• International Area Studies Review
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• v.12 no.3
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• pp.49-67
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• 2008

In this paper, we address the problem of optimal monetary policy rule in the presence of abrupt shifts in the structure of the economy. To do so, we first estimate a Markov switching model for the US housing price inflation, and find evidence supporting the presence of two distinct regimes for the US housing price inflation. One of the two regimes identified appears 'usual', in that housing price inflation negatively responds to higher real interest rate. The other regime is 'unusual', in that the housing price inflation is positively related with real interest rate. We then solve an optimal control problem of the FRB under the presence of the two regimes thus identified. The optimal policy is 'asymmetric' in that the optimal responses in the 'usual' regime require the FRB to lean against the wind to inflationary pressure, while the FRB is recommended to accommodate it in the unusual regime. It is also found that the optimal degree of responses is more conservative when the FRB acknowledges the uncertainty about future regime.

• Journal of the Korean Data and Information Science Society
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• v.28 no.4
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• pp.843-851
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• 2017

The rise of the Robo-advisor represents one of the most profound shifts in FinTech. It also raises concerns about their financial management. As the most Robo-Advisors utilize ETFs, we seek to determine the appropriate risk management model in estimating 95% Value-at-Risk (VaR) and 99% VaR in this paper. The GARCH and the Markov regime wwitching GARCH are evaluated in terms of the accuracy of probability, the independence of extreme events occurrence and both. The result shows that the Markov regime switching GARCH can be a good ETF risk management tool since it can reflect financial market structural changes into the volatility.

• The Korean Journal of Financial Management
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• v.21 no.2
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• pp.183-209
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• 2004

This paper uses both the bivariate GARCH type BEKK error correction model and Bivariate-AR(1)-Markov-Switching-VECM model to estimate the volatility, time-varying correlation and hedge ratio for the KTB spot and futures indexes, sampled daily over 1/4/2000-10/30/2003. This study suggests that the volatility regime has more significant influence on KTB markets than incline/decline regime does. The results support the importance of the bivariate model in stead of univariate model between KTB spot and futures markets, which may consider not only individual variance process but also covariance process at the same time.

• The Korean Journal of Applied Statistics
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• v.36 no.1
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• pp.85-100
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• 2023

The stochastic volatility (SV) model is one of the main methods of modeling time-varying volatility. In particular, SV model is actively used in estimation and prediction of financial market volatility and option pricing. This paper attempts to model the time-varying volatility of the bitcoin market price using SV model. Hidden Markov model (HMM) is combined with the SV model to capture characteristics of regime switching of the market. The HMM is useful for recognizing patterns of time series to divide the regime of market volatility. This study estimated the volatility of bitcoin by using data from Upbit, a cryptocurrency trading site, and analyzed it by dividing the volatility regime of the market to improve the performance of the SV model. The MCMC technique is used to estimate the parameters of the SV model, and the performance of the model is verified through evaluation criteria such as MAPE and MSE.

• The Journal of Economics, Marketing and Management
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• v.12 no.4
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• pp.27-36
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• 2024

Purpose: The paper analyzes for detecting unexpected shocks such as global financial crisis and COVID-19 pandemic, and contagion between countries by capturing in the mean-shift, variance-covariance-shift, and skewness-coskewness-shift parameters of interest rates. Research design, data and methodology: A flexible multivariate model of interest rates is provided by allowing for regime switching and a joint skewed normal distribution. The model is applying to the structural breaks of crisis and contagion between the US and the selected global bond markets during the global financial crisis and COVID-19 pandemic, respectively. Inspection of the moment statistics weakly suggests a flight to safety to the US during the global financial crisis and to Canada during the COVID-19 pandemic. Results: The results indicate that risk averse investors had a higher risk appetite for the US and Canada assets during the crisis regimes, compared to their counterparts. Conclusions: The results show that coskewness contagion dominates correlation contagion, and coskewness contagion is significant for the Korea and Japan-US pairs for the global financial crisis and the Euro-US pair for the COVID-19 pandemic. All channels of structural breaks of crisis and contagion are significant when considered jointly, reinforcing the need to consider contagion and structural breaks during crises in a multivariate setting.

