• Management & Information Systems Review
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• v.32 no.4
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• pp.189-207
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• 2013

Using high-frequency data for 2 years, this study investigates intraday lead-lag relationship between stock index and stock index futures markets in Korea and China. We found that there are some differences in price discovery and volatility transmission between Korea and China after the stock index futures markets was introduced. Following Stoll-Whaley(1990) and Chan(1992), the multiple regression is estimated to examine the lead-lag patterns between the two markets by Newey-West's(1987) heteroskedasticity and autocorrelation consistent covariance matrix(HAC matrix). Empirical results of KOSPI 200 shows that the futures market leads the cash market and weak evidence that the cash market leads the futures market. New market information disseminates in the futures market before the stock market with index arbitrageurs then stepping in quickly to bring the cost-of-carry relation back into alignment. The regression tests for the conditional volatility which is estimated using EGARCH model do not show that there is a clear pattern of the futures market leading the stock market in terms of the volatility even though controlling nonsynchronous trading effects. This implies that information in price innovations that originate in the futures market is transmitted to the volatility of the cash market. Empirical results of CSI 300 shows that the cash market is found to play a more dominant role in the price discovery process after the Chinese index started a sharp decline immediately after the stock index futures were introduced. The new stock index futures markets does not function well in its price discovery performance at its infancy stage, apparently due to high barriers to entry into this emerging futures markets. Based on EGAECH model, the results uncover strong bi-directional dependence in the intraday volatility of both markets.

• Asian Journal of Business Environment
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• v.12 no.3
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• pp.13-22
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• 2022

Purpose: The research aims to analyze the export performance of processed seaweed, its competitiveness, and determinants on seven main destination countries. Research design, data and methodology: The study uses data of seven main destination countries of Indonesian processed seaweed from 2010 to 2019. For competitiveness analysis, the study uses Revealed Comparative Advantage, Export Product Dynamics, and X-Model of Potential Export Product. Results: The study reveals that the export performance has decreased on all five countries except for Japan and USA. The X-Model analysis shows that the market classification has increased or been stable in every country except for Germany and France. GDP per capita of each destination country and competitiveness index have positive and significance effect while other factors have negative and significance effect. Conclusions: In 2019, Indonesia's processed seaweed market in Japan, United States, and France are on potential market, while Singapore and Italy are on optimistic market. In the future, Indonesia's processed seaweed export can be focused more on countries that have a good market potential. To improve the export volume, GDP per capita of destination country, and competitiveness index of Indonesian processed seaweed should be higher, while export price, economic distance, and real exchange rate should be lower.

• Journal of Fisheries and Marine Sciences Education
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• v.29 no.2
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• pp.560-569
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• 2017

With a remarkable and rapid change of universities in Korea, the role of universities has been changed from a traditional education supplier to a demander. Both the remarkable decrease of the number of entering students and the advent of an open education market are enforcing the universities to be changed. Universities should provide a variety of educational services in accordance with the students' needs. This study is based on the systematical Kuh's model which the educational service quality provide a decision making of alternative plan. This research is purposed to empirically study the effects of educational service quality(circumstance index, input index, participate index, output index) provided by universities on student satisfaction and educational performance(Perceived usefulness, Education Achievement). The results of this research follows; first, circumstance index, input index and output index significantly effect student satisfaction, but participate index does not effect satisfaction. Second, student satisfaction significantly effects on the educational performance.

• Journal of Intelligence and Information Systems
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• v.17 no.3
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• pp.187-201
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• 2011

