• 한국경영과학회지
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• 제21권3호
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• pp.197-214
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• 1996

Financial analysis of stock data usually involves extensive computation of large amount of time series data sets. To handle the large size of the data sets and complexity of the analyses, database management systems have been increasingly adaopted for efficient management of stock data. Specially, relational database management system is employed more widely due to its simplistic data management approach. However, the normalized two-dimensional tables and the structured query language of the relational system turn out to be less effective than expected in accommodating time series stock data as well as the various computational operations. This paper explores a new data management approach to stock data management on the basis of an object-oriented database management system (ODBMS), and proposes a data model supporting times series data storage and incorporating a set of financial analysis functions. In terms of functional stock data analysis, it specially focuses on a primitive set of operations such as variance of stock data. In accomplishing this, we first point out the problems of a relational approach to the management of stock data and show the strength of the ODBMS. We secondly propose an object model delineating the structural relationships among objects used in the stock data management and behavioral operations involved in the financial analysis. A prototype system is developed using a commercial ODBMS.

• 산경연구논집
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• 제9권6호
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• pp.49-55
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• 2018

Purpose - This paper examines the effect of related party transactions on crash firm-specific stock price crash risk. Ownership of a typical Korean conglomerate is concentrated in a single family. In those entities, management and board positions are often filled by family members. Therefore, a dominant shareholder can benefit from related party transactions. In Korea, firms have to report related party transactions in financial statement footnotes. However, those are not disclosed in detail. The more related party transactions are the greater information risk. Thus, companies with related party transactions are likely to experience stock price crashes. Research design, data, and methodology - 2,598 firm-year observations are used for the main analysis. Those samples are from TS2000 database from 2009 to 2013, and the database covers KOSPI-listed firms in Korea. The proxy for related party transactions (RTP) is calculated by dividing total transactions to the related-party by total sales. A dummy variable is used as a dependent variable (CRASH) in the regression model. Logistic regression is used to explain the relationship between related party transactions and crash risk. Then, the sample was separated into two groups; tunneling firms and propping firms. The relation between related party transactions and crash risk variances with features of the transaction were investigated. Results - Using a sample of KOSPI-listed firms in TS2000 database for the period of 2009-2013, I find that stock price crash risk increases as the trade volume of related-party transactions increases. Specifically, I find that the coefficient of RPT is significantly positive, supporting the prediction. In addition, this relationship is strong and robust in tunneling firms. Conclusions - The results report that firms with related party transactions are more likely to experience stock price crashes. The results mean that related party transactions increase the possibility of future stock price crashes by enlarging information asymmetry between controlling shareholders and minority shareholders. In case of tunneling, it could be seen that related party transactions are positively associated with stock crash risk. The result implies that the characteristic of the transaction influences crash risk. This study is related to a literature that investigates the effect of related party transactions on the stock market.

• Journal of Information Technology Applications and Management
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• 제9권4호
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• pp.65-78
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• 2002

We propose a new application method of the datamining technique that might help building an efficient trade strategy in the stock market, where the analysis of the huge database is essential. The proposed method utilizes the association rules among the price changes of individual stock from the market basket analysis (a datamining technique typically used in the Marketing field) in building the strategy We also apply the proposed method to the daily stock prices in Korean stock market, from Jan. 2000 to Dec. 2001. The application results show that the proposed method gives an significantly higher yield rate than the actual stock chage rate.

• 정보처리학회논문지D
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• 제16D권2호
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• pp.169-176
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• 2009

규칙 탐사는 주어진 데이터베이스로부터 빈번하게 발생하는 패턴들을 발견하는 연산이다. 규칙 탐사 연산을 이용하여 주식 데이터베이스로부터 유용한 규칙들을 발견하고 이를 토대로 주식 투자자들에게 주식의 매매를 적절한 시점에 추천할 수 있다. 본 논문에서는 이러한 주식 투자 시스템에서 질의를 효율적으로 처리하기 위한 저장 구조에 관하여 논의한다. 먼저, 주식 투자 추천을 지원하기 위한 다섯 가지 저장 구조들을 제안하고, 각 구조들의 특징과 장단점을 비교한다. 또한, 실제 주가 데이터를 이용한 실험을 통하여 제안된 저장 구조들의 성능을 검증한다. 실험 결과에 의하면, 히스토그램을 이용한 저장 구조의 경우, 기존의 기법에 비하여 질의 처리 성능이 약 170배 개선되는 것으로 나타났다.

