• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.107-122
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• 2017

Volatility in the stock market returns is a measure of investment risk. It plays a central role in portfolio optimization, asset pricing and risk management as well as most theoretical financial models. Engle(1982) presented a pioneering paper on the stock market volatility that explains the time-variant characteristics embedded in the stock market return volatility. His model, Autoregressive Conditional Heteroscedasticity (ARCH), was generalized by Bollerslev(1986) as GARCH models. Empirical studies have shown that GARCH models describes well the fat-tailed return distributions and volatility clustering phenomenon appearing in stock prices. The parameters of the GARCH models are generally estimated by the maximum likelihood estimation (MLE) based on the standard normal density. But, since 1987 Black Monday, the stock market prices have become very complex and shown a lot of noisy terms. Recent studies start to apply artificial intelligent approach in estimating the GARCH parameters as a substitute for the MLE. The paper presents SVR-based GARCH process and compares with MLE-based GARCH process to estimate the parameters of GARCH models which are known to well forecast stock market volatility. Kernel functions used in SVR estimation process are linear, polynomial and radial. We analyzed the suggested models with KOSPI 200 Index. This index is constituted by 200 blue chip stocks listed in the Korea Exchange. We sampled KOSPI 200 daily closing values from 2010 to 2015. Sample observations are 1487 days. We used 1187 days to train the suggested GARCH models and the remaining 300 days were used as testing data. First, symmetric and asymmetric GARCH models are estimated by MLE. We forecasted KOSPI 200 Index return volatility and the statistical metric MSE shows better results for the asymmetric GARCH models such as E-GARCH or GJR-GARCH. This is consistent with the documented non-normal return distribution characteristics with fat-tail and leptokurtosis. Compared with MLE estimation process, SVR-based GARCH models outperform the MLE methodology in KOSPI 200 Index return volatility forecasting. Polynomial kernel function shows exceptionally lower forecasting accuracy. We suggested Intelligent Volatility Trading System (IVTS) that utilizes the forecasted volatility results. IVTS entry rules are as follows. If forecasted tomorrow volatility will increase then buy volatility today. If forecasted tomorrow volatility will decrease then sell volatility today. If forecasted volatility direction does not change we hold the existing buy or sell positions. IVTS is assumed to buy and sell historical volatility values. This is somewhat unreal because we cannot trade historical volatility values themselves. But our simulation results are meaningful since the Korea Exchange introduced volatility futures contract that traders can trade since November 2014. The trading systems with SVR-based GARCH models show higher returns than MLE-based GARCH in the testing period. And trading profitable percentages of MLE-based GARCH IVTS models range from 47.5% to 50.0%, trading profitable percentages of SVR-based GARCH IVTS models range from 51.8% to 59.7%. MLE-based symmetric S-GARCH shows +150.2% return and SVR-based symmetric S-GARCH shows +526.4% return. MLE-based asymmetric E-GARCH shows -72% return and SVR-based asymmetric E-GARCH shows +245.6% return. MLE-based asymmetric GJR-GARCH shows -98.7% return and SVR-based asymmetric GJR-GARCH shows +126.3% return. Linear kernel function shows higher trading returns than radial kernel function. Best performance of SVR-based IVTS is +526.4% and that of MLE-based IVTS is +150.2%. SVR-based GARCH IVTS shows higher trading frequency. This study has some limitations. Our models are solely based on SVR. Other artificial intelligence models are needed to search for better performance. We do not consider costs incurred in the trading process including brokerage commissions and slippage costs. IVTS trading performance is unreal since we use historical volatility values as trading objects. The exact forecasting of stock market volatility is essential in the real trading as well as asset pricing models. Further studies on other machine learning-based GARCH models can give better information for the stock market investors.

