Report NEP-CMP-2022-03-07

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:

• Taylan Kabbani & Fatih Enes Usta, 2022. "Predicting The Stock Trend Using News Sentiment Analysis and Technical Indicators in Spark," Papers 2201.12283, arXiv.org.
• Ron Kaniel & Zihan Lin & Markus Pelger & Stijn Van Nieuwerburgh, 2022. "Machine-Learning the Skill of Mutual Fund Managers," NBER Working Papers 29723, National Bureau of Economic Research, Inc.
• Carmina Fjellstrom, 2022. "Long Short-Term Memory Neural Network for Financial Time Series," Papers 2201.08218, arXiv.org.
• Krzysztof Rusek & Piotr Bory{l}o & Piotr Jaglarz & Fabien Geyer & Albert Cabellos & Piotr Cho{l}da, 2022. "RiskNet: Neural Risk Assessment in Networks of Unreliable Resources," Papers 2201.12263, arXiv.org, revised Jun 2023.
• Rahal, Charles & Verhagen, Mark D. & Kirk, David, 2021. "The Rise of Machine Learning in the Academic Social Sciences," SocArXiv gydve, Center for Open Science.
• Schmidt, Lorenz & Odening, Martin & Schlanstein, Johann & Ritter, Matthias, 2021. "Estimation of the Farm-Level Yield-Weather-Relation Using Machine Learning," 61st Annual Conference, Berlin, Germany, September 22-24, 2021 317075, German Association of Agricultural Economists (GEWISOLA).
• Chaofan Sun & Ken Seng Tan & Wei Wei, 2022. "Credit Valuation Adjustment with Replacement Closeout: Theory and Algorithms," Papers 2201.09105, arXiv.org, revised Jan 2022.
• Zhe Wang & Nicolas Privault & Claude Guet, 2021. "Deep self-consistent learning of local volatility," Papers 2201.07880, arXiv.org, revised Nov 2023.
• Shuo Sun & Wanqi Xue & Rundong Wang & Xu He & Junlei Zhu & Jian Li & Bo An, 2021. "DeepScalper: A Risk-Aware Reinforcement Learning Framework to Capture Fleeting Intraday Trading Opportunities," Papers 2201.09058, arXiv.org, revised Aug 2022.
• Koch, Bernard & Sainburg, Tim & Geraldo, Pablo & JIANG, SONG & Sun, Yizhou & Foster, Jacob G., 2021. "Deep Learning of Potential Outcomes," SocArXiv aeszf, Center for Open Science.
• Stephan Martin, 2022. "Estimation of Conditional Random Coefficient Models using Machine Learning Techniques," Papers 2201.08366, arXiv.org.
• Daoud, Adel & Jordan, Felipe & Sharma, Makkunda & Johansson, Fredrik & Dubhashi, Devdatt & Paul, Sourabh & Banerjee, Subhashis, 2021. "Using satellites and artificial intelligence to measure health and material-living standards in India," SocArXiv vf28g, Center for Open Science.
• Verhagen, Mark D., 2021. "Identifying and Improving Functional Form Complexity: A Machine Learning Framework," SocArXiv bka76, Center for Open Science.
• Celine de Quatrebarbes & Bertrand Laporte & Stéphane Calipel, 2021. "Fighting the soaring prices of agricultural food products. VAT versus Trade tariffs exemptions in a context of imperfect competition in Niger : CGE and micro-simulation approach," CERDI Working papers hal-03138369, HAL.
• Thompson, Jason & Zhao, Haifeng & Seneviratne, Sachith & Byrne, Rohan & Vidanaarachichi, Rajith & McClure, Roderick, 2021. "Improving speed of models for improved real-world decision-making," SocArXiv sqy8c, Center for Open Science.
• Ivan Letteri & Giuseppe Della Penna & Giovanni De Gasperis & Abeer Dyoub, 2022. "A Stock Trading System for a Medium Volatile Asset using Multi Layer Perceptron," Papers 2201.12286, arXiv.org.
