Self Organization in Complex Systems and New Problems in the Theory of Measurement

Malinetskii, Georgii Gennadyevich; Ахромеева, Татьяна Сергеевна

doi:10.1007/s11018-016-1011-4

Search citation statements

Order By: Relevance

Paper Sections

Select...

Introduction1

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2020

Publication Types

Select...

Other1

Relationship

Self Cite0

Independent1

Authors

Journals

Cited by 1 publication

(1 citation statement)

References 1 publication

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The new interdisciplinary study of complex systems, known as the complex networks theory, laid the foundation for a new network paradigm of synergetic [17]. The complex networks theory studies the characteristics of networks, taking into account not only their topology, but also statistical properties, the distribution of weights of individual nodes and edges, the effects of information dissemination, robustness, etc.…”

Section: Introductionmentioning

confidence: 99%

Complex networks theory and precursors of financial crashes

Soloviev¹,

Solovieva²,

Tuliakova³

et al. 2020

View full text Add to dashboard Cite

Based on the network paradigm of complexity in the work, a systematic analysis of the dynamics of the largest stock markets in the world and cryptocurrency market has been carried out. According to the algorithms of the visibility graph and recurrence plot, the daily values of stock and crypto indices are converted into a networks and multiplex networks, the spectral and topological properties of which are sensitive to the critical and crisis phenomena of the studied complex systems. This work is the first to investigate the network properties of the crypto index CCI30 and the multiplex network of key cryptocurrencies. It is shown that some of the spectral and topological characteristics can serve as measures of the complexity of the stock and crypto market, and their specific behaviour in the pre-crisis period is used as indicators- precursors of critical phenomena.

show abstract

Section: Introductionmentioning

confidence: 99%