• The Korean Journal of Financial Management
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• v.23 no.2
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• pp.85-107
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• 2006

This paper investigates whether the futures market responds to the news more sensitively and uses more diverse information than the spot market. The sensitivity to the news is measured by the coefficients of the model which regresses the daily changes in the futures prices to the daily changes in the theoretical prices computed from spot prices using the spot-futures parity. The diversity of news is measured by the mean range differences ($\overline{RD}$), mean hi-price differences($\overline{HD}$) and mean low-price differences. The data in this paper is the closing prices of the nearest-to-maturity and the second-nearest-to-maturity contracts of the KOSPI 200 index futures. As the estimates of the relative sensitivity of the futures prices($^{\beta}$) for the whole-period sample are not significantly different from 1, the sensitivity of two markets to the news are not different. However, $\hat{\beta}$ of the most recent period(Nov. 2002 to Dec. 2005) are strongly different from 1. And, in the most recent period, the futures price changes for the good news, which is defined as the price increase of KOSPI of more than 1.5% in a day, show additional sensitivity. Since the mean range different which measures the relative diversity of information used, are not significantly different from 0 for the whole-period and subperiod samples, and this can be interpreted that the futures market does not use more diverse information than the spot market. However, the mean high-price difference, which measures the relative diversity of good news, are significantly different from 0 for the nearest-maturity contracts in the whole-period and subperiod samples. This evidence supports that the futures prices reflects more diverse good news which brings price increase in the market.

• Journal of the Korean Society of Costume
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• v.33
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• pp.175-188
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• 1997

the main purpose of this study was to inves-tigate the consumer dissatisfaction and com-plaining behavior in purchase and use by con-sumer value. The subjects participated this study were 204 female students. They were classified into 3 groups by important degree of instrumental value which is one of the 2 value categories that divided by the Rokeach. In order to assess consumer dissatishaction in purchase and use of clothing by those groups. The Clothing Purchase Dissatisfaction Inventory was used and The Consumer Complaining Behavior Inventory was adapted to asses consumer complaining behavior. The Clothing Purchase Dissatisfaction Inventory has 4 subscales(Price related factor Produt and Quality related factor Information and Service related factor Purchase decision-mak-ing related factor)and The Consumer Complaining behavior Inventory consisted in 3 subscales(Do nothing Private complaining Public complaining) Using SAS package in order to examine Clothing Purchase Dissatisfaction Inventory scores anaslysis of variance (MANOVA) was excuted And turkety test a kind of post-hoc multiple comparisons methods was adapted to compare Clothing Purchase Dissatisfaction In-ventory scores of each groups. in order to in-vestigate consumer complaining behavior by each groups and grade major pocket money a month the mean purchse price of clothing a month x2-test Frequency Percent were executed. Conclusion eached in this study are as fol-low: 1. Each group had differences in price re-lated factor Product nad Quality related fac-tor Information and Service related factor ex-cept Purchase decision -making related factor Groups which made much of value tend to dis-satisfy in price related facor Product and Quality related factor Information and Service related factor. 2. Group that made much of value had more high scores in private complaining complainto third party and the middle group had more high scores in private complaining . Group made little of value tended to do nothing. 3. Grade major pocket money a monty the mean purchase price of clothing a month didn't have difference signficantly in consumer behavior. but major had difference on private complaining.

• Journal of the Korean Society of Clothing and Textiles
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• v.31 no.11
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• pp.1500-1509
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• 2007

The purpose of this study was to observe lifestyle of female consumers aged 15-25. Also it was to measure brand awareness, to determine purchase criteria in fashion magazine, and to determine promotion preferences according to lifestyle segmentation variables. We distributed 600 questionnaires and 475 reliable questionnaires were used for a statical analysis. Data analyses were conducted with SPSS program on the frequency mean value, Chi-square test, Cluster analysis, and Factor analysis. We classified four clusters such as individual style seekers, trend seekers, promotion/good appearance seekers, and low fashion interest group, based on lifestyle variables. There was a significant difference in brand awareness in Vogue Girl, Cosmo Girl, Elle, Figaro, Ecole magazine among four clusters. There was a significant difference in such purchase criteria as favorable cover models, good "burok" which is a magazine supplement, brand names, and price among four clusters. In addition, the results of ANOVA represent that there was a significant difference in preferred types of promotion such as discount price, clothing gifts, fashion accessary gifts and hair tool gifts. However, the first ranked preferred one was a cosmetic gift in all the magazines, which favored more by trend seeker group.