KOSPI200 index is the Korean stock price index consisting of actively traded 200 stocks in the Korean stock market. Its base value of 100 was set on January 3, 1990. The Korea Exchange (KRX) developed derivatives markets on the KOSPI200 index. KOSPI200 index futures market, introduced in 1996, has become one of the most actively traded indexes markets in the world. Traders can make profit by entering a long position on the KOSPI200 index futures contract if the KOSPI200 index will rise in the future. Likewise, they can make profit by entering a short position if the KOSPI200 index will decline in the future. Basically, KOSPI200 index futures trading is a short-term zero-sum game and therefore most futures traders are using technical indicators. Advanced traders make stable profits by using system trading technique, also known as algorithm trading. Algorithm trading uses computer programs for receiving real-time stock market data, analyzing stock price movements with various technical indicators and automatically entering trading orders such as timing, price or quantity of the order without any human intervention. Recent studies have shown the usefulness of artificial intelligent systems in forecasting stock prices or investment risk. KOSPI200 index data is numerical time-series data which is a sequence of data points measured at successive uniform time intervals such as minute, day, week or month. KOSPI200 index futures traders use technical analysis to find out some patterns on the time-series chart. Although there are many technical indicators, their results indicate the market states among bull, bear and flat. Most strategies based on technical analysis are divided into trend following strategy and non-trend following strategy. Both strategies decide the market states based on the patterns of the KOSPI200 index time-series data. This goes well with Markov model (MM). Everybody knows that the next price is upper or lower than the last price or similar to the last price, and knows that the next price is influenced by the last price. However, nobody knows the exact status of the next price whether it goes up or down or flat. So, hidden Markov model (HMM) is better fitted than MM. HMM is divided into discrete HMM (DHMM) and continuous HMM (CHMM). The only difference between DHMM and CHMM is in their representation of state probabilities. DHMM uses discrete probability density function and CHMM uses continuous probability density function such as Gaussian Mixture Model. KOSPI200 index values are real number and these follow a continuous probability density function, so CHMM is proper than DHMM for the KOSPI200 index. In this paper, we present an artificial intelligent trading system based on CHMM for the KOSPI200 index futures system traders. Traders have experienced on technical trading for the KOSPI200 index futures market ever since the introduction of the KOSPI200 index futures market. They have applied many strategies to make profit in trading the KOSPI200 index futures. Some strategies are based on technical indicators such as moving averages or stochastics, and others are based on candlestick patterns such as three outside up, three outside down, harami or doji star. We show a trading system of moving average cross strategy based on CHMM, and we compare it to a traditional algorithmic trading system. We set the parameter values of moving averages at common values used by market practitioners. Empirical results are presented to compare the simulation performance with the traditional algorithmic trading system using long-term daily KOSPI200 index data of more than 20 years. Our suggested trading system shows higher trading performance than naive system trading.

• Journal of the Korean Operations Research and Management Science Society
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• v.40 no.2
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• pp.1-17
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• 2015

In this paper, we propose a portfolio selection model utilizing a Markov chain for investing in the foreign exchange market based on market forecasts and exchange rate movement predictions. The proposed model is utilized to compute optimum investment portfolio weights for investing in margin-based markets such as the FX margin market. We further present an objective investment algorithm for applying the proposed model in real-life investments. Empirical performance of the proposed model and investment algorithm is evaluated by conducting an experiment in the FX market consisting of the 7 most traded currency pairs, for a period of 9 years, from the beginning of 2005 to the end of 2013. We compare performance with 1) the Dollar Index, 2) a 1/N Portfolio that invests the equal amount in the N target assets, and 3) the Barclay BTOP FX Index. Performance is compared in terms of cumulated returns and Sharpe ratios. The results suggest that the proposed model outperforms all benchmarks during the period of our experiment, for both performance measures. Even when compared in terms of pre- and post-financial crisis, the proposed model outperformed all other benchmarks, showing that the model based on objective data and mathematical optimization achieves superior performance empirically.

• Korean Management Science Review
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• v.32 no.4
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• pp.57-67
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• 2015

It is a familiar Wall Street adage that "It takes volume to make prices move." Numerous researches have found the positive correlation between trading volume and price changes. Recent studies have documented that informed traders have strong influences on stock market prices through their trading with distinctive information power. Ever since 1992 capital market liberalization in Korea, it is said that foreign investors make consistent profits with their superior information and analytical skills. This study aims at whether we can make a profitable trading strategy by using the foreign investors' trading information. We analyse the relation between the KOSPI index returns and the foreign investors trading volume using GARCH models and VAR models. This study suggests the profitable trading strategies based on the documented relation between the foreign investors' trading volume and KOSPI index returns. We simulate the trading system with the real stock market data. The data include the daily KOSPI index returns and foreign investors' trading volume for 2001~2013. We estimate the GARCH and VAR models using 2001~2011 data and simulate the suggested trading system with the remaining out-of-sample data. Empirical results are as follows. First, we found the significant positive relation between the KOSPI index returns and contemporaneous foreign investors' trading volume. Second, we also found the positive relation between the KOSPI index returns and lagged foreign investors' trading volume. But the relation showed no statistical significance. Third, our suggested trading system showed better trading performance than B&H strategy, especially trading system 2. Our results provide good information for uninformed traders in the Korean stock market.

