• Journal of the Korean Operations Research and Management Science Society
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• v.21 no.3
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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.

• The Journal of Industrial Distribution & Business
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• v.9 no.6
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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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• v.9 no.4
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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.

• The KIPS Transactions:PartD
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• v.16D no.2
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• pp.169-176
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• 2009

Rule discovery is an operation that discovers patterns frequently occurring in a given database. Rule discovery makes it possible to find useful rules from a stock database, thereby recommending buying or selling times to stock investors. In this paper, we discuss storage structures for efficient processing of queries in a system that recommends stock investments. First, we propose five storage structures for efficient recommending of stock investments. Next, we discuss their characteristics, advantages, and disadvantages. Then, we verify their performances by extensive experiments with real-life stock data. The results show that the histogram-based structure improves the query performance of the previous one up to about 170 times.

• Journal of KIISE:Databases
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• v.30 no.2
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• pp.209-224
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• 2003

Recent development of electronic commerce enables the use of Electronic Stock Trading Systems(ESTS) to be expanded. In ESTS, information with various sensitivity levels is shared by multiple users with mutually different clearance levels. Therefore, it is necessary to use Multilevel Secure Database Management Systems(MLS/DBMSs) in controlling concurrent execution among multiple transactions. In ESTS, not only analytical OLAP transactions, but also mission critical OLTP transactions are executed concurrently, which causes it difficult to adapt traditional secure transaction management schemes to ESTS environments. In this paper, we propose Secure One Snapshot(SOS) protocol that is devised for Secure Transaction Management in ESTS. By maintaining additional one snapshot as well as working database SOS blocks covert-channel efficiently, enables various real-time transaction management schemes to be adapted with ease, and reduces the length of waiting queue being managed to maintain freshness of data by utilizing the characteristics of less strict correctness criteria. In this paper, we introduce the process of SOS protocol with some examples, and then analyze correctness of devised protocol.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.3
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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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• v.10 no.1
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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.

• Journal of the Korea Safety Management & Science
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• v.6 no.2
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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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• v.8 no.1
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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.

• Proceedings of the KSR Conference
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• 2004.06a
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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.