• Journal of Industrial Convergence
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• v.20 no.2
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• pp.11-19
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• 2022

This study examines the role of economic uncertainty in stock price determination in the domestic stock market. To this end, we analyzed the relationship between economic uncertainty indices at home and abroad (USA, China) and stock returns for non-financial companies in Korea from January 2000 to 2017. For the analysis model, the 3-factor model of Fama and French (1992) and the 5-factor model including momentum and liquidity were used. As a result of the analysis, a portfolio with a high beta of economic uncertainty showed higher stock returns than a portfolio with a low beta. This was the same as the US analysis result. Also, the analysis results using the US uncertainty index were more significant than the regression analysis results using the Korean economic uncertainty index.

• The Korean Journal of Food And Nutrition
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• v.36 no.6
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• pp.588-604
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• 2023

This study was conducted to investigate whether there were differences in eco-friendly food, home meal replacement (HMR) purchases, and eating-out behavior according to the level of agri-food consumer competence. The data for the study were extracted from main food consumers (n=3,321) in the 2022 Food Consumption Behavior Survey. The competence index was divided into awareness-attitude-practice items, and three groups were classified by competence level. The results showed an agri-food consumer competency score of 70.62, with the highest score for awareness (73.96), followed by practice (69.28) and attitude (66.18). The frequency of purchasing eco-friendly food was higher in the excellent group compared to other groups, and quality and price satisfaction was higher with higher competency (p<0.001). Regarding HMR, the results showed that the shortage group had the lowest HMR consumption rate, and satisfaction decreased as competence decreased (p<0.001). The main reason for eating-out was to enjoy food in all groups (59.0%), followed by a lack of cooking time in the excellent group (15.7%) and hassle with food preparation in the moderate and shortage groups (17.3%, 16.6%) (p<0.001). In short, agri-food consumption competency showed differences by contents and components, and differences in food purchases and eating-out behavior by competency level were found.

• Asia-Pacific Journal of Business
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• v.15 no.2
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• pp.257-270
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• 2024

Purpose - The purpose of this study is to analyze the changes in the business environment, business conditions, and detailed indicators related to management of Korea's port industry companies as global supply chains have been reorganized since the shock of COVID-19 in 2020 and uncertainties in the global economy have expanded. Design/methodology/approach - This study use the business survey index of the port industry to analyze. It is a weighted BSI with the weight of workers applied. Findings - Since 2020 the BSI in the port industry including business conditions, sales unit price, profitability, and financial conditions fluctuated, but it has been generally above normal level(100). During the analysis period, the BSI for export sales was found to be better than that of domestic sales. Employment BSI was generally stable, and in the case of facility BSI, the port industry was shown to be very active in facility investment. Research implications or Originality - First, it is necessary to make manpower training systems to cultivate experts in the port industry to cope with uncertainties caused by the rapidly changing global economy and the global supply chain environment. Second, it is necessary to support for investment in technology and facilities for automation and smartization. Finally, it is necessary to establish a continuous monitoring system for the business conditions.

• The Korean Journal of Financial Management
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• v.22 no.1
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• pp.71-91
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• 2005

The object or this paper is to analyze the rollover effect on KOSPI 200 index option prices. Especially we analyze the implied volatilities of the options that became the near maturity options as the old one expired. For this analysis, a panel data of KOSPI 200 Index Option Prices from year 1999 to year 2001 were used, and following results were obtained. First, after controlling for the underlying index returns, strike prices and other pricing factors, the call option prices tend to decrease while the put option prices tend to increase during the week of expiry. Second, if one concentrates on the daily price changes, call option prices tend to go up on Thursday (as the old options expire), and then experience a price decrease on the following day, while the reverse is true for the put options. These results imply that the option prices are affected by some of the market micro-structure effects such as whether the option is the near maturity option. We conjecture that the reason for this is related to the undervaluation of KOSPI 200 futures. The results from this paper have implications on the timing of option trades. If one wants to buy put options, and/or sell call options, he has better off by executing his intended trades before the old options expire. On the other hand, if one wants to buy call options, and/or sell put options, hi has better off by executing his intended trades after the expiry.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.59-71
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• 2014

