The instability of the price dynamics of the energy market from a theoretical point of view indicates the inadequacy of the dominant paradigm of the quantitative description of pricing processes, and from a practical point of view, it leads to abnormal shocks and crashes. A striking example is the COVID-stimulated spring drop of spot prices for crude oil by 305% to $36.73 a barrel. The theory of complex systems with the latest complex networking achievements using pragmatically verified econophysical approaches and models can become the basis of modern environmental science. In this case, it is possible to introduce certain measures of complexity, the change in the dynamics of which makes it possible to identify and prevent characteristic types of critical phenomena. In this paper, the possibility of using some econophysical approaches for quantitative assessment of complexity measures: (1) informational (Lempel-Ziv measure, various types of entropies (Shannon, Approximate, Permutation, Recurrence), (2) fractal and multifractal (Multifractal Detrended Fluctuation Analysis), (3) recurrent (Recurrence Plot and Recurrence Quantification Analysis), (4) Lévy’s stable distribution properties, (5) network (Visual Graph and Recurrence based) and (6) quantum (Heisenberg uncertainty principle) is investigated. Each of them detects patterns that are general for crisis states. We conclude that these measures make it possible to establish that the socially responsive exhibits characteristic patterns of complexity and the proposed measures of complexity allow us to build indicators-precursors of critical and crisis phenomena. Proposed quantitative measures of complexity classified and adapted for the crude oil market. Their behavior in the face of known market shocks and crashes has been analyzed. It has been shown that most of these measures behave characteristically in the periods preceding the critical event. Therefore, it is possible to build indicators-precursors of crisis phenomena in the crude oil market.
This is an introductory text to a collection of selected papers from the M3E2 2019: The 8th International Conference on Monitoring, Modeling & Management of Emergent Economy, which was held in Odessa, Ukraine, on the May 22-24, 2019. It consists of short introducation and some observations about the event and its future.
The article deals with the method of calculating the fractal analysis, the time series of economic sustainability of the industrial enterprise on the trend-resistant sustainability were investigated by estimating the depth of the long-term memory of the time series and constructing a phase portrait. According to the approach used, the “depth of the long memory” is estimated in terms of fuzzy sets. The approach to the estimation of the index of economic stability is developed, based on the methods of forming an integrated indicator consisting of an assessment of such subsystems as the industrial and technical, financial-economic and subsystem of main parameters of the market environment. These helps to estimate the economic stability of the enterprise in the conditions of incomplete information from purpose of making effective management decisions. Combination of techniques for the formation of an integral index and a fractal analysis of the assessment of its trend stability showed an effective result, which was confirmed by the experiments.
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