• East Asian mathematical journal
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• v.38 no.5
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• pp.617-641
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• 2022

In this study, we first present a brief overview of the Korean general insurance market. We then explore the characteristics of the loss ratios of the Korean general insurance industry and apply Markov regime-switching methodology to model the loss ratios of these insurance companies by line of business based on changes in economic regimes. This study applies a number of confirmatory tests such as Zivot-Andrews test (2002), the Chow (1960) test and the Bai and Perron (1998) to confirm the presence of structural breaks in the time series of the loss ratios by line of business. Then, we employ Markov regime-switching methodology to model these loss ratios. We find empirical evidence that the loss ratios reported by insurance companies in Korea is characterized by two distinct regimes; a regime with high volatility and a regime with low volatility, except for vehicle insurance. Our analyses suggest that macro-economic conditions have significant explanatory effect on loss ratios but the direction of effect differs based on the line of business and the regime. Unlike previous studies that have applied linear regressions or divided the samples into different periods and then apply linear regressions to model loss ratios, we argue for the application of Markov regime-switching methodology, which are able to automatically distinguish the different regimes that may be associated with the movements of loss ratios based on differing economic conditions and regulatory upheavals. This study provides a more in depth understanding of loss ratios in the general insurance industry and will be of value to insurance practitioners in modelling the loss ratios associated with their businesses to aid in their decision making. The results may also provide a basis for further studies in other markets apart from Korea as well as for shaping policy decisions related to loss ratios.

• Environmental and Resource Economics Review
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• v.13 no.3
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• pp.417-440
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• 2004

For the behavior of the wholesale spot price, a regime switching model with time-varying transition probabilities was estimated using the data from the PJM (Pennsylvania-New Jersey-Maryland) market. By including the temperature as an explanatory variable in the transition probability equations, the threshold effect of changing regime is clearly enhanced. And hence the predictability of the price spikes was improved. This means that the model showed a very clear threshold effect, with a low probability of switching for low loads and low temperatures and a high probability for high loads and high temperatures. And temperature showed a clearer threshold effect than load does. This implies that weather-related contracts may help to hedge against the risk in the cost of buying electricity during a summer.

• Journal of Korean Institute of Industrial Engineers
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• v.36 no.2
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• pp.101-107
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• 2010

Among a variety of asset dynamics models in order to explain the common properties of financial underlying assets, parametric models are meaningful when their parameters are set reliably. There are two main methods from which we can obtain them. They are to use time-series data of an underlying price or the market option prices of the underlying at one time. Based on the Girsanov theorem, in the pure diffusion models, the parameters calibrated from the option prices should be partially equivalent to those from time-series underling prices. We call this phenomenon model consistency. In this paper, we verify that the two-state regime switching Black-Scholes model is superior in the sense of model consistency, comparing with two popular conventional models, the Black-Scholes model and Heston model.

• Journal of Korean Institute of Industrial Engineers
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• v.42 no.4
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• pp.290-295
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• 2016

This paper proposes a new method for the automatic detection of atrial fibrillation (AF), using Markov regime switching GARCH (1, 1) model. The proposed method is based on the observation that variability patterns of heart rate intervals during AF significantly differ from regular patterns. The proposed method captures the different patterns of heart rate intervals between two regimes : normal and AF states. We test the proposed method using Massachusetts Institute of Technology-Beth Israel Hospital (MIT-BIH) atrial fibrillation database, and demonstrate the effectiveness of the proposed method.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.12
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• pp.63-73
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• 2021

This study investigates the key determinants of exchange rate (RER) misalignment for the period 1991 to 2020. The BEER technique has been used to estimate the degree of the equilibrium exchange rate. To explore the actual exchange rate misalignment and to assess the behavior of variables that are different in different regimes of undervaluation and overvaluation, the nonlinear technique of Markov regime-switching (MSM) was applied. The mean and variance of each regime are highly significant and show that undervaluation episodes have a low mean (116.139) and more volatility (1.229) while overvaluation episodes have a high mean (126.732) with less volatility (0.871). The findings show that MSM accurately identifies exchange rate misalignment in both regimes as separate incidents of overvaluation and undervaluation. Results further depict that misalignment of the RER is affected by terms of trade, net foreign assets, interest differential, government investment, and consumption decision. Results recommend that if policymakers want to use the exchange rate as a policy tool, they must first consider the drivers of the equilibrium exchange rate. As a result, any deliberate actions to address exchange rate misalignment must focus on the underlying fundamentals that drive the exchange rate.

• Journal of the Korean Magnetics Society
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• v.21 no.2
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• pp.48-51
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• 2011

We performed macro-spin simulation studies of the current-induced magnetization reversal of nanomagnetic elements with short current pulses. A special attention was paid to the effect of the energy barrier on the switching current distribution. The switching current and its distribution increase with decreasing the current pulse-width. The relationship between the energy barrier and switching current distribution is described by the Arrhenius-N$\'{e}$el law at a long pulse-width regime. At a regime of short pulse-width, however, the relationship is left unaddressed. The difficulty to address this issue arises because the magnetization switching with a short current pulse is governed not by the thermal activation but by the precession motion. Therefore, an exact formulation for the short pulse regime by solving the Fokker-Plank equation is needed to understand the result.

• Electronics and Telecommunications Trends
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• v.36 no.3
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• pp.34-40
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• 2021

For developing a switching device of a new concept that cannot be implemented with a semiconductor device, we introduce the Mott insulator-metal transition (IMT) phenomenon occurring out of the semiconductor regime, such as the temperature-driven IMT, the electric-field or voltage-driven IMT, the negative differential resistance (NDR)-IMT switching generated at constant current, and the NDR-based IMT-oscillation. Moreover, the possibilities of new concept IMT switching devices are briefly explained.

• The Korean Journal of Applied Statistics
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• v.28 no.3
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• pp.429-442
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• 2015

Volatility forecasting in financial markets is an important issue because it is directly related to the profit of return. The volatility is generally modeled as time-varying conditional heteroskedasticity. A generalized autoregressive conditional heteroskedastic (GARCH) model is often used for modeling; however, it is not suitable to reflect structural changes (such as a financial crisis or debt crisis) into the volatility. As a remedy, we introduce the Markov regime switching GARCH (MRS-GARCH) model. For the empirical example, we analyze and forecast the volatility of the daily Korea Composite Stock Price Index (KOSPI) data from January 4, 2000 to October 30, 2014. The result shows that the regime of low volatility persists with a leverage effect. We also observe that the performance of MRS-GARCH is superior to other GARCH models for in-sample fitting; in addition, it is also superior to other models for long-term forecasting in out-of-sample fitting. The MRS-GARCH model can be a good alternative to GARCH-type models because it can reflect financial market structural changes into modeling and volatility forecasting.

• Environmental and Resource Economics Review
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• v.31 no.3
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• pp.393-417
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• 2022

Using hourly SMP data from 2016 to 2020, this paper measures the weekly realized volatility and investigates the main force of its determinants. To this end, we extend the Bayesian variable selection by incorporating the regime-switching model which identifies important variables among a large number of predictors by regimes. We find that the increase in coal and nuclear generation, as well as solar power, reinforce the SMP volatility in both high volatility and low volatility regime. In contrast the increase in gas generation and gas price decrease SMP volatility when SMP volatility is high. These results suggest that the expansion of renewable energy according to 2050 Carbon Neutrality or energy transition policies increases SMP volatility but the increase in the gas generation or reduction of coal generation might offset its impact.

• 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.