• Journal of the korean veterinary medical association
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• v.44 no.9
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• pp.803-818
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• 2008

동물의 결핵은 Mycobacterium bovis의 감염에 의한 만성 소모성 질병이며 인수공통전염병이다. 동물로부터 사람으로의 결핵 전염은 생유 섭취하던 시대에 상당히 많이 보고되었다. 우유의 살균처리와 소에서 피내진단에 의한 양성우 살처분 및 보상금 지급 정책을 전개하면서 M. bovis의 사람전염은 급격히 감소하였다. 소 결핵은 우리나라에서 연간 0.15% 내외의 발생을 보이고 있으며, 발생의 주원인으로는 외부입식소, 인근발생농장, 과거발생농장의 사후관리소홀 등이다. 사람 결핵의 주원인균인 M. tuberculosis와 M. bovis는 유전체가 99.9% 유사하며, M. bovis를 M. tuberculosis의 아종으로 분류하기도 한다. 두 세균은 M. tuberculosis complex에 속하며, M. tuberculosis와 M. bovis이외에도 M. africanum, M. canettii, M. microti, M. pinnipedii 등이 있다. M. bovis는 M. tuberculosis complex중에서 가장 넓은 숙주범위를 가진다. M. bovis의 대표적인 숙주는 종이름에도 나타나 있듯이 소이다. 소결핵 전파원으로서는 M. bovis에 감염된 소가 가장 중요하다. 소 이외에도 면양, 산양, 말, 돼지, 사슴, 엘크, 영양 (antelope, kudus, elands, sitatungas, oryxes, addaxes), 개, 고양이, 흰족제비 (ferrets), 낙타, 여우, 밍크, 오소리, 쥐, 영장류, 라마, 맥 (tapirs), 코끼리, 코뿔소 (rhinoceroses), 주머니쥐, 땅다람쥐 (ground squirrels), 수달 (otters), 물개, 산토끼 (hares), 두더쥐 (moles), 너구리 (raccoons), 코요테, 사자, 호랑이, 표범, 살쾡이 (lynx) 등에 감염될 수 있으나, 대부분 종결숙주 (spillover host)로 가축의 결핵방제가 유지되고 있는 국가에서는 야생동물 결핵의 가축 전염이 문제시되고 있다. M. bovis는 주로 호흡기와 소화기를 통하여 감염되며, 결핵결절이 형성되는 부위를 관찰하면 감염경로를 추정할 수 있다. 결핵에 감염되면, 초기에는 뚜렷한 임상증상을 보이지 않으나, 아침, 추운 날씨, 또는 운동 중에 심한 기침을 하며, 호흡곤란을 일으킬 수 있다. 결핵은 감염되어도 대부분 무증상이기 때문에 피내진단, 결핵결절 병리소견, 원인균 분리 등에 의해 진단하여야 한다. 감염된 결핵균은 탐식세포에 탐식되어 특징적인 육아종성 결절 병변으로 진행된다. 현재 결핵은 피내진단과 결핵결절 병리소견 등에 의해 판정하고 있다. 최신 진단법으로는 피내진단을 대체할 수 있는 인터페론 감마 검사법과 우군의 결핵 스크리닝과 말기 결핵 검사에 우수한 항체진단법이 개발되어 있다. 그러나, 소 결핵 근절을 위해서는 일관성있는 진단법과 진단기준을 적용하는 것이 중요한 성공요인중 하나이다. 소결핵 청정국인 호주와 캐나다에서는 피내진단과 도축장 결절검사를 결핵 양성우 색출방법의 근간으로 삼고 있으며, 소결핵 근절의 최종단계에 이르러서는 특이적인 검사법을 적용하였지만, 근절목적상 민감성이 높은 피내진단법을 사용하였다. 이와 더불어, 피내진단 양성우의 부검소견과 원인균 분리를 통해 결핵을 확진하여 출처농장의 역추적 검사를 통하여 결핵 양성소를 제거하였다. 한편, 결핵의 농장간 및 지역간 전파방지를 위해 결핵 청정농장과 결핵 오염농장, 결핵 청정지역과 결핵 오염지역 구분을 통하여 결핵 오염농장과 결핵 오염지역으로부터 결핵 청정농장과 결핵 청정지역으로의 이동전 결핵 검진을 통해 개체 이동에 따른 결핵 전파를 근본적으로 차단하는 시스템을 엄격히 적용한 것이 주요한 성공 요인중 하나였다. 호주 결핵 근절정책 성공요인을 요약하면, 일관성 있는 결핵진단법 적용, 양성우 출처농장의 철저한 역추적 검사, 개체 이동전 결핵 음성증명 확인, 농가단체의 경제적 및 방역상 적극적인 지원 및 협조 결핵의 지속적인 모니터 링과 현장요구에 부응하는 방제신기술의 지속적인 연구개발 등을 들 수 있다. 최근 들어 국내 동물 결핵은 소, 특히, 한우의 결핵발생이 증가하고 있으며, 사슴 결핵발생도 증가하고 있다. 농장간 및 지역간에 결핵 감수성 가축, 특히, 소와 사슴의 거래가 아주 복잡하게 이루어지고 있는 현실을 고려할 때, 결핵전파의 주원인인 결핵감염 소나 사슴의 농장내 반입을 철저히 차단해야 할 것이다. 이때, 개체 검사는 물론이고, 출처농장에 대한 결핵 음성을 확인한 후 입식하여야 할 것이며, 입식 후에도 60일정도 격리사육하면서 피내진단등 결핵검진 후 음성인 경우에만 합사하여야 할 것이다. M. bovis는 사람을 비롯한 거의 모든 온혈동물에서 결핵을 일으킬 수 있기 때문에, 결핵 감염소로 판정된 농장 종사자는 각 시도 보건소의 협조를 받아 결핵검진을 받도록 해야 한다. 농장 가축에 접촉할 수 있는 야생동물의 접촉을 차단하여야 하며, 특히, 농장 사료의 야생동물에 의한 오염을 방지할 수 있는 사료창고관리를 철저히 해야 한다. 결핵 감염소를 다룰 때는 분비물 또는 가검물에 의해 감염될 수 있기 때문에 개인방역장비 - 방역복, 마스크, 비닐장갑, 비닐장화 - 를 착용한 상태에서 다루어야 한다. 특히, 결핵 감염소를 매몰 또는 소각하는 과정에서 결핵 감염소의 배설물 및 분비물 처리를 철저히 하여야 한다. 모든 작업을 마친 후에는 개인방역장비, 매몰 또는 소각에 사용하였던 장비 등을 청소 및 소독하고 필요시 소각 또는 매몰하여야 하며, 개인감염위험과 타인 감염위험을 방지하기 위해 노출부위를 세척하여야 한다.

