Abstract:
An approach to forecasting consumer demand based on generalized non-parametric method is developed. Necessary and sufficient conditions for trading statistics to be in a correspondence with the inverse function of demand, satisfying the Law of Demand were found. Warshall-Floyd algorithm verifies these conditions. This algorithm has polynomial complexity over the number of trading statistics points of time. Demand forecasting technique based on the analysis of trading statistics rationalization and the Law of Demand feasibility is suggested.
Citation:
V. A. Grebennikov, A. A. Shananin, “Generalized non-parametric method: the law of demand in prognosis problems”, Mat. Model., 20:9 (2008), 34–50; Math. Models Comput. Simul., 1:5 (2009), 591–604
This publication is cited in the following 2 articles:
Klemashev N.I., Shananin A.A., Zhang Sh., “Inverse Problems in Pareto'S Demand Theory and Their Applications to Analysis of Stock Market Crises”, J. Inverse Ill-Posed Probl., 26:1 (2018), 95–108
Klemashev N.I., Shananin A.A., “Inverse Problems of Demand Analysis and Their Applications to Computation of Positively-Homogeneous Konus-Divisia Indices and Forecasting”, J. Inverse Ill-Posed Probl., 24:4 (2016), 367–391