• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.65-82
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• 2021

Stock market investors are generally split into foreign investors, institutional investors, and individual investors. Compared to individual investor groups, professional investor groups such as foreign investors have an advantage in information and financial power and, as a result, foreign investors are known to show good investment performance among market participants. The purpose of this study is to propose an investment strategy that combines investor-specific transaction information and machine learning, and to analyze the portfolio investment performance of the proposed model using actual stock price and investor-specific transaction data. The Korea Exchange offers daily information on the volume of purchase and sale of each investor to securities firms. We developed a data collection program in C# programming language using an API provided by Daishin Securities Cybosplus, and collected 151 out of 200 KOSPI stocks with daily opening price, closing price and investor-specific net purchase data from January 2, 2007 to July 31, 2017. The self-organizing map model is an artificial neural network that performs clustering by unsupervised learning and has been introduced by Teuvo Kohonen since 1984. We implement competition among intra-surface artificial neurons, and all connections are non-recursive artificial neural networks that go from bottom to top. It can also be expanded to multiple layers, although many fault layers are commonly used. Linear functions are used by active functions of artificial nerve cells, and learning rules use Instar rules as well as general competitive learning. The core of the backpropagation model is the model that performs classification by supervised learning as an artificial neural network. We grouped and transformed investor-specific transaction volume data to learn backpropagation models through the self-organizing map model of artificial neural networks. As a result of the estimation of verification data through training, the portfolios were rebalanced monthly. For performance analysis, a passive portfolio was designated and the KOSPI 200 and KOSPI index returns for proxies on market returns were also obtained. Performance analysis was conducted using the equally-weighted portfolio return, compound interest rate, annual return, Maximum Draw Down, standard deviation, and Sharpe Ratio. Buy and hold returns of the top 10 market capitalization stocks are designated as a benchmark. Buy and hold strategy is the best strategy under the efficient market hypothesis. The prediction rate of learning data using backpropagation model was significantly high at 96.61%, while the prediction rate of verification data was also relatively high in the results of the 57.1% verification data. The performance evaluation of self-organizing map grouping can be determined as a result of a backpropagation model. This is because if the grouping results of the self-organizing map model had been poor, the learning results of the backpropagation model would have been poor. In this way, the performance assessment of machine learning is judged to be better learned than previous studies. Our portfolio doubled the return on the benchmark and performed better than the market returns on the KOSPI and KOSPI 200 indexes. In contrast to the benchmark, the MDD and standard deviation for portfolio risk indicators also showed better results. The Sharpe Ratio performed higher than benchmarks and stock market indexes. Through this, we presented the direction of portfolio composition program using machine learning and investor-specific transaction information and showed that it can be used to develop programs for real stock investment. The return is the result of monthly portfolio composition and asset rebalancing to the same proportion. Better outcomes are predicted when forming a monthly portfolio if the system is enforced by rebalancing the suggested stocks continuously without selling and re-buying it. Therefore, real transactions appear to be relevant.

• Journal of the Korean Applied Science and Technology
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• v.38 no.1
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• pp.318-331
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• 2021

This study was conducted on the assumption that bone age would be more effective when it comes to physique and physical fitness assessment for adolescents, and the purpose of this study was to identify the differences in physique and physical fitness for students in their adolescence through bone age and chronological age in order to contribute to the well-balanced physique and physical fitness development in adolescents and the health improvement in students. Total 874 adolescents(483 males, 391 females) aged 11~16 were selected as subjects out of the total population of 1100 adolescents aged 6~16 based on the PAPS(Physical Activity Promotion System) and age standards of the TW3 method; and skeletal maturation, which symbolize the indicators of biological maturation, were evaluated by using the TW3(Tanner-Whitehouse 3) method after hand-wrist radiographs, and birth date was used for chronological age. A stadiometer and InBody 270 (Biospace, Korea) were used to measure 2 components in physique. A total of 7 components in physical fitness, which included muscular strength, muscular endurance, flexibility, power, cardiovascular endurance, balance, agility, were measured as well. A independent samples t-test was conducted for data processing using SPSS 25.0, and the significance level was set at p< .05. The study results are as follows. First, bone age and chronological age used for physique comparison in males aged 11 and 12, height and weight showed significant difference; in males aged 13, weight showed signicant difference. Weight and height in females aged 11, and height in females aged 12 showed significant difference. Second, bone age and chronological age used for physical fitness comparison in males aged 11, muscular strength, power, flexibility, cardiovascular endurance showed significant difference; in males aged 12, muscular strength. power, cardiovascular endurance; in males aged 13, flexibility showed significant difference. Muscular strength, power, flexibility, muscular endurance, cardiovascular endurance in females aged 11, and flexibility in females aged 14 showed significant difference. As a result, this study concluded that in a period of rapid skeletal growth, evaluating physique and physical fitness based on bone age is more accurate than evaluating based on chronological age.