• Korea Real Estate Review
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• v.28 no.1
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• pp.79-90
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• 2018

The purpose of this study was to estimate the pricing factors of residential lands in new cities by estimating the pricing model of residential lands. For this purpose, hedonic equations for each quantile of the conditional distribution of land prices were estimated using quantile regression methods and the sale price date of Jangyu New Town in Gimhae. In this study, a quantile regression method that models the relation between a set of explanatory variables and each quantile of land price was adopted. As a result, the differences in the effects of the characteristics by price quantile were confirmed. The number of years that elapsed after the completion of land construction is the quadratic effect in the model because its impact may give rise to a non-linear price pattern. Age appears to decrease the price until certain years after the construction, and increases the price afterward. In the estimation of the quantile regression, land age appears to have a statistically significant impact on land price at the traditional level, and the turning point appears to be shorter for the low quantiles than for the higher quantiles. The positive effects of the use of land for commercial and residential purposes were found to be the biggest. Land demand is preferred if there are more than two roads on the ground. In this case, the amount of sunshine will improve. It appears that the shape of a square wave is preferred to a free-looking land. This is because the square land is favorable for development. The variables of the land used for commercial and residential purposes have a greater impact on low-priced residential lands. This is because such lands tend to be mostly used for rental housing and have different characteristics from residential houses. Residential land prices have different characteristics depending on the price level, and it is necessary to consider this in the evaluation of the collateral value and the drafting of real estate policy.