• Journal of the East Asian Society of Dietary Life
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• v.20 no.4
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• pp.596-605
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• 2010

The purpose of this study was to measure consumers' recognition of service quality in Korean restaurants, and to compare the differences in perceived service quality according to consumers' general characteristics. Self-administrated questionnaires were completed by 1,494 subjects and data were analysed by frequency, factor, reliability, and subjected to t-test and one-way ANOVA. The major results of this study can be outlined as follows: Factor analysis on perceived service quality resulted in 4 factors: staff service (5 variables), menu quality (4 variables), price and value (4 variables) and atmosphere and convenience (5 variables). Cronbach's alpha values for the reliability were over 0.8 for all the factors. The mean value in the elicited factors was indicated to be in order of menu quality ($4.73{\pm}1.19$), atmosphere and convenience ($4.57{\pm}1.09$), price and value ($4.55{\pm}1.15$), and staff service ($4.46{\pm}1.12$). Also, a significant difference was shown in service quality, which was perceived according to consumers' general characteristics. A higher mean value in perceived service quality was shown in women than in men, in the older than in the younger, in people with a high frequency of visiting Korean restaurants than those who do so with low frequency, and in people with high cost expenditure when visiting than those with low cost expenditure. In terms of region, the mean value in perceived service quality was significantly lower for consumers in the Gwangju region than in other regions.

• Journal of the East Asian Society of Dietary Life
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• v.20 no.6
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• pp.987-996
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• 2010

The purpose of this study was to measure customers' perception of the service quality of Korean restaurants and then compare differences in perceived service quality according to customer nationality. Self-administered questionnaires were completed by 2812 subjects, and data were analyzed by frequency, chi-square, t-test, one-way ANOVA, factor, reliability, cluster, and discriminant analysis. Results of the study were as follows. The factor analysis of perceived service quality produced four factors, employee service (5 variables), menu quality (4 variables), price & value (4 variables), and physical environment (4 variables). Cronbach's alpha values for reliability were over 0.8 for all factors. Further, a significant difference was observed in service quality, which was perceived according to customer nationality. A higher mean value of perceived service quality was held by foreigners when compared to Koreans. Especially, the mean value of perceived service quality was significantly low for all items for Japanese compared to foreigners. Cluster analysis divided subjects into two groups based on attitude toward service quality of Korean restaurants: an unfavorable group and favorable group. These two groups differed from each other in general characteristics as well. Limitations and future research directions are also discussed.

• The Journal of Fisheries Business Administration
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• v.33 no.2
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• pp.127-152
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• 2002

This study intends to review the development of Large Purse Seine Fisheries in Korea and Japan, and subsequent changes in the fisheries regime as well as management conditions and to examine reorganization directions. In the Northeast Asian Fishing Area, each country has done mutual operation, which causes the fishery competition and controls fishery development. Besides, Exclusive Economic Zon(EEZ) established in 1996 resulted in the prominent changes of fishery development as well as fishery relationship among each country, demands reorganization of fisheries. In the Large Purse Seine fisheries, Korea and Japan are not decreasing, they are stable. In other words, the increase in one country does not necessarily make the decrease in the other country. This is a difference from the case of the bottom fishery. Japan is the highest in the cost, the management is getting worse due to decreasing fish price and shortage of labor. In the case of Korea, the stagnant productivity has been compensated by the rising fish price, but the fishery of low productivity to cut down the size. In addition, during the 1990s the environment of fishery is getting worse because of the free import fishery, shortage of labor, etc. Following the new fisheries paradigm, each country should reorganize its fisheries structure. The principle for reorganization of fisheries structure in each country should be focused on the establishment of sustainable fisheries. The reorganization of fisheries structure for each country by EEZ establishment does not mean only dividing fishing ground and fisheries resources by countries, but means that countries should cooperate together in fisheries management for long-run benefits from fisheries.

