• International Commerce and Information Review
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• v.12 no.4
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• pp.171-192
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• 2010

In general, a stock index and its individual stocks are assumed to follow a random walk. A stock index is an important source of information and one that is seen by people everyday, regardless of their investment intentions. This paper examines the correlation between the KOSPI-the index that best reflects the Korean stock market and the macro - economic variables that have been found to influence the index by previous studies. The sample period considers the years after 2000 when the Korean stock market matured as restrictions on foreign investors were removed. For this purpose, a Vector Error Correction Model (VECM) and KOSPI equation with a general pacific approach were used. This paper aims at verifying the factors that determined the KOSPI after 2000 and at examining whether there was structural change in the investment environment. It also investigates changes in the factors determining the KOSPI's performance as a result of structural changes in the investment environment. The V AR (Vector Autoregressive) model including the nine variables was selected as a baseline model whose stability was tested using the unit root test. The results from the VECM and the structural changes in the investment environment can be summarized by the following Inner story points.

• The Journal of Asian Finance, Economics and Business
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• v.5 no.4
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• pp.35-44
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• 2018

The study is aimed at investigating the main factors that affect the interest rate yields, in the long-term. In addition, the study surveys the theories and literature relating to the determinants of interest rate. The importance of which is essential not only for governments, but also for banks and corporate financial risk management decisions, including risk exposures in banks and capital markets. Interest rate influences corporate profit as well as growth. For this purpose, the study examines the impact of budget deficit, risk-free rate, capital inflows, money supply and business cycles on real interest rate in Jordan. These factors are based upon well-established theories and straightforward practical view as interest rate determinants. Using data for (1990-2015), the study employed Johansen's co-integrating test, which takes into consideration the long-term unsynchronized relationships. The data is tested for normality, symmetric correlations, covariance diagonal and unit root. The results show that the government budget deficit, short-term risk-free interest rate, capital inflows, money supply and business cycle are long-term determinants of the real interest rate in Jordan. The coefficients of government budget deficit, short-term risk-free rate, money supply and business cycle all are inversely affecting the real interest rate, while capital inflows has a positive impact on the real interest rate.

• Journal of Distribution Science
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• v.11 no.7
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• pp.15-22
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• 2013

Purpose - The study investigates the influence of tourism and hospitality industry on economic growth and CO2 emissions. Research design, data, and methodology - In the empirical analysis, unit root tests, cointegration test and vector error correction model regression using time series data of South Korea from the first quarter of 1970 to the third quarter of 2010 are performed to examine the long-run equilibrium relationship and short-run dynamics among the tourism and hospitality industry, CO2 emissions, economic growth and other industry sectors. Results - Results indicate that a long-run equilibrium relationship exists among these variables. Furthermore, the tourism and hospitality industry and CO2 emissions have high significant positive effect on economic growth. The tourism and hospitality industry in Korea, in turns, shows a high significant positive impact on economic growth while the industry sector incursa high significant negative impact on CO2 emissions. Conclusions - The tourism and hospitality industry in Korea may havebeen prompted by several factors such as accelerated process of technological innovation or energy and environmental policies. These findings suggest that the effectively managed tourism and hospitality sector in Korea has resulted in both economic growth and a reduction in CO2 emissions.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.8
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• pp.705-714
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• 2020

This study aims to investigate the main factors that affected the government health expenditures in Gulf Cooperation Council (GCC) countries (Kingdom of Saudi Arabia (KSA), United Arab Emirates (UAE), Oman, Qatar, Bahrain and Kuwait), during the period from 2005 to 2019. The study employs a panel data technique in order to monitor the pooled determinant variables of healthcare expenditures in these countries. The study's results indicate, by using FMOLS approach for panel data, that the average healthcare expenditures per capita in GCC countries have a positive and a significant relationship with the government revenues, the size of the population, and the governments' public debt. The positive and the significant relationships of governments' public debt may be explained even if the governments of the GCC countries suffer from a budget deficit; the GCC countries continue to increase the healthcare expenditure. The study suggests that the policymakers of the GCC countries must take into consideration those variables when they develop their healthcare policies. Also, the GCC countries urgently need to have high levels of foreign exchange reserves to maintain the expected level of spending on the healthcare sector, because their public revenues depend mainly on the oil revenues, which are fluctuating continuously.

• The Korean Journal of Financial Management
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• v.16 no.2
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• pp.243-261
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• 1999

본 논문은 순이익의 시계열 속성을 조사하고, 순이익의 시계열이 랜덤워크 모형과 일치하는지를 단위근 검증방식을 사용하여 조사하며, 시계열 속성에 근거하여 도출된 예측모형과 흔히 사용되어 온 랜덤워크 모형의 예측능력을 비교하여 선행연구에서 사용되고 있는 랜덤워크 모형에 실증적 타당성을 제시하는 것을 주목적으로 하고 있다. 본 연구는 한국신용평가주식회사의 데이터 베이스에 1980년부터 1996년까지 17년간 자료가 연속적으로 포함되어 있는 금융기업을 제외한 모든 기업(272개)을 표본으로 사용하고 있다. 표본기업의 순이익 시계열에 가장 적합한 과정은 랜덤워크나 AR(1) 또는 AR(2) 모형이다. 또한 본 논문은 대부분의 기업에 때해 순이익이 랜덤워크 과정을 따른다는 가설을 기각할 수 없음을 보였다. 이들 상이한 모형의 표본외 예측력(out-of-sample predictive ability)을 비교한 결과 상수항을 포함한 랜덤워크 모형이 가장 작은 평균 절대 예측오차(mean absolute forecast error)를 갖는 것으로 나타나고 있다. 본 연구는 기존의 연구가 순이익 시계열의 불안정성(nonstationarity) 문제를 무시하거나 명시적으로 다루고 있지 않은 것과는 달리 단위근 검증(unit root test)을 통해 연간 순이익이 대체로 불안정하다는 것을 보였으며, 또한 상이한 모형의 표본외 예측능력을 비교한 결과 선행연구에서 사용하여 온 랜덤워크 모형의 우월성에 대한 실증적 증거를 제공하였다는 데 의의가 있다.

