• The Korean Journal of Financial Management
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• v.20 no.1
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• pp.125-162
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• 2003

This paper investigates the short- and long- run relationship among Korean, U.S. and Japanese construction indices. We conducted the Johansen's cointegration tests on the hypotheses that the construction indices of three countries we related in the long-run as well as in the short-run. The test results show that there exists no long-run relationship among three countrie's construction indices. In addition, the cointegrating relation did not exist for three countrie's stock market indices and five major Korean construction firms. It fumed out that the U.S. indices Granger-causes Japanese and Korean indices. This finding implies that there may exist international diversification benefit through forming a portfolio from these indices.

• Korea Trade Review
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• v.48 no.1
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• pp.127-163
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• 2023

The objective of this study is to investigate the volatility spillover effects among BDI, CCFI and SCFI. This paper will divide the empirical analysis section into two periods to analyze and compare the differences in volatility spillover effect between shipping freight indices before and after the outbreak of COVID-19 separately. First, in order to compare the mean spillover impact and index lead-lag correlations in BDI and CCFI indices, along with BDI and SCFI indices before and after COVID-19, the co-integration analysis and the test of Granger causality built on the VAR model were utilized. Second, the impulse response and variance decomposition are employed in this work to investigate how the shipping freight index responds to shocks experienced by itself and other freight indices in a short period. Before the COVID-19 epidemic, the results demonstrated that the BDI freight index is the Granger cause of the variable CCFI freight index. But the BDI and CCFI freight indices have no apparent lead-lag relationships after COVID-19, and this empirical result echoes the cointegration test result. After the COVID-19 epidemic, the SCFI index leads the BDI index. This study employs the VAR-BEKK-GARCH joint model to explore the volatility spillover results between dry bulk and container transport markets before and after COVID-19. The empirical results demonstrate that after COVID-19, fluctuations in the BDI index still affect the CCFI index in the maritime market. However, there is no proof of a volatility spillover relationship between the BDI and SCFI after the COVID-19 epidemic. This study will provide an insight into the volatility relationship among BDI, CCFI and SCFI before and after the the COVID-19 epidemic occurred.

• The Korean Journal of Financial Management
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• v.20 no.2
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• pp.151-180
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• 2003

We examine the interdependence of the major Asia-Pacific stock markets including S&P 500, FTSE 100, Kualar Lumpur Composite, Straits Times, Hang Seng, NIKKEI 225 and KOSPI 200 from October 4, 1995 to March 31,2000. The analysis employs the vector-auto-regression, Granger causality, impulse response function and variance decomposition using daily returns on the national stock market indices. The findings in this paper indicate that the volatilities of all countries has grown after IMF crisis, while there is no significance in cointegration test of both total period and sub-periods. This result implies that investors are able to get abnormal returns by investment diversification according to the portfolio theory. We find that while the effect from NIKKEI 225 to others is relatively weak, the interdependence from S&P 500 to other countries is strong. Also we find that the strong effect from Straits Times to Hang Seng exists. This study suggests that there is slight feedback relation between KOSPI 200 and Kualar Lumpur Composite, Straits Times, Hang Seng stock market.

• The Korean Journal of Financial Management
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• v.24 no.4
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• pp.107-134
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• 2007

This paper tests the relationship among returns, volatilities, contracts and open interests of KOSPI 200 futures markets with the various dynamic models such as granger-causality, impulse response, variance decomposition and ARMA(1, 1)-GJR-GARCH(1, 1)-M. The sample period is from July 7, 1998 to December 29, 2005. The main empirical results are as follows; First, both contract change and open interest change of KOSPI 200 futures market tend to lead the returns of that according to the results of granger-causality, impulse response and variance decomposition with VAR. These results are likely to support the KOSPI 200 futures market seems to be inefficient with rejecting the hypothesis 1. Second, we also find that the returns and volatilities of the KOSPI 200 futures market are effected by both contract change and open interest change of that due to the results of ARMA(1,1)-GJR-GARCH(1,1)-M. These results also reject the hypothesis 1 and 2 suggesting the evidences of inefficiency of the KOSPI 200 futures market. Third, the study shows the asymmetric information effects among the variables. In addition, we can find the feedback relationship between the contract change and open interest change of KOSPI 200 futures market.

• Journal of Technology Innovation
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• v.11 no.1
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• pp.79-97
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• 2003

R&D expenditure of Korean firms has been increasing drastically since 1980 and occupied 84% of total R&D expenditure in 1994. After 1994, however, the growth rate of industry R&D expenditure has dropped below single digit. R&D concentration rate of upper 20 companies declined from 61.9% in 1999 to 49.8% in 2001. The technology trade balance has diverged by 2.8 billion dollars in 2000 compared to around 0.3 billion dollars in 1985. We find several reasons on declining the industry R&D growth rate in Korea. First, we carefully say there might be an crowding out effect in increasing government R&D investment from Granger causality test between industry R&D and government R&D. Second, the decreasing benefit of tax credit since 1992 on industry R&D expenditure has caused the decrease of industry R&D growth rate. Third, the type of R&D cost becomes to similar to matured countries type of cost, which means the portion of capital expenditure has been decreased since late of 1980s. Therefore, industry R&D growth rate gets to saturation point. We draw several policy implications from the changing structure of business R&D of Korean company. Firstly, to stimulate industry R&D investment Korean government needs to strengthen tax credit policy. Secondly, to induce foreign direct investment Korean government needs to establish technology infrastructures and high quality of manpower. To utilize foreign technology resources Korean government need to introduce global R&D program executed by foreign scientist as an Project Leader.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.3
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• pp.101-113
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• 2020