• Journal of Positioning, Navigation, and Timing
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• v.3 no.1
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• pp.25-30
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• 2014

Differential Global Positioning System-Correction Projection (DGPS-CP) algorithm, which has been suggested as a method of correcting pre-calculated position error by projecting range-domain correction to positional domain, is a method to improve the accuracy performance of a low price GPS receiver to 1 to 3 m, which is equivalent to that of DGPS, just by using a software program without changing the hardware. However, when DGPS-CP algorithm is actually realized, the error is not completely eliminated in a case where a reference station does not provide correction of some satellites among the visible satellites used in user positioning. In this study, the problem of decreased performance due to the difference in visible satellites between a user and a reference station was solved by applying the Multifunctional Transport Satellites (MTSAT) based Augmentation System (MASA) correction to DGPS-CP, instead of local DGPS correction, by using the Satellite Based Augmentation System (SBAS) operated in Japan. The experimental results showed that the accuracy was improved by 25 cm in the horizontal root mean square (RMS) and by 20 cm in the vertical RMS in comparison to that of the conventional DGPS-CP.

• The Journal of Bigdata
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• v.4 no.2
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• pp.1-12
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• 2019

As Artificial Intelligence (AI) technology develops, it is applied to various fields such as image, voice, and text. AI has shown fine results in certain areas. Researchers have tried to predict the stock market by utilizing artificial intelligence as well. Predicting the stock market is known as one of the difficult problems since the stock market is affected by various factors such as economy and politics. In the field of AI, there are attempts to predict the ups and downs of stock price by studying stock price patterns using various machine learning techniques. This study suggest a way of predicting stock price patterns based on the Convolutional Neural Network(CNN) among machine learning techniques. CNN uses neural networks to classify images by extracting features from images through convolutional layers. Therefore, this study tries to classify candlestick images made by stock data in order to predict patterns. This study has two objectives. The first one referred as Case 1 is to predict the patterns with the images made by the same-day stock price data. The second one referred as Case 2 is to predict the next day stock price patterns with the images produced by the daily stock price data. In Case 1, data augmentation methods - random modification and Gaussian noise - are applied to generate more training data, and the generated images are put into the model to fit. Given that deep learning requires a large amount of data, this study suggests a method of data augmentation for candlestick images. Also, this study compares the accuracies of the images with Gaussian noise and different classification problems. All data in this study is collected through OpenAPI provided by DaiShin Securities. Case 1 has five different labels depending on patterns. The patterns are up with up closing, up with down closing, down with up closing, down with down closing, and staying. The images in Case 1 are created by removing the last candle(-1candle), the last two candles(-2candles), and the last three candles(-3candles) from 60 minutes, 30 minutes, 10 minutes, and 5 minutes candle charts. 60 minutes candle chart means one candle in the image has 60 minutes of information containing an open price, high price, low price, close price. Case 2 has two labels that are up and down. This study for Case 2 has generated for 60 minutes, 30 minutes, 10 minutes, and 5minutes candle charts without removing any candle. Considering the stock data, moving the candles in the images is suggested, instead of existing data augmentation techniques. How much the candles are moved is defined as the modified value. The average difference of closing prices between candles was 0.0029. Therefore, in this study, 0.003, 0.002, 0.001, 0.00025 are used for the modified value. The number of images was doubled after data augmentation. When it comes to Gaussian Noise, the mean value was 0, and the value of variance was 0.01. For both Case 1 and Case 2, the model is based on VGG-Net16 that has 16 layers. As a result, 10 minutes -1candle showed the best accuracy among 60 minutes, 30 minutes, 10 minutes, 5minutes candle charts. Thus, 10 minutes images were utilized for the rest of the experiment in Case 1. The three candles removed from the images were selected for data augmentation and application of Gaussian noise. 10 minutes -3candle resulted in 79.72% accuracy. The accuracy of the images with 0.00025 modified value and 100% changed candles was 79.92%. Applying Gaussian noise helped the accuracy to be 80.98%. According to the outcomes of Case 2, 60minutes candle charts could predict patterns of tomorrow by 82.60%. To sum up, this study is expected to contribute to further studies on the prediction of stock price patterns using images. This research provides a possible method for data augmentation of stock data.

