• 한국컴퓨터정보학회논문지
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• 제22권11호
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• pp.111-116
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• 2017

This paper proposes a data mining approach to predicting stock price direction. Stock market fluctuates due to many factors. Therefore, predicting stock price direction has become an important issue in the field of stock market analysis. However, in literature, there are few studies applying data mining approaches to predicting the stock price direction. To contribute to literature, this paper proposes comparing single classifiers and ensemble classifiers. Single classifiers include logistic regression, decision tree, neural network, and support vector machine. Ensemble classifiers we consider are adaboost, random forest, bagging, stacking, and vote. For the sake of experiments, we garnered dataset from Korea Stock Exchange (KRX) ranging from 2008 to 2015. Data mining experiments using WEKA revealed that random forest, one of ensemble classifiers, shows best results in terms of metrics such as AUC (area under the ROC curve) and accuracy.

• East Asian Economic Review
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• 제19권3호
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• pp.275-322
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• 2015

The key objective of this study is to investigate the return and volatility spillover effects among stock market, credit default swap (CDS) market and foreign exchange market for three countries: Korea, the US and Japan. Using the trivariate VAR BEKK GARCH (1,1) model, the study finds that there are significant return and volatility spillover effects between the Korean CDS market and the Korean stock market. In addition, the return spillover effects from foreign exchange markets and the US stock market to the Korean stock market, and the volatility spillover effect from the Japanese stock market to the Korean stock market are both significant.

• Asia pacific journal of information systems
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• 제11권4호
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• pp.99-111
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• 2001

The prediction of stock price index is a very difficult problem because of the complexity of stock market data. It has been studied by a number of researchers since they strongly affect other economic and financial parameters. The movement of stock price index has a series of change points due to the strategies of institutional investors. This study presents a two-stage forecasting model of stock price index using change-point detection and artificial neural networks. The basic concept of this proposed model is to obtain intervals divided by change points, to identify them as change-point groups, and to use them in stock price index forecasting. First, the proposed model tries to detect successive change points in stock price index. Then, the model forecasts the change-point group with the backpropagation neural network(BPN). Finally, the model forecasts the output with BPN. This study then examines the predictability of the integrated neural network model for stock price index forecasting using change-point detection.

• 정보처리학회논문지:소프트웨어 및 데이터공학
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• 제3권10호
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• pp.441-450
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• 2014

주식시장은 항상 변하며 특별한 이유 없이도 주가가 급락하거나 급등하는 현상도 나타난다. 그러므로 주식시장은 복잡계로 인식되고 있으며, 주가의 변화는 예측하기 어렵다. 최근에 많은 연구자는 주식시장을 개별 주식 간의 네트워크로 간주하고 그것을 이해하려고 하며, 인터넷에서 실시간으로 생성되는 빅데이터를 통해 주가의 변화를 밝히려고 노력하고 있다. 우리는 주가와 인터넷 특히 주식토론방에 나타나는 사람들의 반응 간의 상관관계에 주목한다. 이 상관관계를 밝히기 위해서 KOSPI200에 속한 회사 중 57개 회사와 관련 있는 게시물들을 수집하고 분석하였다. 분석 결과에 따르면, 개별 주가와 게시물 수 사이에는 특별한 상관관계가 나타나지 않았지만, 주가와 게시물 수의 상관관계가 주식 수익률과 관계가 있는 것으로 나타났다. 우리는 이 분석결과를 기반으로 주식투자 포트폴리오를 추천하는 새로운 방법을 제안한다. '다음' 포털의 주식토론방 데이터를 이용한 모의 투자 실험 결과에서, '다음' 주식토론방 데이터를 사용한 경우 제안 방법으로 구성한 주식 포트폴리오의 월평균 수익률은 약 1.55%로 마코위츠의 효율적 포트폴리오의 수익률보다 약 0.72% 높으며, 코스피 평균 수익률보다 약 1.21% 높게 나타났다. 또한 '네이버' 주식토론방 데이터를 사용한 경우는 모의 투자 수익률이 약 0.90%로 기존 방법과 마코위츠 효율적 포트폴리오와 코스피 평균 수익률보다 각각 0.35%와 0.40%, 0.58% 높게 나타났다. 이 연구는 인터넷 주식토론방에 나타난 사람들의 집단적인 행위는 주식시장을 이해하는 데 많은 도움을 줄 수 있으며, 주가와 사람들의 집단행위 사이의 상관관계가 주식투자에 활용될 수 있음을 제시하였다.

