Report NEP-CMP-2021-02-15

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:

• Javier Gonzalez-Conde & 'Angel Rodr'iguez-Rozas & Enrique Solano & Mikel Sanz, 2021. "Efficient Hamiltonian Simulation for Solving Option Price Dynamics," Papers 2101.04023, arXiv.org, revised Jan 2024.
• Jérôme Lelong & Zineb El Filali Ech-Chafiq & Adil Reghai, 2021. "Automatic Control Variates for Option Pricing using Neural Networks," Post-Print hal-02891798, HAL.
• Jaegi Jeon & Kyunghyun Park & Jeonggyu Huh, 2021. "Extensive networks would eliminate the demand for pricing formulas," Papers 2101.09064, arXiv.org.
• Paolo Falbo & Juri Hinz & Piyachat Leelasilapasart & Cristian Pelizzari, 2021. "A Computational Approach to Sequential Decision Optimization in Energy Storage and Trading," Research Paper Series 422, Quantitative Finance Research Centre, University of Technology, Sydney.
• Mr. Benjamin L Hunt & Susanna Mursula & Mr. Rafael A Portillo & Marika Santoro, 2020. "Modeling Trade Tensions: Different Mechanisms in General Equilibrium," IMF Working Papers 2020/279, International Monetary Fund.
• Asiya Maskaeva & Mgeni Msafiri, 2021. "Youth unemployment hysteresis in South Africa: Macro-micro analysis," WIDER Working Paper Series wp-2021-20, World Institute for Development Economic Research (UNU-WIDER).
• Georges Sfeir & Filipe Rodrigues & Maya Abou-Zeid, 2021. "Gaussian Process Latent Class Choice Models," Papers 2101.12252, arXiv.org.
• Omotosho, Babatunde S., 2020. "Oil price shocks, fuel subsidies and macroeconomic (in)stability in Nigeria," MPRA Paper 105464, University Library of Munich, Germany.
• Majid Bazarbash, 2019. "FinTech in Financial Inclusion: Machine Learning Applications in Assessing Credit Risk," IMF Working Papers 2019/109, International Monetary Fund.
• Daeyung Gim & Hyungbin Park, 2021. "A deep learning algorithm for optimal investment strategies," Papers 2101.12387, arXiv.org.
• Claudius Gros, 2021. "Collective strategy condensation: When envy splits societies," Papers 2101.10824, arXiv.org.
• Yi Wei, 2021. "Absolute Value Constraint: The Reason for Invalid Performance Evaluation Results of Neural Network Models for Stock Price Prediction," Papers 2101.10942, arXiv.org, revised Mar 2021.
• In-Koo Cho & Jonathan Libgober, 2021. "Machine Learning for Strategic Inference," Papers 2101.09613, arXiv.org.
• John Ery & Loris Michel, 2021. "Solving optimal stopping problems with Deep Q-Learning," Papers 2101.09682, arXiv.org, revised Jun 2024.
• Ravi Goyal & John Hotchkiss & Robert T. Schooley & Victor De Gruttola & Natasha K. Martin, "undated". "Evaluation of SARS-CoV-2 Transmission Mitigation Strategies on a University Campus Using an Agent-Based Network Model," Mathematica Policy Research Reports 51c58d1aed8e47a0ad7eefb3c, Mathematica Policy Research.
• Xiaodong Wang & Fushing Hsieh, 2021. "Unraveling S&P500 stock volatility and networks -- An encoding-and-decoding approach," Papers 2101.09395, arXiv.org, revised Oct 2021.
• Item repec:ehl:lserod:108470 is not listed on IDEAS anymore

• Aref Mahdavi Ardekani, 2020. "Liquidity, Interbank Network Topology and Bank Capital," Documents de travail du Centre d'Economie de la Sorbonne 20022r, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne, revised Dec 2020.
• Jaehyuk Choi & Desheng Ge & Kyu Ho Kang & Sungbin Sohn, 2021. "Yield Spread Selection in Predicting Recession Probabilities: A Machine Learning Approach," Papers 2101.09394, arXiv.org, revised Jan 2022.
• Xianfei Hui & Baiqing Sun & Hui Jiang & Indranil SenGupta, 2021. "Analysis of stock index with a generalized BN-S model: an approach based on machine learning and fuzzy parameters," Papers 2101.08984, arXiv.org, revised Feb 2022.
• Mark Kiermayer, 2021. "Modeling surrender risk in life insurance: theoretical and experimental insight," Papers 2101.11590, arXiv.org, revised Aug 2021.
• Vera Eichenauer & Ronald Indergand & Isabel Z. Martínez & Christoph Sax, 2020. "Constructing Daily Economic Sentiment Indices Based on Google Trends," KOF Working papers 20-484, KOF Swiss Economic Institute, ETH Zurich.
• Jeffrey Grogger & Ria Ivandic & Tom Kirchmaier, 2020. "Comparing conventional and machine-learning approaches to risk assessment in domestic abuse cases," CEP Discussion Papers dp1676, Centre for Economic Performance, LSE.