, Jan & Lappoehn, Sarah & Plank, Kerstin, 2020. "The Determinants of Economic Competitiveness," IHS Working Paper Series 24, Institute for Advanced Studies.
• Ya Chen & Mike Tsionas & Valentin Zelenyuk, 2020. "LASSO DEA for small and big data," CEPA Working Papers Series WP092020, School of Economics, University of Queensland, Australia.
• Steven J. Davis & Stephen Hansen & Cristhian Seminario-Amez, 2020. "Firm-Level Risk Exposures and Stock Returns in the Wake of Covid-19," CESifo Working Paper Series 8594, CESifo.
• Garance Génicot & Laurent Bouton & Micael Castanheira De Moura, 2020. "Electoral Systems and Inequalities in Government Interventions," Working Papers ECARES 2020-44, ULB -- Universite Libre de Bruxelles.
• Céline Bonnet & Jan Philip Schain, 2020. "An Empirical Analysis of Mergers: Efficiency Gains and Impact on Consumer Prices," Post-Print hal-02952921, HAL.
• Alves, Vasco, 2019. "Pricing and waiting time decisions in a health care market with private and public provision," MPRA Paper 100996, University Library of Munich, Germany.
• Andrew Clark, 2020. "A Pound Centric look at the Pound vs. Krona Exchange Rate Movement from 1844 to 1965," Economics Discussion Papers em-dp2020-22, Department of Economics, University of Reading.
• Anastasios Petropoulos & Vassilis Siakoulis & Konstantinos P. Panousis & Loukas Papadoulas & Sotirios Chatzis, 2020. "A Deep Learning Approach for Dynamic Balance Sheet Stress Testing," Papers 2009.11075, arXiv.org, revised Sep 2022.
• Bruno Spilak & Wolfgang Karl Hardle, 2020. "Tail-risk protection: Machine Learning meets modern Econometrics," Papers 2010.03315, arXiv.org, revised Aug 2021.
• Martin Jaraiz, 2020. "Ants, robots, humans: a self-organizing, complex systems modeling approach," Papers 2009.10823, arXiv.org, revised Oct 2020.
• Stefan Tübbicke, 2020. "Entropy Balancing for Continuous Treatments," CEPA Discussion Papers 21, Center for Economic Policy Analysis.
• Andrey Itkin & Dmitry Muravey, 2020. "Semi-analytic pricing of double barrier options with time-dependent barriers and rebates at hit," Papers 2009.09342, arXiv.org, revised Oct 2020.
• Thomas Dierckx & Jesse Davis & Wim Schoutens, 2020. "Using Machine Learning and Alternative Data to Predict Movements in Market Risk," Papers 2009.07947, arXiv.org.
• Peter K. Friz & Paul Gassiat & Paolo Pigato, 2020. "Short dated smile under Rough Volatility: asymptotics and numerics," Papers 2009.08814, arXiv.org, revised Sep 2021.
• Baranowski, Rafal & Chen, Yining & Fryzlewicz, Piotr, 2020. "Ranking-based variable selection for high-dimensional data," LSE Research Online Documents on Economics 90233, London School of Economics and Political Science, LSE Library.
• Xiao Yang & Weiqing Liu & Dong Zhou & Jiang Bian & Tie-Yan Liu, 2020. "Qlib: An AI-oriented Quantitative Investment Platform," Papers 2009.11189, arXiv.org.
• Qi Zhao, 2020. "A Deep Learning Framework for Predicting Digital Asset Price Movement from Trade-by-trade Data," Papers 2010.07404, arXiv.org.
• Hannes Mueller & Andre Groger & Jonathan Hersh & Andrea Matranga & Joan Serrat, 2020. "Monitoring War Destruction from Space: A Machine Learning Approach," Papers 2010.05970, arXiv.org, revised Oct 2020.
• Samuel Mugel & Enrique Lizaso & Roman Orus, 2020. "Use Cases of Quantum Optimization for Finance," Papers 2010.01312, arXiv.org.
• Junfeng Hu & Xiaosa Li & Yuru Xu & Shaowu Wu & Bin Zheng, 2020. "Evaluation of company investment value based on machine learning," Papers 2010.01996, arXiv.org.
• Poblete-Cazenave, Miguel & Pachauri, Shonali, 2020. "A simulation-based estimation model of household electricity demand and appliance ownership," MPRA Paper 103403, University Library of Munich, Germany.