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Report NEP-CMP-2019-08-12
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:
- Heinrich, Torsten & Sabuco, Juan & Farmer, J. Doyne, 2019, "A simulation of the insurance industry: The problem of risk model homogeneity," MPRA Paper, University Library of Munich, Germany, number 95096, Jul.
- Item repec:spo:wpmain:info:hdl:2441/1j4v8sl4fc9a49ankmnhv6bb6a is not listed on IDEAS anymore
- Magni, Carlo Alberto & Malagoli, Stefano & Marchioni, Andrea & Mastroleo, Giovanni, 2019, "Rating firms and sensitivity analysis," MPRA Paper, University Library of Munich, Germany, number 95265, Jul.
- Jian Liang & Zhe Xu & Peter Li, 2019, "Deep Learning-Based Least Square Forward-Backward Stochastic Differential Equation Solver for High-Dimensional Derivative Pricing," Papers, arXiv.org, number 1907.10578, Jul, revised Oct 2020.
- Mateo Dulce Rubio, 2019, "Predicting criminal behavior with Levy flights using real data from Bogota," Documentos de Trabajo, Quantil, number 17347, Apr.
- Elizabeth Jane Casabianca & Michele Catalano & Lorenzo Forni & Elena Giarda & Simone Passeri, 2019, "An Early Warning System for banking crises: From regression-based analysis to machine learning techniques," "Marco Fanno" Working Papers, Dipartimento di Scienze Economiche "Marco Fanno", number 0235, Aug.
- Martin Wiegand, 2019, "Do early-ending conditional cash transfer programs crowd out school enrollment?," Tinbergen Institute Discussion Papers, Tinbergen Institute, number 19-053/V, Jul.
- Teppei USUKI & Satoshi KONDO & Kengo SHIRAKI & Miki SUGA & Daisuke MIYAKAWA, 2019, "Using Machine Learning to Detect and Predict Corporate Accounting Fraud (Japanese)," Discussion Papers (Japanese), Research Institute of Economy, Trade and Industry (RIETI), number 19039, Jul.
- Olivier Gu'eant & Iuliia Manziuk & Jiang Pu, 2019, "Accelerated Share Repurchase and other buyback programs: what neural networks can bring," Papers, arXiv.org, number 1907.09753, Jul, revised Nov 2019.
- Zuzana Mucka, 2019, "The mirror does not lie: Endogenous fiscal limits for Slovakia," Working Papers, Council for Budget Responsibility, number Working Paper No. 2/2019, May.
- Schauder, Stephanie A. & Thomsen, Michael R. & Nayga, Rodolfo M., , "The Effect of the Fresh Fruit and Vegetable Program (FFVP) on Fruit and Vegetable Consumption: An Agent Based Modeling Approach," 2019 Annual Meeting, July 21-23, Atlanta, Georgia, Agricultural and Applied Economics Association, number 290942, DOI: 10.22004/ag.econ.290942.
- Alexis Bogroff & Dominique Guegan, 2019, "Artificial Intelligence, Data, Ethics: An Holistic Approach for Risks and Regulation," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers), HAL, number halshs-02181597, Jun.
- Lewis Gaul & Jonathan Jones & Pinar Uysal, 2019, "Forecasting High-Risk Composite CAMELS Ratings," International Finance Discussion Papers, Board of Governors of the Federal Reserve System (U.S.), number 1252, Jul, DOI: 10.17016/IFDP.2019.1252.
- Joseph Attia, 2019, "Evaluating the Effectiveness of Common Technical Trading Models," Papers, arXiv.org, number 1907.10407, Jul.
- Mustafa Caglayan & Tho Pham & Oleksandr Talavera & Xiong Xiong, 2019, "Asset mispricing in loan secondary markets," Discussion Papers, Department of Economics, University of Birmingham, number 19-07, Jul.
- Draca, Mirko & Schwarz, Carlo, 2019, "How Polarized are Citizens? Measuring Ideology from the Ground-Up," The Warwick Economics Research Paper Series (TWERPS), University of Warwick, Department of Economics, number 1218.
- Nassim Nicholas Taleb, 2019, "On the Statistical Differences between Binary Forecasts and Real World Payoffs," Papers, arXiv.org, number 1907.11162, Jul, revised Dec 2019.