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Report NEP-CMP-2020-03-09
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:
- Jacopo Staccioli & Mauro Napoletano, 2018, "An agent-based model of intra day financial markets dynamics," Documents de Travail de l'OFCE, Observatoire Francais des Conjonctures Economiques (OFCE), number 2018-34, Oct.
- Taran Faehn & Gabriel Bachner & Robert Beach & Jean Chateau & Shinichiro Fujimori & Madanmohan Ghosh & Meriem Hamdi-Cherif & Elisa Lanzi & Sergey Paltsev & Toon Vandyck & Bruno Cunha & Rafael Garaffa , 2020, "Capturing Key Energy and Emission Trends in CGE Models: Assessment of Status and Remaining Challenges," CESifo Working Paper Series, CESifo, number 8072.
- Matthew Dixon & Igor Halperin, 2020, "G-Learner and GIRL: Goal Based Wealth Management with Reinforcement Learning," Papers, arXiv.org, number 2002.10990, Feb.
- Lilit Popoyan & Mauro Napoletano & Andrea Roventini, 2019, "Winter is possibly not coming : mitigating financial instability in an agent-based model with interbank market," Documents de Travail de l'OFCE, Observatoire Francais des Conjonctures Economiques (OFCE), number 2019-14, Jul.
- Carmine de Franco & Christophe Geissler & Vincent Margot & Bruno Monnier, 2020, "ESG investments: Filtering versus machine learning approaches," Papers, arXiv.org, number 2002.07477, Feb, revised Apr 2020.
- Andreas Binder & Onkar Jadhav & Volker Mehrmann, 2020, "Model order reduction for parametric high dimensional models in the analysis of financial risk," Papers, arXiv.org, number 2002.11976, Feb, revised Jul 2020.
- Evgeny Ponomarev & Ivan Oseledets & Andrzej Cichocki, 2020, "Using Reinforcement Learning in the Algorithmic Trading Problem," Papers, arXiv.org, number 2002.11523, Feb.
- Akshay Krishnamurthy & Thodoris Lykouris & Chara Podimata & Robert Schapire, 2020, "Contextual Search in the Presence of Adversarial Corruptions," Papers, arXiv.org, number 2002.11650, Feb, revised Aug 2022.
- Pang,Jun & Timilsina,Govinda R., 2019, "Implications for Provincial Economies of Meeting China's NDC through an Emission Trading Scheme : A Regional CGE Modeling Analysis," Policy Research Working Paper Series, The World Bank, number 8909, Jun.
- Marcelo Veracierto, 2020, "Computing Equilibria of Stochastic Heterogeneous Agent Models Using Decision Rule Histories," Working Paper Series, Federal Reserve Bank of Chicago, number WP 2020-05, Feb, DOI: 10.21033/wp-2020-05.
- Oksana Bashchenko & Alexis Marchal, 2020, "Deep Learning for Asset Bubbles Detection," Papers, arXiv.org, number 2002.06405, Feb.
- Yusuke Narita & Shota Yasui & Kohei Yata, 2020, "Debiased Off-Policy Evaluation for Recommendation Systems," Papers, arXiv.org, number 2002.08536, Feb, revised Aug 2021.
- Timilsina,Govinda R. & Pang,Jun & Yang,Xi, 2019, "How Much Would China Gain from Power Sector Reforms ? An Analysis Using TIMES and CGE Models," Policy Research Working Paper Series, The World Bank, number 8908, Jun.
- Pfeiffer,Basile Fabrice & Rabe,Claus & Selod,Harris & Viguie,Vincent, 2019, "Assessing Urban Policies Using a Simulation Model with Formal and Informal Housing : Application to Cape Town, South Africa," Policy Research Working Paper Series, The World Bank, number 8921, Jun.
- Cai,Yongyang & Steinbuks,Jevgenijs & Judd,Kenneth L. & Jaegermeyr,Jonas & Hertel,Thomas W., 2020, "Modeling Uncertainty in Large Natural Resource Allocation Problems," Policy Research Working Paper Series, The World Bank, number 9159, Feb.
- Myriem Alijo & Otman Abdoun & Mostafa Bachran & Amal Bergam, 2020, "Optimization by Hybridization of a Genetic Algorithm with the PROMOTHEE Method: Management of Multicriteria Localization," Papers, arXiv.org, number 2002.04068, Jan.
- Tesi Aliaj & Aris Anagnostopoulos & Stefano Piersanti, 2020, "Firms Default Prediction with Machine Learning," Papers, arXiv.org, number 2002.11705, Feb.
- Lucia Cipolina Kun & Simone Caenazzo & Ksenia Ponomareva, 2020, "Mathematical Foundations of Regression Methods for the approximation of the Forward Initial Margin," Papers, arXiv.org, number 2002.04563, Feb, revised Sep 2022.
- Tianping Zhang & Yuanqi Li & Yifei Jin & Jian Li, 2020, "AutoAlpha: an Efficient Hierarchical Evolutionary Algorithm for Mining Alpha Factors in Quantitative Investment," Papers, arXiv.org, number 2002.08245, Feb, revised Apr 2020.
- Marco Pangallo, 2020, "Synchronization of endogenous business cycles," Papers, arXiv.org, number 2002.06555, Feb, revised Sep 2024.
- Chi Chen & Li Zhao & Wei Cao & Jiang Bian & Chunxiao Xing, 2020, "Trimming the Sail: A Second-order Learning Paradigm for Stock Prediction," Papers, arXiv.org, number 2002.06878, Feb.
- Greg Lewis & Vasilis Syrgkanis, 2020, "Double/Debiased Machine Learning for Dynamic Treatment Effects via g-Estimation," Papers, arXiv.org, number 2002.07285, Feb, revised Jun 2021.
- Daniel Guterding, 2020, "Inventory effects on the price dynamics of VSTOXX futures quantified via machine learning," Papers, arXiv.org, number 2002.08207, Feb.
- Warwick McKibbin & Roshen Fernando, 2020, "The global macroeconomic impacts of COVID-19: Seven scenarios," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2020-19, Mar.
- Masaya Abe & Kei Nakagawa, 2020, "Cross-sectional Stock Price Prediction using Deep Learning for Actual Investment Management," Papers, arXiv.org, number 2002.06975, Feb.
- Brad Hershbein & Melissa Schettini Kearney & Luke W. Pardue, 2020, "College Attainment, Income Inequality, and Economic Security: A Simulation Exercise," NBER Working Papers, National Bureau of Economic Research, Inc, number 26747, Feb.
- Thiago W. Alves & Ionut Florescu & George Calhoun & Dragos Bozdog, 2020, "SHIFT: A Highly Realistic Financial Market Simulation Platform," Papers, arXiv.org, number 2002.11158, Feb, revised Aug 2020.
- Born, Andreas & Janssen, Aljoscha, 2020, "Does a District-Vote Matter for the Behavior of Politicians? A Textual Analysis of Parliamentary Speeches," Working Paper Series, Research Institute of Industrial Economics, number 1320, Feb.
- Item repec:spo:wpmain:info:hdl:2441/7vu7u98l6982393tfrj30mj1l4 is not listed on IDEAS anymore
- Kieran Marray & Nikhil Krishna & Jarel Tang, 2020, "How Do Expectations Affect Learning About Fundamentals? Some Experimental Evidence," Papers, arXiv.org, number 2002.07229, Feb, revised Jul 2021.