How Modern Financial Support Drives Innovative Urban Planning and Construction: Grey Relation Analysis

Li, Jianzhong; Wang, Mancang

doi:10.1108/ohi-01-2018-b0024

Cited by 2 publications

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“…The objective of this study is to propose an assignment model that integrates the Attribute Hierarchy Model (AHM) and the Intercriteria Correlation (CRITIC) coupling techniques for the development of a comprehensive FSI index. Firstly, the Gray Relation Analysis (GRA) is employed to calculate the grey integrated correlation among the constituent indicators of the FSI index, thereby assessing the strength of their relationships and eliminating redundant indicators [19]. In addition, the indicators were assigned weights using the AHM-CRITIC coupling model [20].…”

Section: Introductionmentioning

confidence: 99%

Systemic Financial Risk Forecasting: A Novel Approach with IGSA-RBFNN

Tian,

2024

Preprint

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Accurate measurement of systemic financial risk is critical to maintaining the stability of financial markets. Taking China as the subject of investigation, the Chinese Financial Stress Index (CFSI) indicator system was con-structed by integrating six dimensions and employing Gray Relation Analysis (GRA) for dimensionality reduction of the indicators. The CFSI was derived using the Attribute Hierarchy Model (AHM) method with the Criteria Importance Through the Intercriteria Correlation (CRITIC) method, and an Improved Gravitational Search Algorithm (IGSA) optimized Radial Basis Function Neural Network (RBFNN) was proposed for out-of-sample prediction of CFSI trends from 2024 to 2026. By analyzing the trend of financial pressure indicators, the relationship between financial pressure and economic activity can be effectively identified. The research findings indicate that: (1) The CFSI is capable of accurately reflecting the current financial stress situation in China; (2) The IGSA-RBFNN demonstrates good robustness and generalization capabilities, predicting that the CFSI index will reach a peak value of 0.543 by the end of 2024, and there exists a regular pattern of stress rebound towards the end of each year. The novel methodology benefits policymakers and regulatory authorities to formulate preventive measures and risk management by identifying potential risks and vulnerabilities in advance.

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Section: Introductionmentioning

confidence: 99%

Systemic Financial Risk Forecasting: A Novel Approach with IGSA-RBFNN

Tian,

2024

Preprint

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“…The objective of this study aims to propose an assignment model that integrates the AHM and CRITIC coupling techniques for the development of a comprehensive FSI index. Initially, the Gray Relation Analysis (GRA) is employed to calculate the grey integrated correlation among the constituent indicators of the FSI index, thereby assessing the strength of their relationships and eliminating redundant indicators [21]. Additionally, the indicators were assigned weights using the AHM-CRITIC coupling model [22].…”

Section: Introductionmentioning

confidence: 99%

Systemic Financial Risk Forecasting: A Novel Approach with IGSA-RBFNN

Tian,

2024

Mathematics

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Accurate measurement of systemic financial risk is crucial for maintaining the stability of financial markets. Taking China as the subject of investigation, the Chinese Financial Stress Index (CFSI) indicator system was constructed by integrating six dimensions and employing Gray Relation Analysis (GRA) to reduce the dimensionality of the indicators. The CFSI was derived using the Attribute Hierarchy Model (AHM) method with the Criteria Importance Through the Intercriteria Correlation (CRITIC) method, and an Improved Gravitational Search Algorithm (IGSA)-optimized Radial Basis Function Neural Network (RBFNN) was proposed for out-of-sample prediction of CFSI trends from 2024 to 2026. By analyzing the trends in financial pressure indicators, the intricate relationship between financial pressure and economic activity can be effectively discerned. The research findings indicate that (1) the CFSI is capable of accurately reflecting the current financial stress situation in China, and (2) the IGSA-RBFNN demonstrates strong robustness and generalization capabilities, predicting that the CFSI index will reach a peak value of 0.543 by the end of 2024, and there exists a regular pattern of stress rebound towards the end of each year. The novel methodology enables policymakers and regulatory authorities to proactively identify potential risks and vulnerabilities, facilitating the formulation of preventive measures.

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How Modern Financial Support Drives Innovative Urban Planning and Construction: Grey Relation Analysis

Cited by 2 publications

References 0 publications

Systemic Financial Risk Forecasting: A Novel Approach with IGSA-RBFNN

Systemic Financial Risk Forecasting: A Novel Approach with IGSA-RBFNN

Systemic Financial Risk Forecasting: A Novel Approach with IGSA-RBFNN

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