• Journal of Distribution Science
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• v.12 no.2
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• pp.59-71
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• 2014

Purpose - In recent years, many firms have attempted various approaches to cope with the continual increase of aviation transportation. The previous research into freight charge forecasting models has focused on regression analyses using a few influence factors to calculate the future price. However, these approaches have limitations that make them difficult to apply into practice: They cannot respond promptly to small price changes and their predictive power is relatively low. Therefore, the current study proposes a freight charge-forecasting model using time series data instead a regression approach. The main purposes of this study can thus be summarized as follows. First, a proper model for freight charge using the autoregressive integrated moving average (ARIMA) model, which is mainly used for time series forecast, is presented. Second, a modified ARIMA model for freight charge prediction and the standard process of determining freight charge based on the model is presented. Third, a straightforward freight charge prediction model for practitioners to apply and utilize is presented. Research design, data, and methodology - To develop a new freight charge model, this study proposes the ARIMAC(p,q) model, which applies time difference constantly to address the correlation coefficient (autocorrelation function and partial autocorrelation function) problem as it appears in the ARIMA(p,q) model and materialize an error-adjusted ARIMAC(p,q). Cargo Account Settlement Systems (CASS) data from the International Air Transport Association (IATA) are used to predict the air freight charge. In the modeling, freight charge data for 72 months (from January 2006 to December 2011) are used for the training set, and a prediction interval of 23 months (from January 2012 to November 2013) is used for the validation set. The freight charge from November 2012 to November 2013 is predicted for three routes - Los Angeles, Miami, and Vienna - and the accuracy of the prediction interval is analyzed using mean absolute percentage error (MAPE). Results - The result of the proposed model shows better accuracy of prediction because the MAPE of the error-adjusted ARIMAC model is 10% and the MAPE of ARIMAC is 11.2% for the L.A. route. For the Miami route, the proposed model also shows slightly better accuracy in that the MAPE of the error-adjusted ARIMAC model is 3.5%, while that of ARIMAC is 3.7%. However, for the Vienna route, the accuracy of ARIMAC is better because the MAPE of ARIMAC is 14.5% and the MAPE of the error-adjusted ARIMAC model is 15.7%. Conclusions - The accuracy of the error-adjusted ARIMAC model appears better when a route's freight charge variance is large, and the accuracy of ARIMA is better when the freight charge variance is small or has a trend of ascent or descent. From the results, it can be concluded that the ARIMAC model, which uses moving averages, has less predictive power for small price changes, while the error-adjusted ARIMAC model, which uses error correction, has the advantage of being able to respond to price changes quickly.

• Fashion & Textile Research Journal
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• v.8 no.1
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• pp.55-63
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• 2006

The purpose of this study examines difference of cunsumer satisfaction by expected selection attribute of wedding dress and bride make-up. It is looking into influencing variables in consumer satisfaction, and is supplying real information to wedding market. The subjects of this study were 241 women getting married within one year of Daegu. The data were analyzed by using frequency, mean, the standard deviation, ANOVA, duncan test, correlation analysis, cross-analysis. Conclusion obtained from the results and discussions of the research are as follows: 1) In the attribution of expected selection according to occupation, blue-collar women are concerned about cost factor but they are low content with the perceptual satisfaction factor. 2) When selecting places for wedding dresses and wedding make-up, in the attribute of expected selection about the number of visiting the shop for wedding dresses and make-up, people who visit over 7 dress shops are highly interested in the appearance fancy degree, advertisements effect factors. But they are concerned with advertisements effect factor, cost factor in the perceptual satisfaction factor about wedding dress. Besides, the more they get chances to visit many dress shops, they are concerned with advertisements, cost factors, and satisfied with both the effect of advertisements and appearance factor degree in the attribution of expected selection about wedding make-up. 3) In the attribution of expected selection about the cost of wedding dresses and make-up, the lower the cost paid, people are interested in price factor. Furthermore, in the attribution of expected selection about the wedding dress and make-up cost, those who spent over 150 million Won are interested in quality, others influence factor, and the case of less than 120~150 million Won, people are highly interested in the appearance fancy degree, advertisements effect factor, and the women are satisfied with the advertisement effect factor in the perceptual satisfaction factor of wedding make-up.