• The Korean Journal of Financial Management
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• v.26 no.2
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• pp.181-201
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• 2009

This study is on the forecasting performance analysis of range volatility estimators(Parkinson, Garman and Klass, and Rogers and Satchell) relative to historical one using two-scale realized volatility estimator as a benchmark. American sub-prime mortgage loan shock to Korean stock markets happened in sample period(January 2, 2006~March 10, 2008), so the structural change somewhere within this period can make a huge influence on the results. Therefore sample was divided into two sub-samples by May 30, 2007 according to Zivot and Andrews unit root test results. As expected, the second sub-sample was much more volatile than the first sub-sample. As a result of forecasting performance analysis, Rogers and Satchell volatility estimator showed the best forecasting performance in the full sample and relatively better forecasting performance than other estimators in sub-samples. Range volatility estimators showed better forecasting performance than historical volatility estimator during the period before the outbreak of structural change(the first sub-sample). On the contrary, the forecasting performance of range volatility estimators couldn't beat that of historical volatility estimator during the period after this event(the second sub-sample). The main culprit of this result seems to be the increment of range volatility caused by that of intraday volatility after structural change.

• Journal of Biosystems Engineering
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• v.29 no.1
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• pp.59-64
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• 2004

This study was performed to determine drying equations of sarcodon aspratus. Drying tests for sarcodon aspratus were conducted in an experimental dryer equiped with an air conditioning unit. The drying tests were performed at three air temperatures of 30$^{\circ}C$, 40$^{\circ}C$ and 50$^{\circ}C$, and two relative humidities of 30% and 50%. Measured moisture ratio data were fitted with the selected four drying models(Page, Thompson, Lewis and simplified diffusion models) using stepwise multiple regression analysis. When the coefficients of determination and root mean square errors of moisture ratio were evaluated for four drying models, the Page model was found to fit adequately to all the drying test data with coefficient of determination of 0.9996 and RMSE of 0.00523.

• Nuclear Engineering and Technology
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• v.41 no.9
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• pp.1181-1190
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• 2009

Knowing more about the Local Power Density (LPD) at the hottest part of a nuclear reactor core can provide more important information than knowledge of the LPD at any other position. The LPD at the hottest part needs to be estimated accurately in order to prevent the fuel rod from melting in a nuclear reactor. Support Vector Machines (SVMs) have successfully been applied in classification and regression problems. Therefore, in this paper, the power peaking factor, which is defined as the highest LPD to the average power density in a reactor core, was estimated by SVMs which use numerous measured signals of the reactor coolant system. The SVM models were developed by using a training data set and validated by an independent test data set. The SVM models' uncertainty was analyzed by using 100 sampled training data sets and verification data sets. The prediction intervals were very small, which means that the predicted values were very accurate. The predicted values were then applied to the first fuel cycle of the Yonggwang Nuclear Power Plant Unit 3. The root mean squared error was approximately 0.15%, which is accurate enough for use in LPD monitoring and for core protection that uses LPD estimation.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.12
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• pp.31-38
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• 2021

This study contributes to the existing literature and tries to analyze the validity of the Fisher hypothesis in the Philippines. Using monthly data from January 1995 to December 2020, the empirical analysis used the Engle-Granger and Johansen cointegration testing technique. The correlation coefficient suggests a strong positive association. All things being equal, a rise in inflation leads to a rise in the nominal interest rate. The unit-root tests show that inflation and the nominal interest rate are both stationary. Based on both Engle-Granger and cointegrating regression Durbin-Watson tests, the nominal interest rate and inflation are cointegrated. Likewise, the results from Johansen cointegration indicate that there exists a long-run relationship between the variables. However, we rejected a one-to-one relationship between nominal interest rate and inflation. The error correction term coefficient (ECM) shows that it is statistically significant suggesting that the nominal interest rate adjusts to the inflation rate with a lag. The Pair-wise Granger Causality test reported a bi-directional causal relationship between nominal interest rate and inflation. Inflation targeting has been the monetary policy framework of choice for most central banks. In essence, the conclusions of this study are useful to central banks because they help them better comprehend the long-run equilibrium relationship between the nominal interest rate and inflation.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.4
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• pp.173-183
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• 2022

The objective of this research is to examine the influence of the COVID-19 pandemic on stock markets in a few developing and developed countries. This study uses daily data from January 2020 to May 2021 and obtained from World Health Organization and Thomson Reuters. The secondary data was evaluated through panel econometric methodology that includes different unit root tests, and to analyze the long-run relationship between variables, panel cointegration techniques were applied. The long-run causality among variables was examined through Panel Vector Error Correction Model. The overall findings of this study suggest a long-run association exists between several cases and death with the stock returns of the GCC and other stock markets. Furthermore, the VECM model also identified a long-run causality running from COVID cases and death towards the stock rerun of both sets of stock markets. However, a subsequent Wald test yielded mixed results, indicating no short-run causality between cases and deaths and stock returns in both groups; however, in the case of GCC, several COVID-19 cases are having a causal impact on stock markets, which is notable in light of the fact that the death rate in GCC is significantly lower than in many developed and developing countries.