• 기술혁신연구
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• 제14권1호
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• pp.67-99
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• 2006

Utilizing the patent application data between 1997 and 2002, this study focuses on analysing the impact of patents on firm value. Especially we attempt to examine the difference of patents between venture firms and general firms. This paper first shows that the number of the patent applications of general firms listed on the securities market is more than that of venture firms listed on KOSDAQ. It is thought that this result is originated from the facts that the size of firms of the securities market is usually bigger than that of the firms of KOSDAQ and that these large firms could manage R&D more efficiently. Second, this paper reports that there is no difference in the ratio of patent maintenance between venture firms and general firms. Both venture firms and non-venture firms would do their best to keep their patents after patent regisration. Third, in the regression of patent index and firm growth, we find that the excellence of patent and the number of patents per employee would have an impact on the growth of firms. Fourth, the regression of patent index and profitability shows that the excellence and the number of patents per employee might have an effect on the profitability of firms.

• 응용통계연구
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• 제27권1호
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• pp.159-168
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• 2014

Engle과 Ng (1993)가 제안한 뉴스 임팩트 커브(NIC)는 표준적인 GARCH 모형에 적용되는 대칭 커브이다. 최근들어 금융시계열의 변동성이 비대칭 성질을 가지는 경향이 있으며 이에 따라 분계점(threshlod) GARCH, 이중선형(bilinear) GARCH 등의 비대칭 모형이 연구되고 있다. 본 논문은 비대칭 모형의 변동성 커브에 대해 연구하고 있으며 LASSO를 통한 방법론을 제안하고 있다. 제시된 방법론을 국내 KOSDAQ 자료분석을 통해 예시해 보았다.

• 한국산학기술학회논문지
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• 제13권2호
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• pp.878-884
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• 2012

본 연구에서는 건설 기업을 중심으로 기업의 경영 효율성과 배당성향을 중심으로 한 효율적 포트폴리오를 선택하는 전략을 제시한다. 기업의 경영 효율성을 포트폴리오 선택에 반영하는 방안으로 DEA(Data Envelopment Analysis) 기법을 사용하였고 성장가능성은 기업의 배당 성향을 판단하는 배당 스코어링 테이블을 이용하여 평가하였다. 본 연구에서 제안한 포트폴리오 선택전략의 성능 실험을 위해 KOSPI와 KOSDAQ에 상장된 56개의 건설 산업 관련 기업의 주식을 대상으로 2007~2010년의 4년 동안 매해 3그룹의 포트폴리오를 구성하였고 각각의 포트폴리오 수익률을 벤치마크 수익률과 비교 분석하여 그 성능을 입증하였다.

• 한국IT서비스학회지
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• 제15권3호
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• pp.1-14
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• 2016

According to the growing importance of science and technology policy, investment in research and development (R&D) has been increased. In this context, a patent as one of outcome of firm's systematic R&D investment is the way to hold a dominant position in companies' technology competitiveness and also to protect technology right. This study attempts to find the effects of input resources and intellectual property production activity on company value. It conducted empirical analysis based on 238 KOSDAQ-listed and medium-sized firms. Using the previous research, this study configurated research variables about activity of patent production, company value, and input of resources. Through these variables, it aims to know the effect of input of resources and activity of patent production on company value. First, the result of regression analysis shows that R&D cost has the positive effect on a patent production and sales promotion cost positively affects on the registration of the trademark. Second, the output of regression analysis indicates that a patent has the positive effect on company value but a trademark has not. With regard to the input of resources, R&D cost has the influence on company value but sales promotion cost has not. This study attempts to find the effectiveness of company's intellectual property registration on its value and suggests a way that the systematic R&D investment contributes the growth of company value.

• 지능정보연구
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• 제7권2호
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• pp.95-115
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• 2001

본 논문에서는 우리나라 코스닥시장에 상장된 벤처기업을 대상으로 하여 지식경영 유형을 세분화 하기 위한 방법론을 제시한다. 이 방법론은 우선, 해당 벤처기업에 대하여 설문조사를 통하여 이들 회사의 지식경영 요인을 도출한 다음, 이들 요인 값을 가지고 비감독학습 인공신경망 모형인 SOM을 가지고 4개의 의미 있는 군집을 유도하였다. 이들 군집은 벤처기업이 수행하는 다양한 지식경영 유형을 나타내는 것으로 판명되었으며, 이들 유형은 각각 하이테크형, 조직지식중심형, 정보기술 중심형, 단순형으로 분류된다.