System trading is becoming more popular among Korean traders recently. System traders use automatic order systems based on the system generated buy and sell signals. These signals are generated from the predetermined entry and exit rules that were coded by system traders. Most researches on system trading have focused on designing profitable entry and exit rules using technical indicators. However, market conditions, strategy characteristics, and money management also have influences on the profitability of the system trading. Unexpected price deviations from the predetermined trading rules can incur large losses to system traders. Therefore, most professional traders use strategy portfolios rather than only one strategy. Building a good strategy portfolio is important because trading performance depends on strategy portfolios. Despite of the importance of designing strategy portfolio, rule of thumb methods have been used to select trading strategies. In this study, we propose a SVM-based strategy portfolio management system. SVM were introduced by Vapnik and is known to be effective for data mining area. It can build good portfolios within a very short period of time. Since SVM minimizes structural risks, it is best suitable for the futures trading market in which prices do not move exactly the same as the past. Our system trading strategies include moving-average cross system, MACD cross system, trend-following system, buy dips and sell rallies system, DMI system, Keltner channel system, Bollinger Bands system, and Fibonacci system. These strategies are well known and frequently being used by many professional traders. We program these strategies for generating automated system signals for entry and exit. We propose SVM-based strategies selection system and portfolio construction and order routing system. Strategies selection system is a portfolio training system. It generates training data and makes SVM model using optimal portfolio. We make $m{\times}n$ data matrix by dividing KOSPI 200 index futures data with a same period. Optimal strategy portfolio is derived from analyzing each strategy performance. SVM model is generated based on this data and optimal strategy portfolio. We use 80% of the data for training and the remaining 20% is used for testing the strategy. For training, we select two strategies which show the highest profit in the next day. Selection method 1 selects two strategies and method 2 selects maximum two strategies which show profit more than 0.1 point. We use one-against-all method which has fast processing time. We analyse the daily data of KOSPI 200 index futures contracts from January 1990 to November 2011. Price change rates for 50 days are used as SVM input data. The training period is from January 1990 to March 2007 and the test period is from March 2007 to November 2011. We suggest three benchmark strategies portfolio. BM1 holds two contracts of KOSPI 200 index futures for testing period. BM2 is constructed as two strategies which show the largest cumulative profit during 30 days before testing starts. BM3 has two strategies which show best profits during testing period. Trading cost include brokerage commission cost and slippage cost. The proposed strategy portfolio management system shows profit more than double of the benchmark portfolios. BM1 shows 103.44 point profit, BM2 shows 488.61 point profit, and BM3 shows 502.41 point profit after deducting trading cost. The best benchmark is the portfolio of the two best profit strategies during the test period. The proposed system 1 shows 706.22 point profit and proposed system 2 shows 768.95 point profit after deducting trading cost. The equity curves for the entire period show stable pattern. With higher profit, this suggests a good trading direction for system traders. We can make more stable and more profitable portfolios if we add money management module to the system.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.19-43
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• 2016

This study examines the causes of the Asian exchange rate crisis and compares it to the European Monetary System crisis. In 1997, emerging countries in Asia experienced financial crises. Previously in 1992, currencies in the European Monetary System had undergone the same experience. This was followed by Mexico in 1994. The objective of this paper lies in the generation of useful insights from these crises. This research presents a comparison of South Korea, United Kingdom and Mexico, and then compares three different models for prediction. Previous studies of economic crisis focused largely on the manual construction of causal models using linear techniques. However, the weakness of such models stems from the prevalence of nonlinear factors in reality. This paper uses a structural equation model to analyze the causes, followed by a neural network model to circumvent the linear model's weaknesses. The models are examined in the context of predicting exchange rates In this paper, data were quarterly ones, and Consumer Price Index, Gross Domestic Product, Interest Rate, Stock Index, Current Account, Foreign Reserves were independent variables for the prediction. However, time periods of each country's data are different. Lisrel is an emerging method and as such requires a fresh approach to financial crisis prediction model design, along with the flexibility to accommodate unexpected change. This paper indicates the neural network model has the greater prediction performance in Korea, Mexico, and United Kingdom. However, in Korea, the multiple regression shows the better performance. In Mexico, the multiple regression is almost indifferent to the Lisrel. Although Lisrel doesn't show the significant performance, the refined model is expected to show the better result. The structural model in this paper should contain the psychological factor and other invisible areas in the future work. The reason of the low hit ratio is that the alternative model in this paper uses only the financial market data. Thus, we cannot consider the other important part. Korea's hit ratio is lower than that of United Kingdom. So, there must be the other construct that affects the financial market. So does Mexico. However, the United Kingdom's financial market is more influenced and explained by the financial factors than Korea and Mexico.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.109-114
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• 2020

