Inverse problems in Pareto's demand theory and their applications to analysis of stock market crises

We develop an approach to the analysis of stock market crises based on the generalized nonparametric method. The generalized nonparametric method is based on solvability and regularization of ill-posed inverse problem in Pareto's demand theory. Our approach allows one to select a few companies that may be considered as the main reason for the crisis. We apply this approach to study the Chinese stock market crash in 2015. © 2018 Walter de Gruyter GmbH, Berlin/Boston.

Authors
Klemashev N.I.1 , Shananin A.A. 1, 2, 3, 4 , Zhang S.5
Publisher
Walter de Gruyter GmbH
Number of issue
1
Language
English
Pages
95-108
Status
Published
Volume
26
Year
2018
Organizations
  • 1 Moscow Institute of Physics and Technology, Institutskiy per. 9, Dolgoprudny, Moscow Region, 141701, Russian Federation
  • 2 Dorodnicyn Computing Centre, FRC CSC RAS, Vavilov st. 40, Moscow, 119333, Russian Federation
  • 3 Moscow State University, Leninskiye Gory 1-52, Moscow, 119991, Russian Federation
  • 4 Department of Nonlinear Analysis and Optimization, RUDN University, Miklukho-Maklaya st. 6, Moscow, 117198, Russian Federation
  • 5 Coordinated Innovation Center for Computable Modeling in Management Science, Tianjin University of Finance and Economics, Tianjin, 300222, China
Keywords
demand theory; forecasting; Inverse problem; mathematical programming; revealed preference
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