• Korean Journal of Culture and Social Issue
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• v.29 no.3
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• pp.361-404
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• 2023

This study utilized a cross-temporal meta-analysis to explore shifts in self-efficacy levels among Korean college students from 1999 to 2022. We expected that increases in authoritative parenting styles, narcissism levels among students, and individualism in Korea might have positively influenced the self-efficacy of college students over the years. Conversely, growing economic disparities, decreasing class mobility, and the increasing instability of job markets might have had negative effects on self-efficacy. To investigate this, we analyzed 293 self-efficacy studies involving Korean college students published between 1999 and 2022, encompassing a total of 88,904 participants. Our criteria included studies that used the three most prevalent self-efficacy scales in Korea, focused solely on Korean college students, were cross-sectional with a one-time self-efficacy measurement, and provided essential statistics for our analysis. The results indicated no significant change in the self-efficacy levels of Korean college students over the observed period from 1999 to 2022. Additionally, we examined correlations between self-efficacy and various social indicators from different time points (20, 15, 10, and 5 years prior, as well as the year of data collection). Findings revealed that both birth rate and consumer price fluctuation rate were consistently negatively correlated with self-efficacy, while gross national income was positively correlated. This study is the first to assess Korean college students' self-efficacy levels using a cross-temporal meta-analysis, offering foundational knowledge for implementing such analytical methods for subsequent research and providing an indirect assessment of the generational gap theory. Finally, the limitations of the study and the direction for future research were discussed.

• Korean Journal of Environmental Biology
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• v.40 no.2
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• pp.172-186
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• 2022

Benthic macroinvertebrates are important ecological and environmental indicators as primary or secondary consumers, and therefore are widely used in the evaluation of aquatic environments. However, there are no comprehensive river ecosystem monitoring surveys that link the major physicochemical water quality items with benthic macroinvertebrates in urban streams. Therefore, this study investigated the distribution characteristics of benthic macroinvertebrates and physicochemical water quality items (17 items) in Yangjaecheon and Yeouicheon from 2019 to 2020. At the same time, by applying Spearman's rank correlation analysis and nonmetric multidimensional scaling (nMDS) analysis in the water quality data and biotic index, we tried to provide basic data for diagnosing the current status of river ecosystems in major urban rivers in Seoul. Based on the study results, a total of 39 species and 3,787 individuals were identified in Yangjaecheon, the water quality(based on BOD, TOC, and TP) of Yangjaecheon was higher than Grade Ib(good), and the BMI using benthic macroinvertebrates appeared as Grade C(normal) at all the sites. In Yeouicheon, a total of 51 species and 4,199 individuals were identified, the water quality(based on BOD, TOC, TP) was higher than Grade Ib(good) similar to Yangjaecheon, and the BMI of both Upstream and Saewon bridge was Grade B(good), while Yeoui bridge was Grade C(normal). Overall, analysis results for the distribution of benthic macroinvertebrates by a nonmetric multidimensional scaling method showed no significant difference between the two streams (p=0.1491). Also, significant environmental variables related to benthic macroinvertebrates distribution were determined as water temperature and DO. On the other hand, the results of the correlation analysis between biotic index and major water quality items confirmed that R1 and BMI could be used for on-site urban river water quality evaluation.