• Bruno Mazorra & Victor Adan & Vanesa Daza, 2022. "Do not rug on me: Zero-dimensional Scam Detection," Papers 2201.07220, arXiv.org.
• Beck, Ben & Winters, Meghan & Nelson, Trisalyn & Pettit, Christopher & Saberi, Meead & Thompson, Jason & Seneviratne, Sachith & Nice, Kerry A & Zarpelon-Leao, Simone & Stevenson, Mark, 2021. "Developing urban biking typologies: quantifying the complex interactions of bicycle ridership, bicycle network and built environment characteristics," SocArXiv 8w7bg, Center for Open Science.
• Körtner, John & Bonoli, Giuliano, 2021. "Predictive Algorithms in the Delivery of Public Employment Services," SocArXiv j7r8y, Center for Open Science.
• Thackway, William & Ng, Matthew Kok Ming & Lee, Chyi Lin & Pettit, Christopher, 2021. "Building a predictive machine learning model of gentrification in Sydney," SocArXiv hkc96, Center for Open Science.
• Kresova, Svetlana & Hess, Sebastian, 2021. "Determinants of Regional Raw Milk Prices in Russia," 61st Annual Conference, Berlin, Germany, September 22-24, 2021 317051, German Association of Agricultural Economists (GEWISOLA).
• Daniel Levy & Tamir Mayer & Alon Raviv, 2022. "Economists in the 2008 Financial Crisis: Slow to See, Fast to Act," Working Paper series 22-04, Rimini Centre for Economic Analysis.
• Akey, Pat & Grégoire, Vincent & Martineau, Charles, 2021. "Price Revelation from Insider Trading: Evidence from Hacked Earnings News," SocArXiv qe6tu, Center for Open Science.
• Takanobu Mizuta, 2022. "Do new investment strategies take existing strategies' returns -- An investigation into agent-based models," Papers 2202.01423, arXiv.org.
• Prendergast, Michael, 2022. "Econometric Models for Computing Safe Withdrawal Rates," OSF Preprints jd2xg, Center for Open Science.
• Takanobu Mizuta & Isao Yagi & Kosei Takashima, 2022. "Instability of financial markets by optimizing investment strategies investigated by an agent-based model," Papers 2202.00831, arXiv.org.
• Ihsan Chaoubi & Camille Besse & H'el`ene Cossette & Marie-Pier C^ot'e, 2022. "Micro-level Reserving for General Insurance Claims using a Long Short-Term Memory Network," Papers 2201.13267, arXiv.org.
• Martin Guth, 2022. "Predicting Default Probabilities for Stress Tests: A Comparison of Models," Papers 2202.03110, arXiv.org.
• Zhiqin Zou & Arash Farnoosh & Tom Mcnamara, 2021. "Risk analysis in the management of a green supply chain," Post-Print hal-03181313, HAL.
• Jori Hoencamp & Shashi Jain & Drona Kandhai, 2022. "A semi-static replication approach to efficient hedging and pricing of callable IR derivatives," Papers 2202.01027, arXiv.org.
• Koichi Miyamoto, 2022. "Quantum algorithm for calculating risk contributions in a credit portfolio," Papers 2201.11394, arXiv.org.
• Morteza Taiebat & Elham Amini & Ming Xu, 2022. "Sharing Behavior in Ride-hailing Trips: A Machine Learning Inference Approach," Papers 2201.12696, arXiv.org.
• Yulin Liu & Luyao Zhang, 2022. "Cryptocurrency Valuation: An Explainable AI Approach," Papers 2201.12893, arXiv.org, revised Jul 2023.
• Gabriel Okasa, 2022. "Meta-Learners for Estimation of Causal Effects: Finite Sample Cross-Fit Performance," Papers 2201.12692, arXiv.org.
• Igor Nesiolovskiy, 2021. "Stock exchange shares ranking and binary-ternary compressive coding," Papers 2201.11507, arXiv.org.