• Korea Trade Review
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• v.48 no.4
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• pp.303-320
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• 2023

Recently, import and export companies have been using T/T remittance and Surrender B/L more frequently than L/C when selecting the process and method of trade payment settlement. The new trade and logistics environment is thriving in the era of the Fourth Industrial Revolution (4IR). Document-based trade transactions are undergoing a digitalization as bills of lading or smart contracts are being developed. The purpose of this study is to verify whether exporters choose export payment types based on negotiating factors. In addition, we would like to discuss the application of the characteristics of the new trade and logistics environment. Data for analysis was collected through surveys. The collection method consisted of direct visits to the company, e-mail, fax, and online surveys. The survey distribution period is from February 1, 2023, to April 30, 2023. The questionnaire was distributed in 2,000 copies, and 447 copies were collected. The final 336 copies were used for analysis, excluding 111 copies that were deemed inappropriate for the purpose of this study. The results of the study are shown below. First, among the negotiating factors, the product differentiation of exporters did not significantly affect the selection of export payment types. Second, among the negotiating factors, the greater the purchasing advantage recognized by exporters, the higher the possibility of using the post-transfer method. In addition to analyzing the results, this study suggests that exporters should consider adopting new payment methods, such as blockchain technology-based bills of lading and trade finance platforms, to adapt to the characteristics of the evolving trade and logistics environment. Therefore, exporters should continue to show interest in initiatives aimed at digitizing trade documents as a response to the challenges posed by bills of lading. In future studies, it is necessary to address the lack of social awareness in Korea by conducting advanced research abroad.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.147-168
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• 2017

There have been many studies on accurate stock market forecasting in academia for a long time, and now there are also various forecasting models using various techniques. Recently, many attempts have been made to predict the stock index using various machine learning methods including Deep Learning. Although the fundamental analysis and the technical analysis method are used for the analysis of the traditional stock investment transaction, the technical analysis method is more useful for the application of the short-term transaction prediction or statistical and mathematical techniques. Most of the studies that have been conducted using these technical indicators have studied the model of predicting stock prices by binary classification - rising or falling - of stock market fluctuations in the future market (usually next trading day). However, it is also true that this binary classification has many unfavorable aspects in predicting trends, identifying trading signals, or signaling portfolio rebalancing. In this study, we try to predict the stock index by expanding the stock index trend (upward trend, boxed, downward trend) to the multiple classification system in the existing binary index method. In order to solve this multi-classification problem, a technique such as Multinomial Logistic Regression Analysis (MLOGIT), Multiple Discriminant Analysis (MDA) or Artificial Neural Networks (ANN) we propose an optimization model using Genetic Algorithm as a wrapper for improving the performance of this model using Multi-classification Support Vector Machines (MSVM), which has proved to be superior in prediction performance. In particular, the proposed model named GA-MSVM is designed to maximize model performance by optimizing not only the kernel function parameters of MSVM, but also the optimal selection of input variables (feature selection) as well as instance selection. In order to verify the performance of the proposed model, we applied the proposed method to the real data. The results show that the proposed method is more effective than the conventional multivariate SVM, which has been known to show the best prediction performance up to now, as well as existing artificial intelligence / data mining techniques such as MDA, MLOGIT, CBR, and it is confirmed that the prediction performance is better than this. Especially, it has been confirmed that the 'instance selection' plays a very important role in predicting the stock index trend, and it is confirmed that the improvement effect of the model is more important than other factors. To verify the usefulness of GA-MSVM, we applied it to Korea's real KOSPI200 stock index trend forecast. Our research is primarily aimed at predicting trend segments to capture signal acquisition or short-term trend transition points. The experimental data set includes technical indicators such as the price and volatility index (2004 ~ 2017) and macroeconomic data (interest rate, exchange rate, S&P 500, etc.) of KOSPI200 stock index in Korea. Using a variety of statistical methods including one-way ANOVA and stepwise MDA, 15 indicators were selected as candidate independent variables. The dependent variable, trend classification, was classified into three states: 1 (upward trend), 0 (boxed), and -1 (downward trend). 70% of the total data for each class was used for training and the remaining 30% was used for verifying. To verify the performance of the proposed model, several comparative model experiments such as MDA, MLOGIT, CBR, ANN and MSVM were conducted. MSVM has adopted the One-Against-One (OAO) approach, which is known as the most accurate approach among the various MSVM approaches. Although there are some limitations, the final experimental results demonstrate that the proposed model, GA-MSVM, performs at a significantly higher level than all comparative models.