• 한국정보과학회논문지:데이타베이스
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• 제30권2호
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• pp.209-224
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• 2003

최근 전자 상거래 인프라의 발전으로 인해, 온라인 상에서 주식의 매매가 이루어지는 전자 주식 매매 시스템(Electronic Stock Trading Systems: 약칭 ESTS)의 사용이 확산되고 있다. ESTS 상에서는 다양한 기밀 등급을 가진 정보가 서로 다른 신뢰 등급을 갖는 사용자에 의해 공유된다. 특정 정보가 허가된 사용자에 의해서만 접근되도록 보장하기 위해서는, 트랜잭션의 동시성 제어 과정에서의 다등급 보안 데이타베이스 시스템의 사용이 반드시 필요하다. 한편 ESTS 상에서는 분석적인 성향의 트랜잭션과, 매매 체결을 목적으로 하는 실시간 트랜잭션이 동시에 수행되므로, 기존에 고안된 여러 보안 동시성 제어 기법들이 적용되는 데 어려움이 있다. 본 논문에서는 ESTS 환경에서의 보안 동시성 제어를 위한 프로토콜인 보안 단일 스냅샷(Secure One Snapshot: 약칭 SOS) 프로토콜을 제안한다. SOS는 운용 데이터베이스 외에 하나의 스냅샷을 추가로 유지하여 비밀 경로의 생성 가능성을 차단함과 동시에 실시간 동시성 제어 알고리즘이 용이하게 적용될 수 있는 유열성을 제공한다. 또한 SOS는 완화된 정확성 기준을 사용함으로써 데이타의 신선도를 유지하기 위해 관리되는 큐의 길이를 감소시킬 수 있는 방법도 제시한다. 본 논문에서는, SOS의 동작 과정을 예를 통해 소개하고, 프로토콜의 정확성에 대한 분석을 제공한다.

• The Journal of Asian Finance, Economics and Business
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• 제9권3호
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• pp.195-202
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• 2022

This study investigates whether institutional investors increase or decrease the volatility of stock returns in the Thai stock market. For the purpose we used the data from SETSMART, a database provided by the Stock Exchange of Thailand (SET). Our sample is a balanced panel data covering 3,160 firm-year observations from 316 nonfinancial firms listed on the SET from 2011 to 2020. We analyze the link between institutional holdings and the volatility of stock returns by the pooled Ordinary Least Squares (OLS) model, the fixed effects model, and the random-effects model. In particular, we regress the stock return volatility on institutional ownership while controlling for firm size, financial leverage, growth opportunities, and stock turnover and accounting for industry effects and year effects. Our results indicate institutional investors' positive and significant influence on the volatility of the stock returns. Additionally, we performed the dynamic Generalized Method of Moment (GMM) estimator to alleviate concerns of possible endogeneity. The result still shows a positive impact of institutional investors on the volatility in stock returns. Overall, the findings of this study suggest that an increase in the volatility of stock returns in the Thai stock market may stem from a higher proportion of equity held by the institutional investors.

• Asian Journal of Business Environment
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• 제10권1호
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• pp.19-28
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• 2020

Purpose: This research aims to investigate the impact of corporate integrity on stock price crash risk. Research design, data, and methodology: Taking 1419 firms listed in Shenzhen Stock Exchange in China as a sample, this paper empirically analyzed the relationship between corporate integrity and stock price crash risk. The main integrity data was hand-collected from Shenzhen Stock Exchange Website. Other financial data was collected from CSMAR Database. Results: Findings show that corporate integrity can significantly decrease stock price crash risk. After changing the selection of samples, model estimation methods and the proxy variable of stock price crash risk, the conclusion is still valid. Further research shows that the relationship between corporate integrity and stock price crash risk is only found in firms with weak internal control and firms in poor legal system areas. Conclusions: Results of the study suggest that corporate integrity has a significant influence on behaviors of managers. Business ethics reduces the likelihood of managers to overstate financial performance and hide bad news, which leads to the low likelihood of future stock price crashes. Meanwhile, corporate integrity can supplement internal control and legal system in decreasing stock price crash risks.

• 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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• 제8권1호
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• pp.7-14
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• 2021

This paper examines the impact of foreign ownership on stock price volatility in an emerging market, namely, Thailand. The data were obtained from SETSMART, the database of the Stock Exchange of Thailand (SET). After removing financial firms, banks, and insurance companies as well as filtering outliers, the final sample covers 1,755 firm-year observations from 371 nonfinancial firms listed on the SET over the five-year period from 2014 to 2018. The regression model consists of stock price volatility, measured by two methods, as the dependent variable, foreign ownership as the main independent variable, and firm characteristics including firm size, leverage, market-to book ratio, and stock turnover as the control variables. The pooled OLS, fixed effects, and random effects estimations are employed to examine the relationship between foreign ownership and stock price volatility. The results reveal that foreign ownership has a negative and significant impact on stock price volatility. The two-stage least squares (2SLS) are also performed to address potential endogeneity problem. The results still indicate a negative relationship between foreign ownership and stock price volatility. Taken together, the findings of this study suggest that foreign investors help reduce stock price volatility and thus stabilize share price in the Thai stock market.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2004년도 춘계학술대회 논문집
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• pp.847-852
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• 2004

The virtual engineering technologies have been broadly used for the design, testing, manufacturing and maintenance works of industrial product. Recently many VR systems with walk through navigation and web databases; such as design and installation database. load history database, maintenance history database et al. are developed. However, the virtual engineering in railroad industry is not well developed compared to other industries like automobile, air, shipbuilding. In this paper, we explain the strategy that we have applied the virtual engineering technology to the design works of rolling stock and our plan to build the virtual testing laboratory(VTL) in the Korea Railroad Research Institute.