• The Journal of Asian Finance, Economics and Business
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• v.2 no.4
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• pp.5-11
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• 2015

This study is the first to analyze performance of Taiwanese domestic equity funds between January 2009 and October 2014, the period during which quantitative redirected capital flows toward developing economies and the Taiwanese Stock Exchange Weighted Index compounded at approximately 12.9% annually. Adopting methods endorsed by earlier research, we evaluated 15 Taiwanese equity funds' performance relative to market averages using the Sharpe (1966) and Treynor (1965) ratios and Jensen's alpha method (1968). To test market timing proficiency, we applied the Treynor and Mazuy (1966) and Henriksson and Merton (1981) regression analysis methods. Jensen's alpha method (1968) was used to measure fund managers' stock selection skills. Results revealed that funds significantly under-performed Taiwan's average annual market return and demonstrated no exceptional stock-selection skills and market timing proficiency during the era of quantitative easing.

• The Journal of Industrial Distribution & Business
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• v.10 no.11
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• pp.49-56
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• 2019

Purpose: Corporate social responsibility is a self-regulating business model that helps a firm be socially accountable to the public. By practicing corporate social responsibility, firms can be conscious of the kind of impact they are having on all aspects of society, including economic, social, and environmental. Corporate social responsibility activities are not directly linked to increasing corporate performance and corporate value, but rather involve spending expenses. Based on these facts, this study verifies whether the effects of corporate social responsibility activities differ depending on the firm's situation. Research design, data and methodology: This study analyzed the effect of market competition on corporate social responsibility activities using logistic regression analysis on listed companies in the KOSPI and KOSDAQ for fiscal years 2014 through 2016. In this study, market competition was measured using the Herfindahl-Herschman Index(HHI). Higher HHI value can be interpreted as a lower degree of market competition. We also measured corporate social responsibility activities using the KEJI Index published by the Korea Economic Justice Institute (KEJI). If a firm-year is included in the top 200 companies of the KEJI Index, it is classified as a good corporate social responsibility activity firm. Results: We find that companies in less competitive market were not included in the KEJI Index. This result indicates that firms in the market with lower market competition perform less corporate social responsibility activities that incur costs. An additional analysis showed that there was a significant negative relationship between the market competition and the corporate social responsibility activity scores published by the KEJI Index. These result adds robustness to the result of the hypothesis that firms that have a monopolistic place in the market practice passive corporate social responsibility activities. Conclusions: The results show that managers of a firm in the lower market competition have a lower incentive to use limited resources for projects that are not directly related to revenue. The results of this study imply that corporate social responsibility activities vary according to the position of the business. Therefore, this study suggests that market investors should consider the degree of competition in the market when they evaluate corporate social responsibility activities.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.4
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• pp.1-9
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• 2021

UAE has rapidly developed into one of the leading global financial hubs, with significant transformations in its stock exchanges. In its attempt at economic diversification in the last two decades, the country has also taken a lead in the GCC region in introducing extensive reforms to attract FDI to the Emirates. However, oil price volatilities have posed a significant challenge to all oil-exporting countries. The main aim of this study is to explore the impact of economic diversification and oil price on the UAE stock market. The study applies Granger Causality and Vector Autoregressive Model on monthly Abu Dhabi stock exchange index, Dubai Fateh crude oil spot price, and FDI inflows during 2001-19. The short-term interbank rate has been included as a monetary policy variable. The results show a substantial difference between the two phases of reforms. Oil price and Abu Dhabi stock index show bidirectional relationship during 2001-09 but no causality was found during 2010-19. Furthermore, the second phase was characterized by unidirectional causation from FDI to ADX index. This study highlights FDI inflows as a key driver of stock market performance during the last decade and emphasizes the success of the intense reforms in the UAE initiated for the diversification of its economy.

• International Commerce and Information Review
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• v.12 no.1
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• pp.299-325
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• 2010

The purpose of this empirical study is an index to usage of export assistance programs for korean small-medium exporters. Build around the index make an analysis of SMEs internal or exterior factors have an effect on export at present or in future export performance and the relative importance. Based on 128 surveys form korean SMEs experienced export assistance programs, 8 hypotheses, which are set up each factor, were verified through the practical analysis. The main result of hypothesis drawn by empirical study are as follows : The more SMEs use the programs, the more high export performance at present and in future. Export competitive factor reject at present export performance, but it will affect future export performance. A size of the firm in the characteristics of SEMs will affect export performance. Export rate of own brand will not affect performance. Another factors show adoption partly concerned hypothesis. Classified exterior factors of SMEs, a intensity of market competition shows adoption partly concerned hypothesis. Market growth rate will affect export performance at present and future strongly. Finally the usage of assistance programs will affect between a consumption goods and an industrial goods differently. From this study we found if we want to develop the export assistance programs that can actually in phases help the SEMs.