• Journal of the East Asian Society of Dietary Life
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• v.21 no.6
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• pp.934-947
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• 2011

The purpose of this study is to analyze products for good taste and convenience, which become an engine to constantly create customers. In addition, this study is aimed at investigating the relationship between the selective attributes of Home Meal Replacement, the perceived utilitarian value, and the repurchase intention, and drawing new suggestions on the Home Meal Replacement market from a new marketing perspective. Based on a total of 215 samples, this study reviewed the reliability and fitness of the research model and verified a total of 5 hypothesized using the Amos program. The result of study modeling was GFI=0.905, AGFI=0.849, NFI=0.889, CFI=0.945, and RMR=0.0.092 at the level of $x^2$=230.22 (df=126, p<0.001). First, the food quality (${\beta}$=0.221), convenience (${\beta}$=0.334), packing (${\beta}$=0.278), and employee service (${\beta}$=0.204) of home meal replacement consideration attributes had a positive (+) influence on perceived utilitarian value. Second, perceived utilitarian value (${\beta}$=0.584) had a positive (+) influence on repurchase intention. The factors to differentiate one company from other competitors in terms of the utilitarian value are the quality of food, convenience, wrapping, and services by employees. This study has illustrated the need to focus on the development of a premium menu to compete with other companies and to continue to research and develop nutritious foods that are easy to cook. Moreover, the key factors to have a distinct and constant competitive edge over other companies are the alleviation of consumer anxiety over wrapping container materials, the development of more designs, and the accumulation of service know-how. Therefore, it is necessary for a company to strongly develop the key factors based on its resources as a core capability.

• Journal of Venture Innovation
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• v.2 no.2
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• pp.31-46
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• 2019

Materials and Parts acts as the bridge in the manufacturing industry. In 2018, the materials and parts industry became the leading industry in Korea as its export reached $316.2 billion, accounting for 52.3 percent of the country's total exports. As such, it is the main industry of Korea leading the trade surplus, but when it comes to Japan, it is not. The trade deficit with Japan shrinks to $24 billion last year but the materials and parts industry still accounts for 60 percent of total deficit, which is about $15.1 billion. Today Japan has the top competitiveness in the high-tech materials and parts industry and the factors can be found in cooperation and symbiosis among companies, monotsukuri spirit, and long-term government policy. In order for Korean economy to pursue the Japan's high-tech materials and parts industry, the following change of perception is necessary. First, the material and parts industry requires win-win cooperation. In general, materials and parts are intermediate products. Therefore, it is important to understand the characterist that the transactions are all made up between companies not the with consumers. Second, expansion of joint technology development is absolutely necessary. South Korea is a leading country in the field of general-purpose materials and parts. However, the research shows that South Korea has structure which small and medium-sized companies could have difficulties in developing high-tech products as finding demand and developing market are hard due to low participation of large corporations at R&D stage. It is necessary for large corporations to participate in joint R&D and share opinions of customers from the beginning stage of R&D. Third, a long-term approach is needed. Structural vulnerabilities in the Korea's materials and parts industry, including the lack of advanced technologies is the main reason of solidification of Korea's trade deficit with Japan but there are also cultural differences about technology in the background. Even if it takes time, a long-term approach is absolutely necessary to build up technology and know-how in order to secure competitiveness in the high-tech materials and parts industry. This approach applies to act of corporation and government policy.

• The Journal of Society for e-Business Studies
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• v.16 no.3
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• pp.23-45
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• 2011