• 한국정보시스템학회지:정보시스템연구
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• 제27권3호
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• pp.123-140
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• 2018

Purpose The purpose of this study is to explore the optimal trading frequency which is useful for stock price prediction by using deep learning for charting image data. We also want to identify the appropriate time for accurate forecasting of stock price when performing pattern analysis. Design/methodology/approach In order to find the optimal trading frequency patterns and forecast timings, this study is performed as follows. First, stock price data is collected using OpenAPI provided by Daishin Securities, and candle chart images are created by data frequency and forecasting time. Second, the patterns are generated by the charting images and the learning is performed using the CNN. Finally, we find the optimal trading frequency patterns and forecasting timings. Findings According to the experiment results, this study confirmed that when the 10 minute frequency data is judged to be a decline pattern at previous 1 tick, the accuracy of predicting the market frequency pattern at which the market decreasing is 76%, which is determined by the optimal frequency pattern. In addition, we confirmed that forecasting of the sales frequency pattern at previous 1 tick shows higher accuracy than previous 2 tick and 3 tick.

• 응용통계연구
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• 제21권3호
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• pp.537-546
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• 2008

시계열자료 분석에 있어 주요 목적 중에 하나는 미래에 대한 예측 값을 추정하는 것이다. 이 논문에서는 정상자기회귀이동평균 모형에서 변환-역변환 방법을 이용하여 예측값을 구하는 과정에서 발생하는 문제에 대해 알아보고 회귀분석에서 제안되었던 smearing 추정방법을 시계열분석에서 사용할 수 있도록 붓스트랩을 이용하여 수정한 추정법을 소개한다. Yeo-Johnson 변환 (2000)을 이용한 KOSDAQ지수의 수익률 실증분석을 통해 기존에 사용되고 있는 방법의 문제점과 제안된 방법의 적절성에 대해 고찰해 보았다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권5호
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• pp.1630-1648
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• 2021

Owing to the unprecedented COVID-19 pandemic, the pharmaceutical industry has attracted considerable attention, spurred by the widespread expectation of vaccine development. In this study, we collect relevant topics from news articles related to COVID-19 and explore their links with two South Korean pharmaceutical indices, the Drug and Medicine index of the Korea Composite Stock Price Index (KOSPI) and the Korean Securities Dealers Automated Quotations (KOSDAQ) Pharmaceutical index. We use generalized Dirichlet-multinomial regression (g-DMR) to reveal the dynamic topic distributions over metadata of index values. The results of our analysis, obtained using g-DMR, reveal that a greater focus on specific news topics has a significant relationship with fluctuations in the indices. We also provide practical and theoretical implications based on this analysis.

• 한국멀티미디어학회논문지
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• 제24권3호
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• pp.448-459
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• 2021

In this paper, we propose a method of predicting the next-day stock price fluctuations of 10 KOSDAQ-listed companies in 5G, autonomous driving, and electricity sectors by training SVM, XGBoost, and LightGBM models from macroeconomic·financial market indicators, technical indicators, social interest indicators, and daily positive indices extracted from online news. In the three experiments to find out the usefulness of social interest indicators and daily positive indices, the average accuracy improved when each indicator and index was added to the models. In addition, when feature selection was performed to analyze the superiority of the extracted features, the average importance ranking of the social interest indicator and daily positive index was 5.45 and 1.08, respectively, it showed higher importance than the macroeconomic financial market indicators and technical indicators. With the results of these experiments, we confirmed the effectiveness of the social interest indicators as alternative data and the daily positive index for predicting stock price fluctuation.

• 아태비즈니스연구
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• 제13권1호
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• pp.247-262
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• 2022

Purpose - The purpose of this study is to examine the impact of the Pandamic Declaration on 'untact firms' listed in KOSPI and KOSDAQ market in order to verify Investor Mania Hypothesis. Design/methodology/approach - This study collected financial data for 44 untact firms in KOSPI and KOSDAQ market. Then, we employed ESM(Event Study Methodology), EGARCH model and DID(Difference-In-Difference) for analysis. Findings - First, in contrast with the benchmarking index, KOSPI 200 which shows a negative (-) abnormal return trend, the untact firms have positive abnormal return trend consistently. Second, after the Pandemic Declaration, the variability of abnormal return for the untact firms is found to be significantly positive. Third, we find that the cumulative abnormal return and volatility of the untact firms significantly increase after the Pandemic Declaration. Research implications or Originality - Based on the Investor Mania Hypothesis, we confirm that the market potential of untact firms after the Pandemic Declaration is observed when compared with the KOSPI 200.