The study aims to investigate the existence of overconfidence bias in Vietnam, Thailand, and Singapore. This paper focuses on the Vietnam Stock Market and other two countries of ASEAN, namely Singapore and Thailand. Data was collected over the period from January 1, 2014 to December 31, 2018, daily returns for each of the securities. This paper uses the time series method, namely ADF test, Granger Causality and VAR approach to find evidences of the overconfidence effect in Vietnam in relation to some ASEAN markets. The results show similarities between the observed countries with slight variations, with focus on Vietnam market. In general concrete evidences of overconfidence were found in both Vietnamese and Singaporean markets, in which Singaporean investors show higher degree of overconfidence than Vietnamese investors. Overconfidence is not as clear in Thai market, however a direct causal link from increased returns to increased investor confidence was found. From the model deployed in the paper, there are reasons to conclude that Thai investors are under-confident. The findings of the study shed lights into the existence of overconfidence bias in Vietnam, Thailand, and Singapore on a comparative basis, provide more insights and implications for future research in this new and rising field of research.

• The Journal of Asian Finance, Economics and Business
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• v.4 no.2
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• pp.19-23
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• 2017

It is undisputable that crude oil and its price fluctuations are major components that affect most of the countries' economies. Recent studies have demonstrated that beside the impact that crude oil price fluctuations have on common macroeconomic indicators like gross domestic product (GDP), inflation rates, exchange rates, unemployment rate, etc., it also has a strong influence on stock markets and their performance. This relationship has been examined in a number of settings, but it is yet to be unraveled in the Omani context. Accordingly, the main purpose of this study is to examine the possible effect of the oil price fluctuations on stock price movements. The study applies Toda and Yamamoto's (1995) Granger non-causality test on the daily Oman stock index (Muscat Securities Market Index) and oil prices between the period of 2 January 2003 and 13 March 2016. The results indicated that the oil price fluctuations have a significant impact on stock index movements. However, the stock price movements do not have a significant impact on oil prices. These findings have significant implications not only for the Omani economy but also for the economy of similar countries, particularly in the Gulf Cooperation Council (GCC) countries. The latter should carefully consider their policies and strategies regarding crude oil production and the generated income allocation as it might potentially affect the financial markets performance in these countries.

• The Journal of Asian Finance, Economics and Business
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• v.6 no.4
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• pp.139-145
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• 2019

This study examines the dynamic linkages between food price inflation and its volatility in the context of Sri Lanka. The empirical evidence derived from the monthly data for the period from 2003M1 to 2017M12 for Sri Lanka. The relationship between inflation rate and inflation volatility has attracted more attention by theoretical and empirical macroeconomists. Empirical studies on the relationship between food inflation and food inflation variability is scarce in the literature. Food price inflation is defined as log difference of food price series. The volatility of a food price inflation is measured by conditional variance generated by the FIGARCH model. Preliminary analysis showed that food inflation is stationary series. Granger causality test reveals that food inflation seems to exert positive impact on inflation variability. We find no evidence for inflation uncertainty affecting food inflation rates. Hence, the findings of the study supports the Friedman-Ball hypothesis in both cases of consumer food price inflation and wholesale food price inflation. This implies that past information on food inflation can help improve the one-step-ahead prediction of food inflation variability but not vice versa. Our results have some important policy implications for the design of monetary policy, food policy thereby promoting macroeconomic stability.

• Proceedings of the Korea Contents Association Conference
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• 2006.05a
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• pp.43-46
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• 2006

This study examined the stock return co-movement among Korean digital contents industry, American NASDAQ, and Japanese NIKKEI225. This is to identify the reaction of Korean digital contents industry on the movement of foreign stock market. To investigate the co-movements, during the period of 1999 to 2005, daily logarithm difference returns of each stock market indices are tested by the methodology of Granger(1963, 1969)'s causality test. The positive influence from NASDAQ index to Korean digital contents industry index are found, but not vice versa. It means that the market value of firms in Korean digital contents industry affected by the movement of American NASDAQ market which composite with digital IT firms. However, the co-movements with NIKKEI225 did not found.

• Journal of the Korean Data and Information Science Society
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• v.23 no.6
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• pp.1093-1102
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• 2012

In this paper, we predicted the interest spread using the VAR (vector autoregressive) model. Variables used in the VAR model were selected among 56 domestic and foreign macroeconomic time series through crosscorrelation and Granger causality test. The performance of the VAR model was compared with the univariate time series model, AR (autoregressive) model, in view of MAPE (mean absolute percentage error) and RMSE (root mean square error) of forecasts for the last twelve months.