Report NEP-CMP-2019-11-25

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:

• Yu Zheng & Bowei Chen & Timothy M. Hospedales & Yongxin Yang, 2019. "Index Tracking with Cardinality Constraints: A Stochastic Neural Networks Approach," Papers 1911.05052, arXiv.org, revised Nov 2019.
• Theodoros P. Pantelidis & Joseph Y. J. Chow & Saeid Rasulkhani, 2019. "A many-to-many assignment game and stable outcome algorithm to evaluate collaborative Mobility-as-a-Service platforms," Papers 1911.04435, arXiv.org, revised Jun 2020.
• Sumitra Ganesh & Nelson Vadori & Mengda Xu & Hua Zheng & Prashant Reddy & Manuela Veloso, 2019. "Reinforcement Learning for Market Making in a Multi-agent Dealer Market," Papers 1911.05892, arXiv.org.
• Johannes Ruf & Weiguan Wang, 2019. "Neural networks for option pricing and hedging: a literature review," Papers 1911.05620, arXiv.org, revised May 2020.
• Mehran Azimi & Anup Agrawal, 2019. "Is Positive Sentiment in Corporate Annual Reports Informative? Evidence from Deep Learning," 2019 Papers paz108, Job Market Papers.
• Xiao, Tim, 2018. "Incremental Risk Charge Methodology," arabixiv.org qmcdz, Center for Open Science.
• Luca De Gennaro Aquino & Carole Bernard, 2019. "Bounds on Multi-asset Derivatives via Neural Networks," Papers 1911.05523, arXiv.org, revised Nov 2020.
• Ben Wealer & Simon Bauer & Leonard Göke & Christian von Hirschhausen & Claudia Kemfert, 2019. "Economics of Nuclear Power Plant Investment: Monte Carlo Simulations of Generation III/III+ Investment Projects," Discussion Papers of DIW Berlin 1833, DIW Berlin, German Institute for Economic Research.
• Mazur, Stepan & Otryakhin, Dmitry, 2019. "Linear Fractional Stable Motion with the RLFSM R Package," Working Papers 2019:9, Örebro University, School of Business.
• Andrew J Tiffin, 2019. "Machine Learning and Causality: The Impact of Financial Crises on Growth," IMF Working Papers 19/228, International Monetary Fund.
• R Verbelen & K Antonio & Gerda Claeskens & J Crevecoeur, 2018. "An EM algorithm to model the occurrence of events subject to a reporting delay," Working Papers Department of Accountancy, Finance and Insurance (AFI), Leuven 623951, KU Leuven, Faculty of Economics and Business (FEB), Department of Accountancy, Finance and Insurance (AFI), Leuven.
• Gary S. Anderson & Alena Audzeyeva, 2019. "A Coherent Framework for Predicting Emerging Market Credit Spreads with Support Vector Regression," Finance and Economics Discussion Series 2019-074, Board of Governors of the Federal Reserve System (U.S.).
• B. Shravan Kumar & Vadlamani Ravi & Rishabh Miglani, 2019. "Predicting Indian stock market using the psycho-linguistic features of financial news," Papers 1911.06193, arXiv.org.
• Tyler Pike & Horacio Sapriza & Tom Zimmermann, 2019. "Bottom-up Leading Macroeconomic Indicators: An Application to Non-Financial Corporate Defaults using Machine Learning," Finance and Economics Discussion Series 2019-070, Board of Governors of the Federal Reserve System (U.S.).
• Richard H. Clarida, 2019. "Introductory Remarks : a speech at \"Nontraditional Data, Machine Learning, and Natural Language Processing in Macroeconomics,\" a research conference sponsored by the Federal Reserve Board,," Speech 1088, Board of Governors of the Federal Reserve System (U.S.).
• Christophe HURLIN & Christophe PERIGNON, 2019. "Machine Learning et nouvelles sources de données pour le scoring de crédit," LEO Working Papers / DR LEO 2712, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
• Hammond, Peter J & Qiao, Lei & Sun, Yeneng, 2019. "Monte Carlo Sampling Processes and Incentive Compatible Allocations in Large Economies," The Warwick Economics Research Paper Series (TWERPS) 1229, University of Warwick, Department of Economics.
• Michael Dubrovsky & Marshall Ball & Bogdan Penkovsky, 2019. "Optical Proof of Work," Papers 1911.05193, arXiv.org, revised Feb 2020.
• Christoph March, 2019. "The Behavioral Economics of Artificial Intelligence: Lessons from Experiments with Computer Players," CESifo Working Paper Series 7926, CESifo.
• Jean-Michel Fayolle & Vincent Lemaire & Thibaut Montes & Gilles Pag`es, 2019. "Quantization-based Bermudan option pricing in the $FX$ world," Papers 1911.05462, arXiv.org, revised May 2020.
• Daniel Philps & Artur d'Avila Garcez & Tillman Weyde, 2019. "Making Good on LSTMs' Unfulfilled Promise," Papers 1911.04489, arXiv.org, revised Dec 2019.