Early Detection of Indonesian Financial Crisis Using Combination of Markov Regime Switching and Volatility Models
Keywords:
Early detect, financial crisis, financial indicators, markov regime switching, volatility modelsAbstract
The financial crisis is one of a serious problem which ever hit various countries in the world was no exception Indonesia. The financial crisis had occurred in Indonesia in 1997 to 1998, 2008, and 2020 which caused the economy of Indonesia was down. The impact caused by the financial crisis is very detrimental for Indonesia. Based on this problem, it is proved that the Indonesian government has not yet been optimized overcome a possible financial crisis. Therefore, an early detection system of financial crisis is required so that the crisis it can be solved immediately. Some of the economic indicators which able to detect crisis signals is output and bank deposits indicators because they have high fluctuation and regime changing during the crisis. The data used is secondary data from each indicators start in January 1990 until March 2021. Combination of markov regime switching and volatility models can be used to detect financial crisis. The volatility model can explain the volatility which included in the indicators, while markov regime switching model explain the regime changing of time series data. The results show that output and bank deposits indicators can be modelled using MRS-GARCH(1,1) and MRS-EGARCH(1,1). Based on the results of those two models also predicted that there is financial crisis signal in Indonesia in 2021 especially for output and bank deposits indicators.
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