Pemodelan Deteksi Krisis Keuangan di Indonesia Berdasarkan Indikator M2/Cadangan Devisa

Aisyah Zahrotul Hidayah; Sugiyanto Sugiyanto; Isnandar Slamet

doi:10.31334/bijak.v16i2.511

Pemodelan Deteksi Krisis Keuangan di Indonesia Berdasarkan Indikator M2/Cadangan Devisa

Aisyah Zahrotul Hidayah, Sugiyanto Sugiyanto, Isnandar Slamet

Abstract

The banking crisis reflects the liquidity crisis and bankruptcy of banks in the financial system. The financial crisis that occurred in mid-1997 resulted in a financial crisis that had a severe impact on the Indonesian economy. This made it aware of the importance of building a financial crisis early detection system to prepare for a crisis. The crisis occurs due to several macroeconomic indicators undergoing structural changes (regimes) and contain very high fluctuations. Combined volatility models and Markov regime switching are very suitable for explaining crises. The M2/international reserves indicator from 1990 to 2018 was used to build a crisis model. The results showed that the Markov regime switching autoregressive conditional heteroscedasticity model MRS-ARCH(2,1) could explain the crisis that occurred in mid-1997. Based on this model, in the future the crisis might occur if the M2/international reserves indicator decreased minimum of 13%

Keywords

Crisis Detection; M2/International Reserves; Modeling; MRS-ARCH

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References

Bollerslev, T. 1986. Generalized Autoregressive Conditional Heteroscedacity. Journal of Econometrics, 31(3): 307–327.

Chang, K., Cho, K.Y. & Hong, M.-G. 2010. Stock Volatility , Foreign Exchange Rate Volatility and the Global Financial Crisis. Journal of Economic Research, 15: 249–272.

Engle, R.F. 1982. Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation. Econometrica, 50(4): 987.

Hamilton, J.D. 1989. A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle. Econometrica, 57(2): 357.

Hamilton, J.D. & Susmel, R. 1994. Autoregressive conditional heteroskedasticity and changes in regime. Journal of Econometrics, 64(1–2): 307–333.

Kaminsky, G., Lizondo, S. & Reinhart, C. 1997. Leading Indicators of Currency Crises. International Monetary Fund Working Paper No. 97/79.

Kawai, M., Newfarmer, R. & Schmukler, S. 2001. Crisis and Contagion in East Asia: Nine Lessons. The World Bank, Policy Research Working Paper Series: 2610. Washington DC.

Kim, C.J. & Nelson, C.R. 2017. State-Space Models with Regime Switching. The MIT Press.

Nelson, D.B. 1991. Conditional Heteroskedasticity in Asset Returns: A New Approach. Econometrica, 59(2): 347.

Sugiyanto, Zukhronah, E. & Sari, S.P. 2018a. Detection method of financial crisis in Indonesia using MSGARCH models based on banking condition indicators. Journal of Physics: Conference Series, 1025: 012118.

Sugiyanto, Zukhronah, E. & Setianingrum, M. 2018b. The detection of financial crisis using combination of volatility and markov switching models based on real output, domestic credit per GDP, and ICI indicators. Journal of Physics: Conference Series, 1025: 012115.

Tsay, R.S. 2010. Analysis of Financial Time Series. Wiley Series in Probability and Statistics. USA: John Wiley & Sons, Inc.

DOI: https://doi.org/10.31334/bijak.v16i2.511