• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.157-177
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• 2022

Investors are trading stocks by keeping a close watch on the order information submitted by domestic and foreign investors in real time through Limit Order Book information, so-called price current provided by securities firms. Will order information released in the Limit Order Book be useful in stock price prediction? This study analyzes whether it is significant as a predictor of future stock price up or down when order imbalances appear as investors' buying and selling orders are concentrated to one side during intra-day trading time. Using classification algorithms, this study improved the prediction accuracy of the order imbalance information on the short-term price up and down trend, that is the closing price up and down of the day. Day trading strategies are proposed using the predicted price trends of the classification algorithms and the trading performances are analyzed through empirical analysis. The 5-minute KOSPI200 Index Futures data were analyzed for 4,564 days from January 19, 2004 to June 30, 2022. The results of the empirical analysis are as follows. First, order imbalance information has a significant impact on the current stock prices. Second, the order imbalance information observed in the early morning has a significant forecasting power on the price trends from the early morning to the market closing time. Third, the Support Vector Machines algorithm showed the highest prediction accuracy on the day's closing price trends using the order imbalance information at 54.1%. Fourth, the order imbalance information measured at an early time of day had higher prediction accuracy than the order imbalance information measured at a later time of day. Fifth, the trading performances of the day trading strategies using the prediction results of the classification algorithms on the price up and down trends were higher than that of the benchmark trading strategy. Sixth, except for the K-Nearest Neighbor algorithm, all investment performances using the classification algorithms showed average higher total profits than that of the benchmark strategy. Seventh, the trading performances using the predictive results of the Logical Regression, Random Forest, Support Vector Machines, and XGBoost algorithms showed higher results than the benchmark strategy in the Sharpe Ratio, which evaluates both profitability and risk. This study has an academic difference from existing studies in that it documented the economic value of the total buy & sell order volume information among the Limit Order Book information. The empirical results of this study are also valuable to the market participants from a trading perspective. In future studies, it is necessary to improve the performance of the trading strategy using more accurate price prediction results by expanding to deep learning models which are actively being studied for predicting stock prices recently.

• The Korean Journal of Applied Statistics
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• v.20 no.1
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• pp.117-132
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• 2007

In a $2\times2$ table showing binary agreement between two raters, it is known that Cohen's $\kappa$, a chance-corrected measure of agreement, has two paradoxes. $\kappa$ is substantially sensitive to raters' classification probabilities(marginal probabilities) and does not satisfy conditions as a chance-corrected measure of agreement. However, $\kappa$ and other established measures have a reasonable and similar value when each marginal distribution is close to 0.5. The objectives of this paper are to present a new measure of agreement, H, which resolves paradoxes of $\kappa$ by adjusting unbalanced marginal distributions and to compare the proposed measure with established measures through some examples.

• Korea journal of population studies
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• v.20 no.1
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• pp.65-96
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• 1997

The main purpose of this study is to explore the determinants of sex ratio imbalance at birth in Taegu which has experienced the extremely imbalanced sex ratio at birth since mid-1980s. This paper attempts to compare the determinants of sex ratio imbalance at birth, such as sex discrimination against women, son preference, prenatal sex identification followes by sex-selective induced abortions, among married women aged 25 to 44 in Taegu with those in Bay area, California in USA. The research is based on the survey data which were conducted in Taegu, Repulic of Korea and Bay area, California in USA. The findings of this analysis suggest that married women in Taegu are more likely to feel sex discrimination against women than married women in Bay area. Furthermore, the percentage of married women's effort for son bearing before pregnancy is much higher than that of married women in Bay area. We also have found that the percentage of sex-selective induced abortion in Taegu is six times higher than that of married women in Bay area. According to the logistic regression analysis, the determinants of sex-selective induced abortion among married women in Taegu are discrimination against women, son preference, prenatal sex identification. On the other hand, age is the only variable which has an important impact on sex-selective induced abortion among married women in Bay area. From the findings of this study, we can conclude that son preference based on Cofucianism is the most important impact on sex ratio imbalance at birth in Taegu where son preference is much stronger than other regions in Korea. The phenomenon of extremely imbalanced sex ratio at birth in Taegu is the result of combination of these factors, such as strong son preference, seeking to have at least one son within small family size, and prenatal sex identification followed by sex-selective induced abortion.

• Korean Journal of Organic Agriculture
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• v.25 no.1
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• pp.161-170
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• 2017

To investigate the influence of long-term organic cultivation on soil characteristics, chemical properties of 35 soils in the national scale organically managed over 10 years were analyzed. 57% of soils which were managed by the materials containing livestock manure have higher nutrient concentration than the materials not containing livestock manure. The decomposed composts (containing livestock manure) had higher amount of $P_2O_5$, CaO, $K_2O$ than organic fertilizers (not containing livestock manure). In the results, the nutrient concentration of soils in long-term organically managed was higher than optimum range of upland soil, especially pH 6.9, available phosphorus (Av. $P_2O_5$) 744 mg/kg, exchangeable calcium $9.4cmol_c/kg$, potassium 2.51 cmolc/kg. On the other hand, more than 50% of soils had lower concentration of exchangeable magnesium than optimum range (soil nutrient distribution was unbalanced). It is suggested that farmers have to be careful to apply organic materials, especially containing livestock manure.

