Report NEP-CMP-2023-01-16

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:

• Pierre Bras & Gilles Pag`es, 2022. "Langevin algorithms for Markovian Neural Networks and Deep Stochastic control," Papers 2212.12018, arXiv.org, revised Jan 2023.
• Harrison Mateika & Juannan Jia & Linda Lillard & Noah Cronbaugh & Will Shin, 2022. "Fallen Angel Bonds Investment and Bankruptcy Predictions Using Manual Models and Automated Machine Learning," Papers 2212.03454, arXiv.org, revised Dec 2022.
• Alessandro Gnoatto & Silvia Lavagnini & Athena Picarelli, 2022. "Deep Quadratic Hedging," Papers 2212.12725, arXiv.org, revised Nov 2024.
• Emmanuel Alanis & Sudheer Chava & Agam Shah, 2022. "Benchmarking Machine Learning Models to Predict Corporate Bankruptcy," Papers 2212.12051, arXiv.org.
• Marc Chataigner & Areski Cousin & St'ephane Cr'epey & Matthew Dixon & Djibril Gueye, 2022. "Beyond Surrogate Modeling: Learning the Local Volatility Via Shape Constraints," Papers 2212.09957, arXiv.org.
• Shuhua Xiao & Jiali Ma & Li Xia & Shushang Zhu, 2022. "Optimal Systemic Risk Bailout: A PGO Approach Based on Neural Network," Papers 2212.05235, arXiv.org.
• Jan Ditzen & Francesco Ravazzolo, 2022. "Dominant Drivers of National Inflation," Papers 2212.05841, arXiv.org.
• Piero Mazzarisi & Adele Ravagnani & Paola Deriu & Fabrizio Lillo & Francesca Medda & Antonio Russo, 2022. "A machine learning approach to support decision in insider trading detection," Papers 2212.05912, arXiv.org.
• Jiashu Lou & Leyi Cui & Ye Li, 2022. "Bi-LSTM Price Prediction based on Attention Mechanism," Papers 2212.03443, arXiv.org, revised Jun 2023.
• Pouriya Khalilian & Sara Azizi & Mohammad Hossein Amiri & Javad T. Firouzjaee, 2022. "Design interpretable experience of dynamical feed forward machine learning model for forecasting NASDAQ," Papers 2212.12044, arXiv.org.
• Alicia von Schenk & Victor Klockmann & Jean-Franc{c}ois Bonnefon & Iyad Rahwan & Nils Kobis, 2022. "Lie detection algorithms attract few users but vastly increase accusation rates," Papers 2212.04277, arXiv.org.
• Patrick Rehill & Nicholas Biddle, 2022. "Policy learning for many outcomes of interest: Combining optimal policy trees with multi-objective Bayesian optimisation," Papers 2212.06312, arXiv.org, revised Oct 2023.
• Kazuhiko Shinoda & Takahiro Hoshino, 2022. "Orthogonal Series Estimation for the Ratio of Conditional Expectation Functions," Papers 2212.13145, arXiv.org.
• Fierro, Luca Eduardo & Giri, Federico & Russo, Alberto, 2022. "Inequality-Constrained Monetary Policy in a Financialized Economy," MPRA Paper 115741, University Library of Munich, Germany.
• Chunmeng Yang & Siqi Bu & Yi Fan & Wayne Xinwei Wan & Ruoheng Wang & Aoife Foley, 2022. "Data-Driven Prediction and Evaluation on Future Impact of Energy Transition Policies in Smart Regions," Papers 2212.07019, arXiv.org.
• Berndt, Marvin & Hess, Sebastian, 2022. "Predicting Agricultural Trade Flows under the EU-Japan Free Trade Agreement: A Comparison of CGE Simulations and Gravity Regressions," 62nd Annual Conference, Stuttgart, Germany, September 7-9, 2022 329591, German Association of Agricultural Economists (GEWISOLA).
• Francesco Lamperti & Andrea Roventini, 2022. "Beyond climate economics orthodoxy: impacts and policies in the agent-based integrated-assessment DSK model," LEM Papers Series 2022/39, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
• Marco Di Francesco & Kevin Kamm, 2022. "CDO calibration via Magnus Expansion and Deep Learning," Papers 2212.12318, arXiv.org.