• 복식
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• 제51권2호
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• pp.53-64
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• 2001

The purpose of this study is to create the program for efficient inventory management and reduction, investigating the present conditions and factors of the inventory throughout current apparel industry. The research method applied in this study is to survey 92 domestic companies which were randomly selected with respect to the kinds of goods produced : men′s wear, women′s wear, and unisex wear. The research can be summarized as follows : 1. The seasonal stock rate of current apparel industry was 28.75%, and the rate of men′s wear companies was higher than that of women′s and unisex wear companies. 19.43% of stock cost reflection rate was applied, and the stack cost of men′s and women′s wear companies was higher than that of unisex wear companies. 2. Periodic bargain sale was the most frequently used way of stock clearance, and "uniform price sale"and outlet stores were the second and the third irrespectively. Unisex wear companies appeared to be more enthusiastic in stock clearance than the companies belonging to the other two categories. The main places for the stock clearance were department stores, outlet stores and enterprises specialized in the stock clearance. 3. QR production was proved to be the most commonly adjusted method of stock reduction, and the emphasis on development of new design and the utilization of stock management system through computer network were the next, While unisex wear companies had established the positive policies, men′s wear companies took lukewarm altitudes in every aspect. The companies selling on an order were 18.64%, and unisex wear companies showed the higher rate. The lead-time after QR production was 10.91 days, and it seemed to take more time for men′s wear companies than for women′s and unisex wear companies. The rate of the chance in stock was proved to decrease by 12.94%, and there was found no meaningful difference among the three categories of apparel companies.

• 국제지역연구
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• 제18권3호
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• pp.67-88
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• 2014

본 연구에서는 중국시장을 중심으로 수익률 전이현상(return spillover effect) 및 변동성 전이현상(volatility spillover effect)을 이변량 VAR-EGARCH 모형을 이용하여 실증 분석하였다. 그리고 최근의 글로벌 금융위기를 중심으로 금융위기 이전과 이후로 나누어서 전이효과를 실증 분석하였다. 실증분석 결과, 전체기간에서 중국으로부터 일본 만이 수익률 전이현상을 가지고 있었고 변동성 전이현상은 미국뿐만 아니라 일본, 한국에게도 모두 영향을 주었다. 기간을 나누어서 분석한 결과, 금융위기 전에는 일본과 한국에게 수익률 전이현상을 가지고 있었고 금융위기 후 그 크기가 상대적으로 증가한 것으로 나타났다. 또한, 중국의 변동성 전이현상도 한국에게 영향을 주고 미국으로부터 영향을 받다가, 금융위기 후 한국을 제외한 미국과 일본은 중국과 양방향의 관계를 가지고 있었고 그 크기가 증가하였다. 하지만 미국으로부터 중국으로의 변동성 전이현상은 감소하는 것으로 나타났다. 이는 글로벌 금융위기 이후 중국시장의 영향력이 증대되고 있음을 의미한다.

• 산경연구논집
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• 제11권12호
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• pp.39-45
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• 2020

Purpose: The stock price delay phenomenon refers to a phenomenon in which stock prices do not immediately reflect corporate information and the reflection is delayed. A prior study reported that the stock price delay phenomenon appears strongly when the quality of corporate information is low (Callen, Khan, & Lu, 2013). The purpose of the internal accounting control system is to improve the reliability of accounting information. Specifically, the more professionals such as certified public accountants are placed in the internal accounting control system, the more information is prevented from being distorted, so the occurrence of stock price delay will decrease. Research design, data and methodology: In this study, companies listed on the securities market from 2012 to 2016 were selected as a sample to analyze whether the stock price delay phenomenon is alleviated as accounting experts are assigned to the internal accounting control system. The internal control personnel data were collected in the "Internal Accounting Control System Operation Report" attached to the business report of each company of the Financial Supervisory Service's Electronic Disclosure System(DART). The measurement method of the stock price delay phenomenon was referred to the study of Hou and Moskowitz (2005). The final sample used in the study is 2,641 firm-years. Results: It was found that companies with certified accountants in the internal accounting control system alleviate the stock price delay phenomenon. This result can be interpreted as increasing the speed at which corporate information is reflected in the stock price by improving the reliability of information disclosed in the market by the placement of experts in the system. Conclusions: The results of this study suggest that accounting professionals assigned to the internal accounting control system are playing a positive role in providing high-quality information to the market. In this study, focusing on the fact that the speed at which corporate information is reflected in the stock price is very important for the stakeholders in the capital market, we find that having a certified public accountant in the internal accounting control system alleviates the stock price delay phenomenon.