People could possess different self-identity under virtual world from physical world because of anonymity of the virtual world and this difference could influence their behavior in the virtual world. Based on self-discrepancy theory, this research proposes that continuous use model in self-expression goal. We defined the difference bet ween actual self~identity and ideal self~identity in the virtual world as "self-discrepancy in virtual world", and the difference between actual self-identity in the physical world and actual self-identity in the virtual world as "cross-world self-discrepancy". Before testing hypothesis, we compare the actual self-identity in the online community with the actual self-identity in the physical world, and with ideal self-identity in the virtual world. We derived an index for two different types of self-identity in terms of Personal Self-identity and Social Self-identity through factor analysis. Our results show that online community members have a higher level of ideal self-identity than actual self-identity in online community, and they have better personal self-identity in online community than physical world while a lower level of social self-identity in online community than physical world. The results of the hypothesis testing analysis based on 300 respondents showed that "self-discrepancy in virtual world" negatively influenced perceived usefulness for self-expression while "cross-world self-discrepancy" positively influenced perceived usefulness for self-expression. The perceived usefulness for self-expression and ease of use positively influence both continuous use and knowledge contribution. Specially, the effect of perceived usefulness for self-expression on knowledge contribution is much bigger than the effect of ease of use. This study extends self-discrepancy theory to virtual worlds by suggesting various types of self-discrepancy and by applying the effect of self-discrepancies in online community. Also, this study extends technology acceptance model in the personal goal in terms of self-expression. This study hopes to offer practical insights by suggesting positive effect of self-discrepancy on behavior in the online community.

• Journal of the Korean Society of Clothing and Textiles
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• v.30 no.12 s.159
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• pp.1747-1758
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• 2006

Rapid development of the information technology has influenced on the changes in every sector of human environments. One prominent change in retail market is an increase of electronic stores, which has prompted practical and research interest in the product and store attributes that include consumer to purchase products from the electronic shopping. Therefore many marketers are paying much attention to the criteria of evaluating clothing and web service on internet shopping malls. The purpose of this study is to examine differences of clothing and web service criteria of consumer groups (High-Involvement & High-Ability, Low-Involvement & High-Ability, High-Involvement & Low-Ability, and Low-Involvement & Low-Ability) who are classified into consumer involvement and internet use ability. The subjects of this study were 305 people aged between 19 and 39s, living in Seoul and Gyeonggi-do area, and having experiences in buying products on the internet shopping. Statistical analyses used for this study were the frequency, percentage, factor analysis, ANOVA and Duncan test. The results of this study were as follows: Regarded on the criteria of evaluating clothing, the low different groups had significant differences in the esthetic, the quality performance and the extrinsic criterion. Both HIHA group and HILA group showed the similar results. They considered every criterion of evaluating clothing more important, compared with other groups. Regarded on the criteria of evaluating web service related to the low different groups, there were significant differences in the factors related to the shopping mall reliance, the product, the satisfaction after purchase, and the promotion and policy criterion. Both HIHA group and HILA group showed the similar results as well. They considered every criterion of evaluating web service more important, compared with other groups. In conclusion, HI groups perceive relatively more dangerous factors which can be occurred during internet shopping. Therefore, internet shopping malls need to provide clothing that can satisfy the HI groups as well as make efforts to remove the dangerous factors on the internet.

• The Journal of Society for e-Business Studies
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• v.17 no.4
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• pp.69-93
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• 2012

Various influence-related relationships in Social Network Services (SNS) among users, posts, and user-and-post, can be expressed using links. The current research evaluates the influence of specific users or posts by analyzing the link structure of relevant social network graphs to identify influential users. We applied the concept of mutual interactions proposed for ranking semantic web resources, rather than the voting notion of Page Rank or HITS, to blogosphere, one of the early SNS. Through many experiments with network models, where the performance and validity of each alternative approach can be analyzed, we showed the applicability and strengths of our approach. The weight tuning processes for the links of these network models enabled us to control the experiment errors form the link weight differences and compare the implementation easiness of alternatives. An additional example of how to enter the content scores of commercial or spam posts into the graph-based method is suggested on a small network model as well. This research, as a starting point of the study on identifying influential users in SNS, is distinctive from the previous researches in the following points. First, various influence-related properties that are deemed important but are disregarded, such as scraping, commenting, subscribing to RSS feeds, and trusting friends, can be considered simultaneously. Second, the framework reflects the general phenomenon where objects interacting with more influential objects increase their influence. Third, regarding the extent to which a bloggers causes other bloggers to act after him or her as the most important factor of influence, we treated sequential referencing relationships with a viewpoint from that of PageRank or HITS (Hypertext Induced Topic Selection).