• Journal of KIISE:Databases
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• v.35 no.5
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• pp.432-446
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• 2008

Queries for tracing tag locations are among the most challenging requirements in RFID based applications, including automated manufacturing, inventory tracking and supply chain management. For efficient query processing, a previous study proposed the index scheme for storing tag objects, based on the moving object index, in 3-dimensional domain with the axes being the tag identifier, the reader identifier, and the time. In a different way of a moving object index, the ranges of coordinates for each domain are quite different so that the distribution of query regions is skewed to the reader identifier domain. Previous indexes for tags, however, do not consider the skewed distribution for query regions. This results in producing many overlaps between index nodes and query regions and then causes the problem of traversing many index nodes. To solve this problem, we propose a new disproportional insertion and split policy of the index for RFID tags which is based on the R*-tree. For efficient insertion of tag data, our method derives the weighted margin for each node by using weights of each axis and margin of nodes. Based the weighted margin, we can choose the subtree and the split method in order to insert tag data with the minimum cost. Proposed insertion method also reduces the cost of region query by reducing overlapped area of query region and MBRs. Our experiments show that the index based on the proposed insertion and split method considerably improves the performance of queries than the index based on the previous methods.

• Journal of Korean Academy of Nursing
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• v.3 no.2
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• pp.67-80
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• 1973

발전이란 말은 한 국가나 사회가 교육적, 경제적, 사회문화적 및 정치적으로 안정된 기조를 확립하여 국민 전체가 생을 영위함에 있어서 경제적으로 부족함이 없이 윤택하고 각종 사회적 제도가 참 삶을 추구할 수 있는 방향으로 변천되어 가는 과정을 뜻한다. 본 연구는 발전과 번영을 위해 약진하고 있는 대한민국의 최근 20년간의 발전과정 (1950년부터 1970년까지)을 경제적측면과 교육적 측면에서 미국의 것과를 비교하기 위하여 유네스코 통계 연감에 의하여 그 자료를 분석 검토하였다. 본 연구에서 한국은 경제성장율이 늘어남에 따라서 교육비 투자가 증가되었고 따라서 초등교육과정은 1965년도에서부터 취학율이 100%를 상회하게 되었으나 중등교육은 1968년도에 취학율이 겨우 36%로 아직도 저조하며 여학생 취학율은 초등교육에서 는 남녀 의 차이 가 없으나 중등교육에서는 1/3선으로 떨어지고 있으며 특히 여선생님의 남선생님에 대한 비율은 중등교육과정에서 걱우 14%밖에 안되고 인구 10만당 대학졸업생수는 1968년을 기준으로 볼 때 계속 증가되어 왔으나 미국이 3,735명(그중 40%는 여학생임)인데 비하여 한국은 566명 (여학생은 26%)으로 고등교육의 혜택을 받는 율이 아직도 미국에 비해서 낮고 초등교육과정에서 학생과 선생님의 비율을 보면은 한국은 60 : 1 인데 비하여 미국은 26 : 1로써 미국보다 높고 따라서 한국은 교직원 부족과 시설미비, 농촌과 도시간의 차이 및 고등교육 혜택의 불균형 및 여성교육의 기회가 남성에 비해 낮고 해외 유학의 경우 본국 귀환율이 적어서 지도자 양성이 문제되고 있다. 그러나 한국은 1960년대에 급격한 경제성장과 함께 교육투자도 증가되었고 따라서 발전을 거듭하여 계속하고 있다.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.125-140
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• 2013

