A Robust Set of Indicators for the Financial Stress and Financial Stability: Taiwan’s Case Studies

Chau-Jung Kuo, Yu-Wei Li, Li-Hua Lai

Abstract


This study sets up a detective system for Taiwan’s financial stability with two spindles of the market-based and the bank-based, and uses “Two-state Markov regime-switching” method to capture the turning points from Taiwan’s previous major financial crises through the volatility of Taiwan’s financial stress index between 1997Q1 and 2014Q4. On this basis, a further study to propose the research of “a robust set of indicators for the Taiwan’s financial stability” uses “noise to signal ratio” method from the candidate variables of bank-based Taiwan’s financial stability, to filter out composite indicator of Taiwan’s financial stability with early warning functions as a supervisory tool for financial stability, effectively to detect and alert Taiwan’s financial crises. Empirical results proves, “two-state Markov regime-switching” method with the market-based Taiwan’s financial stress index (FSI), it sure can rationally determine the turning points for Taiwan’s previous major financial crises and successfully identify Asian financial crisis, dot-com bubble, cross-strait political-economic tensions, global financial crisis (GFC), European debt crisis, etc., especially to capture the financial crisis triggered by cross-strait political and economic tensions in 2004Q2, which completely reveals an individual characteristic of political sensitive gene in Taiwan’s financial system. Moreover, a composite indicator of Taiwan’s financial stability (CITFS) constructed by bank-based measure has a good early warning capability to detect the events of Taiwan’s previous major financial crises, and provide Taiwan’s financial supervisory authority some important reference to build up the financial early warning mechanism.

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DOI: https://doi.org/10.5430/ijfr.v7n1p172



This journal is licensed under a Creative Commons Attribution 4.0 License.


International Journal of Financial Research
ISSN 1923-4023(Print)ISSN 1923-4031(Online)

 

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