Disentangling global equity market instability: a network analysis

During a financial crisis, the capital markets network frequently exhibits a high correlation between returns. We developed a network analysis framework based on daily returns from 42 countries to determine systemic stability. Our network is built using the conditional probability of co-movement of...

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Bibliographic Details
Published in:arXiv.org 2022-01
Main Authors: Kamtue, Supanat, Luangaram, Pongsak, Woramongkhon, Sirawit
Format: Article
Language:English
Subjects:
Complexity
Conditional probability
Finance
Fragility
Network analysis
Nodes
Stability analysis
Systems stability
Volatility
Online Access:Get full text
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Summary:During a financial crisis, the capital markets network frequently exhibits a high correlation between returns. We developed a network analysis framework based on daily returns from 42 countries to determine systemic stability. Our network is built using the conditional probability of co-movement of returns, and it identifies nodes, network complexity, and edge as potential sources of fragility. We also introduce the concept of measuring flows from one return to another. Then, we use 120-day rolling data to capture the financial system's behavior and create a financial stability indicator. We discover that the contributions of nodes and network complexity to changes in system stability frequently cancel each other out. Edge change may be a determinant of systemic stability. Furthermore, the total flows in the network are highly correlated with the volatility. It main advantage is the tractability and potential sources of volatility can be determined.
ISSN:2331-8422