• Management & Information Systems Review
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• v.34 no.3
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• pp.17-39
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• 2015

This study examined the structural changes and volatility in the global stock markets using a Markov Regime Switching ARCH model developed by the Hamilton and Susmel (1994). Firstly, the US, Italy and Ireland showed that variance in the high volatility regime was more than five times that in the low volatility, while Korea, Russia, India, and Greece exhibited that variance in the high volatility regime was increased more than eight times that in the low. On average, a jump from regime 1 to regime 2 implied roughly three times increased in risk, while the risk during regime 3 was up to almost thirteen times than during regime 1 over the study period. And Korea, the US, India, Italy showed ARCH(1) and ARCH(2) effects, leverage and asymmetric effects. Secondly, 278 days were estimated in the persistence of low volatility regime, indicating that the mean transition probability between volatilities exhibited the highest long-term persistence in Korea. Thirdly, the coefficients appeared to be unstable structural changes and volatility for the stock markets in Chow tests during the Asian, Global and European financial crisis. In addition, 1-Step prediction error tests showed that stock markets were unstable during the Asian crisis of 1997-1998 except for Russia, and the Global crisis of 2007-2008 except for Korea and the European crisis of 2010-2011 except for Korea, the US, Russia and India. N-Step tests exhibited that most of stock markets were unstable during the Asian and Global crisis. There was little change in the Asian crisis in CUSUM tests, while stock markets were stable until the late 2000s except for some countries. Also there were stable and unstable stock markets mixed across countries in CUSUMSQ test during the crises. Fourthly, I confirmed a close relevance of the volatility between Korea and other countries in the stock markets through the likelihood ratio tests. Accordingly, I have identified the episode or events that generated the high volatility in the stock markets for the financial crisis, and for all seven stock markets the significant switch between the volatility regimes implied a considerable change in the market risk. It appeared that the high stock market volatility was related with business recession at the beginning in 1990s. By closely examining the history of political and economical events in the global countries, I found that the results of Lamoureux and Lastrapes (1990) were consistent with those of this paper, indicating there were the structural changes and volatility during the crises and specificly every high volatility regime in SWARCH-L(3,2) student t-model was accompanied by some important policy changes or financial crises in countries or other critical events in the international economy. The sophisticated nonlinear models are needed to further analysis.

• Communications of the Korean Mathematical Society
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• v.21 no.2
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• pp.375-384
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• 2006

We consider a class of bilinear models with periodic regime switching and find easy-to-check sufficient conditions that ensures the existence of a stationary process obtained from given difference equation. Existence of a higher order moments is examined.

• Environmental and Resource Economics Review
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• v.29 no.2
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• pp.171-194
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• 2020

We revisit the impact of oil shocks on the Korean economy and examine how this impact varies depending on a business cycle. First, we estimate the probability of a recession through a logistic probability distribution, and correct the probability to match business cycles announced by the Korea National Statistical Office. We set up a STVAR model to analyze the response of macroeconomic variables to oil shocks according to business cycles. We find that oil shocks during the recession have a negative effect on GDP in the mid- and long-term, but during the expansion, GDP does not show a statistically significant response to oil shocks. We presume that this finding is associated with the factors of both the increase in demand for consumption and the increase in current account during the economic boom. Also, we find that the impact of oil shocks on the price level was also observed differently in terms of the persistence of inflation by business cycle. These results highlight the importance of an application of a regime switching model, which has been widely used in energy economics in recent years.

• Management & Information Systems Review
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• v.38 no.1
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• pp.181-199
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• 2019

The purpose of this study is to examine whether or not the volatility of the 1997~1998 Asian crisis still affects the monthly stock returns of Korea, Japan, Singapore, Hong Kong and China from 1980 to 2018. This study investigated whether the volatility has already fallen to pre-crisis levels. To illustrate the possible structural changes in the unconditioned variance due to the Asian financial crisis, we use the MRS-GARCH model, which is a regime switching model. The main results of this study were as follows: First, the stock return of each country was weak in the high volatility regime except Japan resulted by the Asian financial crisis from 1997 to 1998 until March 2018, and the Asian stock market has not yet calmed down except for the global financial crisis period of 2007 and 2008. Second, the conditional volatility has been significantly and persistently decreased and eliminated after the Asian financial crisis. Thus, we could be judged that the Asian stock market was not fully recovered(stable) due to the Asian crisis including the capital liberalization high inflation, worsening current account deficit, overseas low interest rates and expansion of credit growth in 1997 and 1998, but the Asian stock market was largely settled down, except for the 2007 and 2008 in Global financial crises. Considering the similarity between the Asian stock markets and the similar correlation of the regime switching, it may be worthwhile to analyze the MRS-GARCH model.

• International Area Studies Review
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• v.15 no.3
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• pp.55-76
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• 2011

In this paper, we estimate a model that incorporates key features of business cycles, co-movement among economic variables and switching between regimes of expansion and recession, to aggregate quarterly data for the NAFTA region. Two common factors reflecting the permanent and transitory components of the business cycle in the region, along with the turning points from one regime to the other, were extracted from the data by using the Kalman filter and maximum likelihood estimation approach of Kim (1994). Estimation results confirm that a typical aspect of business cycles are also observed (i.e., recessions are steeper and shorter than recoveries) in the region, and that both co-movement and that regime switching are found to be important features of the business cycle. The two common factors produce sensible representations of the trend and cycle, and the estimated turning points are in line with independently determined chronologies. It also turns out that the degree of synchronization between the NAFTA region and Korea, has significantly increased since the entry into force of the NAFTA.