We call a data set in which the number of records belonging to a certain class far outnumbers the number of records belonging to the other class, 'imbalanced data set'. Most of the classification techniques perform poorly on imbalanced data sets. When we evaluate the performance of a certain classification technique, we need to measure not only 'accuracy' but also 'sensitivity' and 'specificity'. In a customer churn prediction problem, 'retention' records account for the majority class, and 'churn' records account for the minority class. Sensitivity measures the proportion of actual retentions which are correctly identified as such. Specificity measures the proportion of churns which are correctly identified as such. The poor performance of the classification techniques on imbalanced data sets is due to the low value of specificity. Many previous researches on imbalanced data sets employed 'oversampling' technique where members of the minority class are sampled more than those of the majority class in order to make a relatively balanced data set. When a classification model is constructed using this oversampled balanced data set, specificity can be improved but sensitivity will be decreased. In this research, we developed a hybrid model of support vector machine (SVM), artificial neural network (ANN) and decision tree, that improves specificity while maintaining sensitivity. We named this hybrid model 'hybrid SVM model.' The process of construction and prediction of our hybrid SVM model is as follows. By oversampling from the original imbalanced data set, a balanced data set is prepared. SVM_I model and ANN_I model are constructed using the imbalanced data set, and SVM_B model is constructed using the balanced data set. SVM_I model is superior in sensitivity and SVM_B model is superior in specificity. For a record on which both SVM_I model and SVM_B model make the same prediction, that prediction becomes the final solution. If they make different prediction, the final solution is determined by the discrimination rules obtained by ANN and decision tree. For a record on which SVM_I model and SVM_B model make different predictions, a decision tree model is constructed using ANN_I output value as input and actual retention or churn as target. We obtained the following two discrimination rules: 'IF ANN_I output value <0.285, THEN Final Solution = Retention' and 'IF ANN_I output value ${\geq}0.285$, THEN Final Solution = Churn.' The threshold 0.285 is the value optimized for the data used in this research. The result we present in this research is the structure or framework of our hybrid SVM model, not a specific threshold value such as 0.285. Therefore, the threshold value in the above discrimination rules can be changed to any value depending on the data. In order to evaluate the performance of our hybrid SVM model, we used the 'churn data set' in UCI Machine Learning Repository, that consists of 85% retention customers and 15% churn customers. Accuracy of the hybrid SVM model is 91.08% that is better than that of SVM_I model or SVM_B model. The points worth noticing here are its sensitivity, 95.02%, and specificity, 69.24%. The sensitivity of SVM_I model is 94.65%, and the specificity of SVM_B model is 67.00%. Therefore the hybrid SVM model developed in this research improves the specificity of SVM_B model while maintaining the sensitivity of SVM_I model.

• The Korean Journal of Financial Management
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• v.11 no.2
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• pp.41-64
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• 1994

1988년 초부터 1994년 5월 1일까지 합병된 135개 등록 및 상장기업중 충분한 자료가 확보되어 있는 83개 기업을 표본으로 하여 합병기업의 재무적 특성과 이를 바탕으로 하여 합병대상기업에 대한 예측력을 검증하였다. 피합병기업의 재무적 특성 중 통계적인 유의성이 뒷받침된 것들은 다음과 같았다. 피합병기업은 상대적으로 비효율적으로 운영되고 있었으며, 레버리지가 높고, 장기 채무지급능력이 낮았으며, 기업의 성장성과 자원간의 불균형이 있는 것으로 나타났다. 예측력검증은 선형판별식을 이용하여 예측에 이용될 재무비율을 선정하였으며, 3개의 모형에 적용한 결과 최저 42.4%에서 최고 62.4%까지의 분류정확도를 얻을 수 있었다.

• Proceedings of the KAIS Fall Conference
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• 2012.05a
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• pp.393-396
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• 2012

우리나라 지역발전정책은 80년대 들어서 심화된 국토불균형 문제를 해소하기 위하여 지역경제 활성화 및 지방투자 촉진 목적의 다양한 정책 수단을 마련하면서 본격화 되었다. 수도권 소재 기업의 지방 이전을 위한 각종 법률과 제도가 제정 시행된 결과 일정 부분 성공했다는 평가가 있다. 충북지역 역시 수도권 소재 기업의 유치를 위하여 다양한 노력을 기울이고 있다. 이러한 중앙정부와 지방정부의 다양한 노력 결과, 2000년 이후에 충북으로 이전한 총수는 약 170여개 기업 정도가 되었다. 이들 기업은 업종별이나 지역별 등과 같은 그 구성 비율로 볼 때 고르지 못한 면이 있다. 예를 들어 기업의 지역별 이전기업 수를 보면 충주 46개, 청원 28개 기업으로 주로 충북 북부지역과 중부권에 집중되어 있고 영동과 보은 등의 남부권으로 이전한 기업은 거의 없어, 균형 개발 차원에서 남부 3군(옥천 포함)에 대한 충북도 차원의 지원이 필요할 것으로 보인다.

• Proceedings of the KAIS Fall Conference
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• 2010.05b
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• pp.1025-1028
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• 2010

본 연구의 목적은 충북 지방재정의 실태를 검토하고 운영에 따른 재정건전성을 여러 가지 지표를 통하여 분석하며, 이에 근거하여 충북 지방재정의 문제점을 도출하고 개선방안을 제시하는 것이다. 연구 목적을 달성하기 위하여 행정안전부 및 행정자치부, 각 광역자치단체 등에서 2004년부터 2009까지의 자료를 구하여 재정지표 분석 제도의 틀에 따라 분석하였다. 전체적으로 보아 세입 부문을 보면 충북의 재정자립도와 자주도는 도 평균 대비 우수한 편이다. 주민 1인당 세외수입은 상대적으로 많으나 1인당 자체수입액 및 지방세부담액은 상당한 수준으로 낮다. 세출부문을 나타내는 경상경비 비율은 매우 양호하나 세입 세출 균형 측면에서는 불균형을 나타내고 있다. 이는 기본 경비는 타 도에 비해 적게 사용하고 있어 효율적인 반면, 주민 1인당 주민세 부담액이 매우 낮기 때문이다. 이러한 사실에 기초한 재정건전성 방안을 연구할 필요가 있다.