PROBLEMS OF CRITICAL STUDY OF EVENTS OF MARKET PROCESSJournal: Herald of Kyiv National University of Trade and Economics (Vol.99, No. 1)
Publication Date: 2015-02-09
Authors : KARPOVYCH Andrii;
Page : 151-158
Keywords : model; market processes; trend forecasting; system condition analysis.;
Background. The relevance of research results is due to the ever increasing need of mankind to improve models predicting unsteady economic and market processes. The evolution of economic systems requires continuous improvement and refinement of existing laws of development. Consistent modeling of financial markets remains open and controversial issue. Analysis of recent research and publications showed that despite certain scientific achievements, important scientific and practical problem of forecasting critical events in the market process remains. The aim is to study the basic approaches to the analysis of market processes and develop a model of system status during the approach to critical events. Material and methods. The study used the following methods: statistical, graphical, function approximation of differential equations, mathematical and economic modeling, scientific abstraction. Results. Theoretical foundations of market processes modeling were studied. The model that describes the state of the market according to the hypothesis that the time of the evaluation of the current state of open systems (market trend) its resistance is inversely proportional to the speed limits change rates of contracts (surgical material process) per unit time was developed. One of the possible approaches to market processes modeling using models predicting the stability of the current market trend was offered. Conclusion. Based on the results of a number of statistical tests proposed model for evaluating the stability of market processes is an alternative to the models presented earlier. Among its advantages are scalability in time and a relatively small error of predictions within the 10?15% that is quite acceptable for probabilistic forecasting models of stochastic processes. This model is cross-functional for describing and predicting many economic processes similar to those described characteristics, making it promising for further exploration and development.
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