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. 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:

• Javier Gonzalez-Conde & 'Angel Rodr'iguez-Rozas & Enrique Solano & Mikel Sanz, 2021, "Efficient Hamiltonian Simulation for Solving Option Price Dynamics," Papers, arXiv.org, number 2101.04023, Jan, 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, number hal-02891798, DOI: 10.1515/mcma-2020-2081.
• Jaegi Jeon & Kyunghyun Park & Jeonggyu Huh, 2021, "Extensive networks would eliminate the demand for pricing formulas," Papers, arXiv.org, number 2101.09064, Jan.
• Paolo Falbo & Juri Hinz & Piyachat Leelasilapasart & Cristian Pelizzari, 2021, "A Computational Approach to Sequential Decision Optimization in Energy Storage and Trading," Research Paper Series, Quantitative Finance Research Centre, University of Technology, Sydney, number 422, Jan.
• Mr. Benjamin L Hunt & Susanna Mursula & Mr. Rafael A Portillo & Marika Santoro, 2020, "Modeling Trade Tensions: Different Mechanisms in General Equilibrium," IMF Working Papers, International Monetary Fund, number 2020/279, Dec.
• Asiya Maskaeva & Mgeni Msafiri, 2021, "Youth unemployment hysteresis in South Africa: Macro-micro analysis," WIDER Working Paper Series, World Institute for Development Economic Research (UNU-WIDER), number wp-2021-20.
• Georges Sfeir & Filipe Rodrigues & Maya Abou-Zeid, 2021, "Gaussian Process Latent Class Choice Models," Papers, arXiv.org, number 2101.12252, Jan.
• Omotosho, Babatunde S., 2020, "Oil price shocks, fuel subsidies and macroeconomic (in)stability in Nigeria," MPRA Paper, University Library of Munich, Germany, number 105464.
• Majid Bazarbash, 2019, "FinTech in Financial Inclusion: Machine Learning Applications in Assessing Credit Risk," IMF Working Papers, International Monetary Fund, number 2019/109, May.
• Daeyung Gim & Hyungbin Park, 2021, "A deep learning algorithm for optimal investment strategies," Papers, arXiv.org, number 2101.12387, Jan.
• Claudius Gros, 2021, "Collective strategy condensation: When envy splits societies," Papers, arXiv.org, number 2101.10824, Jan.
• Yi Wei, 2021, "Absolute Value Constraint: The Reason for Invalid Performance Evaluation Results of Neural Network Models for Stock Price Prediction," Papers, arXiv.org, number 2101.10942, Jan, revised Mar 2021.
• In-Koo Cho & Jonathan Libgober, 2021, "Machine Learning for Strategic Inference," Papers, arXiv.org, number 2101.09613, Jan.
• John Ery & Loris Michel, 2021, "Solving optimal stopping problems with Deep Q-Learning," Papers, arXiv.org, number 2101.09682, Jan, revised Jun 2024.
• Ravi Goyal & John Hotchkiss & Robert T. Schooley & Victor De Gruttola & Natasha K. Martin, , "Evaluation of SARS-CoV-2 Transmission Mitigation Strategies on a University Campus Using an Agent-Based Network Model," Mathematica Policy Research Reports, Mathematica Policy Research, number 51c58d1aed8e47a0ad7eefb3c.
• Xiaodong Wang & Fushing Hsieh, 2021, "Unraveling S&P500 stock volatility and networks -- An encoding-and-decoding approach," Papers, arXiv.org, number 2101.09395, Jan, revised Oct 2021.
• Ahlfeldt, Gabriel Peter Gabriel Martins & Albers, Thilo Nils Hendrix & Behrens, Kristian, 2020, "Prime locations," LSE Research Online Documents on Economics, London School of Economics and Political Science, LSE Library, number 108470, Oct.
• Aref Mahdavi Ardekani, 2020, "Liquidity, Interbank Network Topology and Bank Capital," Documents de travail du Centre d'Economie de la Sorbonne, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne, number 20022r, Oct, 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, arXiv.org, number 2101.09394, Jan, 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, arXiv.org, number 2101.08984, Jan, revised Feb 2022.
• Mark Kiermayer, 2021, "Modeling surrender risk in life insurance: theoretical and experimental insight," Papers, arXiv.org, number 2101.11590, Jan, 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, KOF Swiss Economic Institute, ETH Zurich, number 20-484, Jun, DOI: 10.3929/ethz-b-000423548.
• Jeffrey Grogger & Ria Ivandic & Tom Kirchmaier, 2020, "Comparing conventional and machine-learning approaches to risk assessment in domestic abuse cases," CEP Discussion Papers, Centre for Economic Performance, LSE, number dp1676, Feb.

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. 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: