• 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.

• 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.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.1
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• pp.15-22
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• 2021

This study aims to obtain a stock investment strategy model based on the industrial sector in Indonesia Stock Exchange (IDX). This study uses IDX data for the period of January 1996 to December 2016. This study uses the Markov Regime Switching Model to identify trends in market conditions that occur in industrial sectors on IDX. Furthermore, by using the Logit Regression Model, we can see the influence of economic factors in determining trends in market conditions sectorally and the probability of trends in market conditions. This probability can be the basis for determining stock investment decisions in certain sectors. The results showed descriptively that the stocks of the consumer goods industry sector had the highest average return and the lowest standard deviation. The trend in sectoral stock market conditions that occur in IDX can be divided into two conditions, namely bullish condition (high returns and low volatility) and bearish condition (low returns and high volatility). Differences in the conditions are mainly due to differences in volatility. The use of a Logit Regression Model to produce probability of market conditions and to estimate the influence of economic factors in determining stock market conditions produces models that have varying predictive abilities.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.10
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• pp.49-59
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• 2022

This paper examined the impact of real exchange rate volatility on trade balance in Malaysia by using quarterly data from year 2000 until 2019. Generalized Autoregressive Heteroscedasticity (GARCH) model was used to extract the volatility component of real exchange rate before examining its impact on trade balance. Furthermore, Autoregressive Distributed Lag (ARDL) model was used to investigate the long-run relationship and short-run dynamic between trade balance, money supply, national income and volatility of exchange rate. Empirical results show the existence of co-movement between variables under study in the long-run. However, the results also suggest that volatility of real exchange rate does not significantly affect trade balance neither in the long-run nor short-run. The risk which is associated in the movement of exchange rate do not influence trader's behaviour toward Malaysia exports and imports. Thus, it should be note that any depreciation or appreciation in Malaysian Ringgit do not have an impact towards trade balance either it is being further improved or deteriorates. Hence, exchange rate volatility may not be too concern for policymakers. This may be partially due to manage floating exchange rate regime that has been adopted by Malaysia eventually eliminated the element of risk in the currency market.

• 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.

• 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.

• East Asian Journal of Business Economics (EAJBE)
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• v.3 no.4
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• pp.9-15
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• 2015

The exchange rate is a very important macro variable that has influence on the whole economy and has, therefore, been the topic of many discussions amongst policymakers, academics and other economic agents. The issue of whether to have a fixed, pegged or floating exchange rate regime was highly debated during the 1970s. The purpose of this paper is to investigate what factors determine the exchange rate in Somalia. Quantitative research methodology has been employed to develop regression model using time series data for the period of 12 years. The regression model has been developed based on Quantity theory of money, purchasing power parity and uncovered interest rate parity theory. Somalia is on the countries where the highest exchange rate volatility exists; for example in 2012, the rate jumped 29% percent and two weak later dropped 21%, when Turkish humanitarian aid agencies injected the market a lot of U.S dollar. Based on my study using regression model for time series data of 12 years, the four factors are mainly attributable for the exchange rate volatility of Somalia; these factors include the balance of payment, inflation rate, money supply (mostly come from remittance and NGOs) and Bank profits.

• 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.

• Asia-Pacific Journal of Business
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• v.11 no.4
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• pp.255-269
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• 2020

Purpose - This paper analyzes the market efficiency focusing on the long memory properties of the domestic futures market. By decomposing futures prices into yield and volatility and looking at the long memory properties of the time series, this study aims to understand the futures market pricing and change behavior and risks, specifically and in detail. Design/methodology/approach - This study analyzes KOSPI 200 futures, KOSDAQ 150 futures, 3 and 10-year government bond futures, US dollar futures, yen futures, and euro futures, which are among the most actively traded on the Korea Exchange. To analyze the long memory and market efficiency, we used the Variance Ratio, Rescaled-Range(R/S), Geweke and Porter-Hudak(GPH) tests as semi- parametric methods, and ARFIMA-FIGARCH model as the parametric method. Findings - It was found that all seven futures supported the efficiency market hypothesis because the property of long memory turned out not to exist in their yield curves. On the other hand, in futures volatility, all 7 futures showed long memory properties in the analysis, which means that if new information is generated in the domestic futures market and the market volatility once expanded due to the impact, it does not decrease or shrink for a long period of time, but continues to affect the volatility. Research implications or Originality - The results of this paper suggest that it can be useful information for predicting changes and risks of volatility in the domestic futures market. In particular, it was found that the long memory properties would be further strengthened in the currency futures and bond rate futures markets after the global financial crisis if the regime changes of the domestic financial market are taken into account in the analysis.

• The Journal of Asian Finance, Economics and Business
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• v.5 no.2
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• pp.25-33
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• 2018

In the globalization and free trade era, the current account deficit problem is a common phenomenon experienced by most countries, both developing and developed countries. Also with managed floating regime of exchange rate, it becomes very important to analyze the dynamics of current account balance which determine the trade. The deficit condition has lasted for four years in Indonesia, as well the deficit value above the value of the surplus that has been experienced during the period 2005-2011. This study is firstly aim to examine the condition of the deficit which happens in the export and import, manufactured goods and oil and gas, whether related to the transaction of goods and services. We try to build a predicted model which near the actual. Then, the focuses examines an exchange rate volatility impact on current account deficit. The model used in this research is a simultaneous model of Indonesia current account deficit from 2005 to 2014. The simulation result indicated that depreciation increase surplus to current account deficit. The decrease of export manufactured goods (non oil and gas) higher than the increase of import. For the oil and gas sector, depreciation of the rupiah against the US dollar results in an increased burden of higher oil and gas imports due to import transactions.