• 한국정보시스템학회지:정보시스템연구
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• 제32권1호
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• pp.179-199
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• 2023

Purpose This study builds a prediction model to find stocks that can reach intrinsic value among KOSPI and KOSDAQ-listed companies to improve the stability and profitability of the stock investment. And investment simulations are conducted to verify whether stock investment performance is improved by comparing the prediction model, random stock selection, and the market indexes. Design/methodology/approach Value investment theory and machine learning techniques are applied to build the model. Various experiments find conditions such as the algorithm with the best predictive performance, learning period, and intrinsic value-reaching period. This study selects stocks through the prediction model learned with inventive variables, does not limit the holding period after buying to reach the intrinsic value of the stocks, and targets all KOSPI and KOSDAQ companies. The stock and financial data are collected for 21 years (2001-2021). Findings As a result of the experiment, using the random forest technique, the prediction model's performance was the best with one year of learning period and within one year of the intrinsic value reaching period. As a result of the investment simulation, the cumulative return of the prediction model was up to 1.68 times higher than the random stock selection and 17 times higher than the KOSPI index. The usefulness of the prediction model was confirmed in that the number of intrinsic values reaching the predicted stock was up to 70% higher than the random selection.

• 벤처창업연구
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• 제12권2호
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• pp.21-29
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• 2017

주식 투자는 요즘 가장 대중적인 투자 중 하나이며, 주식시장에서 투자자들의 궁극적 목적은 이익극대화 및 손실최소화이며, 이를 달성하기 위해서 투자정보를 바탕으로 선택하게 된다. 또한 투자자는 위험에 대한 태도에 따라 투자성향에 영향을 받는다. 이러한 배경을 중심으로 본 연구는 개인투자자들의 투자성향과 투자정보탐색을 조사함으로서 투자자의 투자만족도에 미치는 영향력을 조명해보고자 한다. 또한 투자심리의 매개효과를 검증하고자 한다. 본 연구의 대상은 증권거래 경험이 있는 투자자이며, 설문 조사는 온라인으로 실시되었으며, 설문조사는 2016년 12월 1일~12월 30일까지 30일간 실시하였으며, 총 330부를 분석 자료로 이용하였다. 분석방법은 SPSS 21.0을 사용하여 기초통계, 신뢰도, 회귀분석을 수행하였다. 분석결과는 다음과 같다. 투자성향 중에서 수익추구성향, 분석추구성향, 투자추구성향이 투자성과에 영향을 미쳤다. 반면, 증권사 정보, 인적정보, 기업회계 정보는 투자성과에 유의미한 영향을 미쳤다. 마지막으로 자기과신 투자심리의 매개역할을 확인하였다.

• 한국경영과학회지
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• 제17권2호
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• pp.145-162
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• 1992

This paper proposes two design principles for expert systems to solve a stock market timing (SMART) problems : machine knowledge and fuzzy post-adjustment, Machine knowledge is derived from past SMART instances by using an inductive learning algorithm. A knowledge-based solution, which can be regarded as a prior SMART strategy, is then obtained on the basis of the machine knowledge. Fuzzy post-adjustment (FPA) refers to a Bayesian-like reasoning, allowing the prior SMART strategy to be revised by the fuzzy evaluation of environmental factors that might effect the SMART strategy. A prototype system, named K-SISS2 (Knowledge-based Stock Investment Support System 2), was implemented using the two design principles and tested for solving the SMART problem that is aimed at choosing the best time to buy or sell stocks. The prototype system worked very well in an actual stock investment situation, illustrating basic ideas and techniques underlying the suggested design principles.

• 대한안전경영과학회지
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• 제6권2호
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• pp.211-229
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• 2004

The basis of cyber trading has been sufficiently developed with innovative advancement of Internet Technology and the tendency of stock market investment has changed from long-term investment, which estimates the value of enterprises, to short-term investment, which focuses on getting short-term stock trading margin. Hence, this research shows a Short-term Stock Price Forecasting System on Learning Agent System using DTA(Decision Tree Algorithm) ; it collects real-time information of interest and favorite issues using Agent Technology through the Internet, and forms a decision tree, and creates a Rule-Base Database. Through this procedure the Short-term Stock Price Forecasting System provides customers with the prediction of the fluctuation of stock prices for each issue in near future and a point of sales and purchases. A Human being has the limitation of analytic ability and so through taking a look into and analyzing the fluctuation of stock prices, the Agent enables man to trace out the external factors of fluctuation of stock market on real-time. Therefore, we can check out the ups and downs of several issues at the same time and figure out the relationship and interrelation among many issues using the Agent. The SPFA (Stock Price Forecasting System) has such basic four phases as Data Collection, Data Processing, Learning, and Forecasting and Feedback.

• The Journal of Asian Finance, Economics and Business
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• 제8권3호
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• pp.11-21
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• 2021

In the last few years, there is growing interest in the field of simultaneous equation estimation in finance due to the endogeneity problem caused by measurement errors, simultaneity, or omitted variables. This study aims to discuss the endogeneity problem in corporate financing decisions and investigate the interrelationship of financial decision-making such as investment decision, dividend decision, and external financing decision in Pakistan Stock Exchange (PSX) using two-stage least squares (2SLS) and generalized method of moment (GMM) estimation. The Bruech-Pagan test shows that the data has no heteroskedasticity issue and 2SLS is a better approach in the context of this study as compared to the GMM approach, and internal instruments are also sufficiently strong and valid. The three financial decision-making attributes are not jointly determined, and the dividend is influenced by one-sided investment. In the emerging stock market context, external financing and investment are not inter-related and did not affect each other. The question of whether the simultaneous equation estimation can be useful in the context of the emerging stock markets and newly-growing firms remains unanswered. The inclusive evidence shows that the theoretical link in the emerging stock market is difficult to prove like in developed stock markets.

