Report NEP-CMP-2022-08-22

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:

• Zarak Jamal Khan, 2021. "Machine Learning: An Introduction for Economists," PIDE Webinar Brief 2021:62, Pakistan Institute of Development Economics.
• Badruddoza, Syed & Fuad, Syed M. & Amin, Modhurima, 2022. "Comparative Effectiveness of Machine Learning Methods for Causal Inference in Agricultural Economics," 2022 Annual Meeting, July 31-August 2, Anaheim, California 322452, Agricultural and Applied Economics Association.
• Jerinsh Jeyapaulraj & Dhruv Desai & Peter Chu & Dhagash Mehta & Stefano Pasquali & Philip Sommer, 2022. "Supervised similarity learning for corporate bonds using Random Forest proximities," Papers 2207.04368, arXiv.org, revised Oct 2022.
• Jimei Shen & Zhehu Yuan & Yifan Jin, 2022. "AlphaMLDigger: A Novel Machine Learning Solution to Explore Excess Return on Investment," Papers 2206.11072, arXiv.org, revised Dec 2022.
• Jungyu Ahn & Sungwoo Park & Jiwoon Kim & Ju-hong Lee, 2022. "Reinforcement Learning Portfolio Manager Framework with Monte Carlo Simulation," Papers 2207.02458, arXiv.org.
• Federico Mecchia & Marcellino Gaudenzi, 2022. "The dynamics of the prices of the companies of the STOXX Europe 600 Index through the logit model and neural network," Papers 2206.09899, arXiv.org.
• Charl Maree & Christian W. Omlin, 2022. "Balancing Profit, Risk, and Sustainability for Portfolio Management," Papers 2207.02134, arXiv.org.
• Emanuel Kohlscheen & Richhild Moessner, 2022. "Changing Electricity Markets: Quantifying the Price Effects of Greening the Energy Matrix," CESifo Working Paper Series 9807, CESifo.
• Emily Aiken & Guadalupe Bedoya & Joshua Blumenstock & Aidan Coville, 2022. "Program Targeting with Machine Learning and Mobile Phone Data: Evidence from an Anti-Poverty Intervention in Afghanistan," Papers 2206.11400, arXiv.org.
• Hans Buehler & Phillip Murray & Ben Wood, 2022. "Deep Bellman Hedging," Papers 2207.00932, arXiv.org, revised Jun 2024.
• Sylvia Klosin & Max Vilgalys, 2022. "Estimating Continuous Treatment Effects in Panel Data using Machine Learning with a Climate Application," Papers 2207.08789, arXiv.org, revised Sep 2023.
• Man-, ZuyiKeunZuyi Wang & Takagi, Chifumi & Kim, Man-Keun & Chung, Anh, 2022. "Uncover Drivers Influencing Consumers' WTP Using Machine Learning: Case of Organic Coffee in Taiwan," 2022 Annual Meeting, July 31-August 2, Anaheim, California 322150, Agricultural and Applied Economics Association.
• Alexey Kushnir & James Michelson, 2022. "Optimal Multi-Dimensional Auctions: Conjectures and Simulations," Papers 2207.01664, arXiv.org.
• Menna Hassan & Nourhan Sakr & Arthur Charpentier, 2022. "Government Intervention in Catastrophe Insurance Markets: A Reinforcement Learning Approach," Papers 2207.01010, arXiv.org.
• Bryan T. Kelly & Semyon Malamud & Kangying Zhou, 2022. "The Virtue of Complexity Everywhere," Swiss Finance Institute Research Paper Series 22-57, Swiss Finance Institute.
• Dimitrios Vamvourellis & Mate Attila Toth & Dhruv Desai & Dhagash Mehta & Stefano Pasquali, 2022. "Learning Mutual Fund Categorization using Natural Language Processing," Papers 2207.04959, arXiv.org.