The aim of this study is to develop basic artificial neural network models in forecasting the in-sample gross domestic product (GDP) of Malaysia. GDP is one of the main indicators in presenting the macro economic condition of a country as set by the world authority bodies such as the World Bank. Hence, this study uses an artificial neural network-based approach to make predictions concerning the economic growth of Malaysia. This method has been proposed due to its ability to overcome multicollinearity among variables, as well as the ability to cope with non-linear problems in Malaysia's growth data. The selected inputs and outputs are based on the previous literatures as well as the economic growth theory. Therefore, the selected inputs are exports, imports, private consumption, government expenditure, consumer price index (CPI), inflation rate, foreign direct investment (FDI) and money supply, which includes M1 and M2. Whilst, the output is real gross domestic product growth rate. The results of this study showed that the neural network method gives the smallest value of mean error which is 0.81 percent with a total difference of 0.70 percent. This implies that the neural network model is appropriate and is a relevant method in forecasting the economic growth of Malaysia.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.95-107
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• 2020

The study investigates the asymmetric effect of exchange rate changes on stock prices in Vietnam. We use the nonlinear autoregressive-distributed lag (ARDL) analysis for monthly data from 2001:01 to 2018:05, based on VN-Index stock price collected from Ho Chi Minh Stock Exchange (HOSE); the nominal exchange rate is separated into currency depreciation and appreciation through a partial sum decomposition process. Asymmetry is estimated both in the long-run relationship and the short-run error correction mechanism. The research results show that the effect of exchange rate changes on stock prices is asymmetrical, both in the short run and in long run. Accordingly, the stock prices react to different levels to depreciation and appreciation. However, the currency appreciation affects a stronger transmission of stock prices when compared to the long-run currency depreciation. In the absence of asymmetry, the exchange rate only has a short-run impact on stock prices. This implies a symmetrical assumption that underestimates the impact of exchange rate changes on stock prices in Vietnam. This study points to an important implication for regulators in Vietnam. They should consider the relationship between exchange rate changes and stock prices in both the long run and the short run to manage the stock and foreign exchange market.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2008.04a
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• pp.387-390
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• 2008

The importance of the life cycle cost analysis for construction projects of bridge has been recognized over the last decades. Accordingly, theoretical models, guidelines, and supporting softwares have been developed for the life cycle cost analysis of bridges. However, it is difficult to predict life cycle cost considering uncertainties precisely. This paper presents methodology for optimal design of substructure for a steel box bridge. Total life cycle cost for the service life is calculated as sum of initial cost, damage cost considering uncertainty, maintenance cost, repair and rehabilitation cost. The optimization method is applied to design of a bridge substructure with minimal cost, in which the objective function is set to life cycle cost and constraints are formulated on the basis of Korean Bridge Design Specification. Initial cost is calculated based on standard costs of the Korea Construction Price Index and damage cost on the damage probabilities to consider the uncertainty of load and resistance. An advanced first-order second moment method is used as a practical tool for reliability analysis using damage probability. Maintenance cost and cycle is determined by a stochastic method and user cost includes traffic operation costs and time delay costs.

• Journal of Distribution Science
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• v.16 no.11
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• pp.37-45
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• 2018

Purpose - Recently, large quantities of factors have affected the signing of the Free Trade Agreement between two countries. Due to this background, this paper selects South Korea as an example to explore the determinants of Free Trade Agreement from Asian countries. Research design, data, and methodology - A cross sectional data of 2016 will be employed and some variables such as real income and GDP will be used to run an empirical analysis under the linear probability model, probit model and logit model. Results - The findings show that the Asian countries' exchange rate regime, real income, GDP and so forth can increase the probability of signing the Free Trade Agreement with Asian countries. Conversely, the distance can lower the probability of signing the Free Trade Agreement with Asian countries. Meanwhile, although the Asian countries' import, consumer price index and population also can affect the probability of signing the Free Trade Agreement with Asian countries, the estimated coefficients are not statistically significant at 5% level. Conclusions - According to the empirical results, this paper provides a new scope for South Korea's government to sign the Free Trade Agreement with other Asian countries.