Complexity analysis based on generalized deviation for financial markets

Li, Chao; Shang, Pengjian

doi:10.1016/j.physa.2017.12.035

Cited by 3 publications

(1 citation statement)

References 29 publications

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“…In order to avoid the fitting of data in exploratory factor analysis and confirmatory factor analysis, the sorted data is divided into two parts. 200 data pieces were used for search factor analysis, and 200 data pieces were used for detection factor analysis [21].…”

Section: Data Evaluationmentioning

confidence: 99%

Complexity of the Analysis of Financial Cloud Based on Fuzzy Theory in the Wisdom of Sustainable Urban Development

2021

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With the rapid growth of our country’s economy, fuzzy theory has become more and more widely used in the financial field. This research mainly explores the application of financial cloud based on fuzzy theory in the sustainable development of smart cities. This research will apply the related knowledge of fuzzy theory, combine the traditional information system risk assessment thought and cloud computing system risk assessment, and propose a series of risk assessment models for the cloud computing system. First, design a smart city model to analyze the potential security issues of the financial cloud computing system. The security level model of cloud computing establishes an index system for evaluation objects based on the level of the security model and uses expert evaluation methods to build models for all levels of the risk profile through the analysis-level process and establish a fuzzy relationship model for each evaluation object value. We objectively evaluate the smart city model based on the designed financial cloud platform. Then, specific statistical analysis is performed on the fuzzy relationship model corresponding to the weight value of the evaluation object, the calculation result is finally obtained, and the risk assessment report of the financial cloud computing system is provided. For every 2% increase in trade dependence, the informatization level of smart cities will drop by about 0.03% on average. The findings have long strengthened the overall coordinated development of the financial system, optimized the financial structure, improved development efficiency, promoted close integration of science and technology and finance, and played the role of government leader it was to fulfill. It shows that we need to maximize it and improve the informatization when building smart cities. The level of development is very important for accelerating urban construction.

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Section: Data Evaluationmentioning

confidence: 99%