• 융합보안논문지
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• 제15권3_2호
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• pp.83-93
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• 2015

본 연구에서는 종합주가지수와 코스닥지수 그리고 융합보안 관련기업인 에스원, 안랩, 슈프리마, 라온시큐어, 이글루시큐리티의 주가를 이용하였다. 지난 2010년 8월에서 2014년 7월까지 총 4년(208주) 동안 지수 및 주가 동향을 파악하였다. 또한 보안 관련주의 기초통계량과, 분산분석, 상관분석, 각 주별 상승률동향 등 다양한 실증 분석을 시도하였다. 본 연구의 목적은 보안관련 기업들과 종합주가지수, 코스닥지수와의 상관관계를 살펴보는데 있다. 또한 각 기업들 주가흐름의 특징들을 파악하면서 투자가치가 있는지 분석하는데 있다. 향후 지식융합보안 산업의 높은 성장 가능성을 보았을 때 보안 관련기업들의 투자 가능성과 투자 메리트에 기대를 걸어보았다. 향후 성장 가능성이 높은 보안 관련기업에 대한 투자는 시장수익률 대비 높은 수익률을 보일 것으로 기대가 된다.

• Asia pacific journal of information systems
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• 제30권2호
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• pp.328-352
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• 2020

If a firm announces an investment in IT security, how the market value of its competitors reacts to the announcement? We try to shed light on this question through an event study design. To test the relationship, we collected 143 announcements on cybersecurity investment and measured the subsequent impact on 533 competitors' abnormal returns, spanning from 2000 to 2019. Our estimation results present that, on average, the announcements have no observable impact on the market value of announcing firms and competitors as well, which is consistent with findings of a prior study. Interestingly, however, the impact becomes evident when we classify our samples by industries (Finance vs. non-Finance or ICT vs. non-ICT) and firm size (Big vs. Small). We interpret our empirical findings through the lenses of contagion effect and competition effect between announcing firms and their competitors. Key finding of our study is that, for financial service firms, the effect resulting from the announcement on cybersecurity investment transfers to competitors in the same direction (i.e., contagion effect).

• International journal of advanced smart convergence
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• 제10권1호
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• pp.97-104
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• 2021

Securities and investment services had the most data per company on the average, and used the most data. Investors are increasingly demanding to invest through their own analysis methods. Therefore, securities and investment companies provide stock data to investors through open API. The data received using the open API is in text format. Python is effective and convenient for requesting and receiving text data. We investigate there are 22 major securities and investment companies in Korea and only 6 companies. Only Daishin Securities Co. supports Python officially. We compare how to receive stock data through open API using Python, and Python programming features. The open APIs for the study are Daishin Securities Co. and eBest Investment & Securities Co. Comparing the two APIs for receiving the current stock data, we find the main two differences are the login method and the method of sending and receiving data. As for the login method, CYBOS plus has login information, but xingAPI does not have. As for the method of sending and receiving data, Cybos Plus sends and receives data by calling the request method, and the reply method. xingAPI sends and receives data in the form of an event. Therefore, the number of xingAPI codes is more than that of CYBOS plus. And we find that CYBOS plus executes a loop statement by lists and tuple, dictionary, and CYBOS plus supports the basic commands provided by Python.

• The Journal of Asian Finance, Economics and Business
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• 제8권1호
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• pp.53-59
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• 2021

This research aims to examine the model of investor herding behavior in making investment decisions in the Indonesian capital market, which is influenced by social and information impacting on the value of the Book Value Per Share (BVPS). The latest stock market conditions show that most investors make the same error pattern in making investment decisions that result in losses. The experiment involves two independent variables, namely, information about BVPS and social influence. This study used a 2×2 factorial design laboratory experimental method. Data collection was carried out through treatment of a sample of 100 individual investors listed on the Indonesia Stock Exchange. Univariate Two-Way Analysis of Variance (ANOVA) statistical tool was used to test the independent variable on the dependent variable. Research results showed that the social influence originating from expert investors is more influential than the Book Value Per Share (BVPS) information on the behavior of herding investors in making investment decisions. These findings suggest that investors know their psychological factors, thereby increasing self-control and investment analysis skills. Further research can use psychological bias and other indicators of accounting relevant information such as Earning Per Share (EPS) to test herding behavior in investment decision making in the capital market.

• 산업공학
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• 제23권4호
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• pp.300-310
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• 2010

This paper is about an optimal investment portfolio strategy. Financial data of stocks, bonds, and savings from January 2. 2001 through October 30. 2009 were utilized in order to suggest the optimal portfolio strategies. Fundamental analysis and technical analysis were used in stocks-related strategy, whereas passive investment strategy and active investment strategy were used in bond-related strategy. The score is assigned to each stock index according to the suggested strategies and set trading rules are based on the scores. The simulation has been executed about each 29,400-portfolios and we figured out with the simulation result that 26.75% of 7,864 portfolios are more profitable than average stock market profit (22.6%, Annualized). The outcome of this research is summarized in two parts. First, it's the rebalancing strategy of portfolio. The result shows that value-oriented investment(long-term investment) strategy yields much higher than short-term investment strategies of stocks or active investment of bonds. Second, it's about the rebalancing cycle forming the portfolios. The result shows that the rate of return for the portfolio is the best when rebalancing cycle is 12 or 18 months.