• International journal of advanced smart convergence
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• 제12권1호
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• pp.18-30
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• 2023

We compared empirically the forecast accuracies of the LSTM model, and the ARIMA model. ARIMA model used auto.arima function. Data used in the model is 100 days. We compared with the forecast results for 50 days. We collected the stock closing prices of the top 4 companies by market capitalization in Korea such as "Samsung Electronics", and "LG Energy", "SK Hynix", "Samsung Bio". The collection period is from June 17, 2022, to January 20, 2023. The paired t-test is used to compare the accuracy of forecasts by the two methods because conditions are same. The null hypothesis that the accuracy of the two methods for the four stock closing prices were the same were rejected at the significance level of 5%. Graphs and boxplots confirmed the results of the hypothesis tests. The accuracies of ARIMA are higher than those of LSTM for four cases. For closing stock price of Samsung Electronics, the mean difference of error between ARIMA and LSTM is -370.11, which is 0.618% of the average of the closing stock price. For closing stock price of LG Energy, the mean difference is -4143.298 which is 0.809% of the average of the closing stock price. For closing stock price of SK Hynix, the mean difference is -830.7269 which is 1.00% of the average of the closing stock price. For closing stock price of Samsung Bio, the mean difference is -4143.298 which is 0.809% of the average of the closing stock price. The auto.arima function was used to find the ARIMA model, but other methods are worth considering in future studies. And more efforts are needed to find parameters that provide an optimal model in LSTM.

• 아태비즈니스연구
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• 제13권4호
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• pp.45-59
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• 2022

Purpose - This study investigates the performance of investment strategies incorporating estimated stock market cycle based on a lead-lag relationship between business cycle and stock market cycle, thereby deriving empirical implications on risk management. Design/methodology/approach - The data period ranges from June 1953 to September 2022 and de-trended short rate, term spread, credit spread, stock market volatility are considered as major input variables to estimate business cycle and stock market cycle by applying probit model. Based on the estimated stock market cycle, two types of strategies are constructed and their performance relative to the benchmark is empirically examined. Findings Two types of strategies based on stock market cycle are considered: The first strategy is to long(short) on stocks when stock market stage is expected to be an expansion(a recession), and the second one is to long on stocks(bonds) when expecting an expansion(a recession). The empirical results show that the strategies based on stock market cycle outperforms a simple buy and hold strategy in both in-sample and out-of-sample investigation. Also the out-of-sample evidence suggests that the second strategy which is in line with asset allocation is more profitable than the first one. Research implications or Originality The strategies considered in this study are based on the estimated stock market cycle which only depends on a few easily available financial variables, thereby making easier to establish such a strategy. It implies that investors enhance investment performance by constructing a relatively simple trading strategies if they set their position on stocks or choose which asset class to buy conditioning on stock market cycle.

• 벤처창업연구
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• 제18권6호
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• pp.1-10
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• 2023

최근 스타트업과 벤처기업의 임직원이 기업 상장 후 적법한 절차에 따라 스톡옵션 행사를 하였지만, 상장 후 일시 매도로 주식시장의 주가에 악영향을 미치며 일반투자자 피해가 발생하는 등 도덕적 해이 논란이 촉발되었다. 이에 정부 당국은 스톡옵션 즉 주식매수선택권 제도에 대해 의무 보호 대상에 포함시키는 규제를 진행함에 따라 더 이상 스톡옵션이 스타트업과 벤처기업의 우수 인력확보 수단이 되기 어렵다는 논란이 제기되고 있다. 본 논문은 우수한 인력확보가 절실한 초기스타트업들에게 양도제한조건부주식(Restricted Stock Unit, 이하 RSU)제도 도입방안을 제시함으로써 주식매수선택권 제도(Stock Option, 이하 스톡옵션)의 문제점을 극복하는 돌파구를 제시하는 것이 목적이다. 이를 위해, 본 논문에서는 첫째, RSU의 국내 도입현황과 이의 개념을 제한조건부주식(Restricted Stock, 이하 RS)과 비교논의를 통해 제시하였다. 또한 RSU와 기존 스톡옵션제도의 특징을 비교설명하였다. 둘째, 탐색적 연구를 통해 RSU의 단점과 한계점을 설명하고 그 한계점을 극복하며 국내 스타트업과 벤처기업들이 이를 효과적으로 도입하는 방안을 제시하였다. 셋째 국내 관련 정책입안 과정에 참여하고 있는 법률전문가들을 대상으로 FGI를 실시하여 RSU 도입이 기존 스톡옵션제도의 문제점을 보완하며 스타트업 벤처 금융제도의 대안으로 안착할수 있는 방안에 대한 실증연구를 실시하였다. 넷째, 탐색적 연구와 실증연구를 토대로 스타트업 벤처금융 대안으로 RSU 도입 및 뿌리내림 위한 정책 방안들을 제안하였다. 이를 통해, 본 논문은 RSU가 기본 스톡옵션제도에 주어지는 도덕적 해이 논란을 벗어나, 스타트업의 새로운 주식연계형 보상 대안 역할을 할 수 있도록 하는 정책수립을 위한 이론적 기반을 제공하였다.