• International Journal of Computer Science & Network Security
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• v.23 no.4
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• pp.166-171
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• 2023

The Stock price analysis is an increasing concern in a financial time series. The purpose of the study is to analyze the price parameters of date, high, low, and news feed about the stock exchange price. Long short term memory (LSTM) is a cutting-edge technology used for predicting the data based on time series. LSTM performs well in executing large sequence of data. This paper presents the Long Short Term Memory Model has used to analyze the stock price ranges of 10 days and 20 days by exponential moving average. The proposed approach gives better performance using technical indicators of stock price with an accuracy of 82.6% and cross entropy of 71%.

• Management & Information Systems Review
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• v.30 no.3
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• pp.217-239
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• 2011

The paper explores how corporate payout polish depends on managers' stock-option value. Specifically, this paper examine the relationship between managers' stock-option value and the ratio of stock repurchase, and analyze the relationship between price-incentive intensity of managers' stock-option and the ratio of stock repurchase. The hypotheses mentioned above are empirically tested using 137 firms listed on the Korean Exchange(KRX). OLS and Tobit regression method are used to above hypotheses. The results of this paper are as follows: First, as managers' stock option value increases, future the ratio of stock repurchase increase. Second, as the price-incentives intensity of managers' stock option increases, the patio of stock repurchase also increase. Overall, The above results imply that managers with stock option prefer stock repurchase over cash dividends to increase private benefits.

• The Korean Journal of Financial Management
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• v.20 no.1
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• pp.61-92
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• 2003

As an extension of previous researches with the conclusion that the announcement of adopting stock options generates positive abnormal returns, this paper examined whether the abnormal return changes over time or varies depending on the number of stock options granted. Empirical analysis was made to find whether the announcement of stock option awards has the same response in the stock market from the early days when stock option plans had been introduced in the Korean stock market till today when it was widespread. Results indicate that the announcement effect had been on a gradual decline since 2000. In addition, it is found that if a company announces stock option awards several times, the abnormal return gradually declines in proportion of the number of stock options granted. This implies that as the stock option awards become widespread, the positive effect that the announcement of adopting stock options generates as news has been on a relatively steady decrease. In short, it leads to a conclusion that the more companies grant stock options, and the more stock options a company announces, the less impact it has on the increase in the firm's value.

• Management & Information Systems Review
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• v.34 no.4
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• pp.15-29
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• 2015

This study aims to empirically analyze the relationship between management ownership and corporate performance and stock returns indicates the ownership structure of the company to target the listed companies in China over the past five years from 2010 to 2014. The empirical results are as follows: Management ownership gave an impact on stock returns, especially high-stakes management ownership showed significant positive effect with the stock returns. But management ownership don't have significant positive effect with ROA. The contribution of this study is as follows. Chinese companies have the efficiency of the management through the separation of ownership and management in accordance with the changes realized in capitalism. And this study is reflecting the fact of China using the Chinese data. This study has limitations of that. Management ownership measurement of governance structure don't expand the range, and measurement of governance structure is just one. The following studies are expected to be more sophisticated by comparison of countries.

• IE interfaces
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• v.17 no.4
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• pp.397-406
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• 2004

It is widely known that labor costs are continuously and rapidly growing in terms of the raw cost of products in Korea. The increased labor costs are degrading the competitiveness of dairy industry sector as in the other major industrial fields. Furthermore, the number of dairy farms is constantly decreasing while that of dairy cattle is increasing. Thus, mechanized and/or automated stockbreeding management systems are crucially required to support professional stockbreeding management, as well as to enhance the productivity of the sector. Hence this paper develops an IIS (Integrated Information System) for dairy cattle stockbreeding management. IIS is composed of five application modules and associated utility programs. The five modules are individual stock management, milking management, feeding management, propagation management, and disease management. The utility programs are involved in stock farm accounting, and handy unloading of individual stock data into a personal data acquisition device. Compared with existing foreign products, the developed system takes advantages of various stock body measurement data such as body weight, body temperature, milk conductivity, milking amount, and the number of walking steps. All the measured data are transmitted into a programmable logic controller that monitors and controls measurement devices. The transmitted data are finally aggregated into an integrated database located in the main personal computer. The integrated data are analyzed and reformed in the five modules of IIS, then, used for providing farmers with various farm states and information through application module scenes. Hence, IIS keeps the each module work in a systematic and compatible manner, while supervising the whole stockbreeding management system.

• 한국디지털정책학회:학술대회논문집
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• 2005.06a
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• pp.325-347
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• 2005

Development of efficient integration management system needs to operate and manage internet shopping mall for customer, sale, product, stock, account management. The purpose of this paper implements of small shopping mall logistics management system as a plan to raise efficiency of management of the Internet shopping mall which was a representative business form of electronic commerce. Logistics management system operates an Internet shopping mall, progressed with the aim of construction of the management system that systematizes a member, a product, a stock, customer management, and can efficiently manage a total stock grasp and the amount of transaction of a product based on Web environment by real time.

• 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 Transactions of the Korean Institute of Electrical Engineers P
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• v.64 no.4
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• pp.220-230
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• 2015

Rolling stock RAMS is a field of engineering which integrates reliability, availability, maintainability and safety (RAMS) characteristics into an inherent product design property through rolling stock system engineering process. It is implemented to achieve operational objectives successfully, and recently the RAMS has become a rapidly growing engineering discipline because it has a great potential to ensure safety and improve cost effectiveness. However, the Korean rolling stock industry has not yet implemented RAMS management in the rolling stock engineering process, despite the issue having been addressed since the introduction of the KTX. Thus, this paper discusses the processes, methods and techniques for RAMS assessment in three parts. Firstly, it outlines a process of the overall RAMS performance assessment for achieving technical RAMS design criteria. Secondly, it discusses a process for assessing the operational RAM and allocating the RAM. This paper also proposes a model for assessing safety-based risk management, which includes five analytic techniques for identifying the causes and consequences of a system failure. Finally, a case example is provided for the risk assessment of the pneumatic braking device.

• Journal of Digital Convergence
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• v.11 no.5
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• pp.145-158
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• 2013

I estimate stock prices of listed companies using financial information and Ohlson model, which is used for the evaluation of company value. Furthermore, I use the artificial neural network, one of artificial intelligence systems, which are not based on linear relationship between variables, to estimate stock prices of listed companies. By reapplying this in estimating stock prices of newly listed companies, I evaluate the appropriateness in stock valuation with such methods. The result of practical analysis of this study is as follows. On the top of that, the multiplier for the actual stock price is accounted by generating the estimated stock prices based on the artificial neural network model. As a result of the comparison of two multipliers, the estimated stock prices by the artificial neural network model does not show statistically difference with the actual stock prices. Given that, the estimated stock price with artificial neural network is close to the actual stock prices rather than the estimated stock prices with Ohlson model.

• Korean Management Science Review
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• v.30 no.1
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• pp.73-89
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• 2013

This paper develops an investment algorithm based on Markowitz's Portfolio Selection Theory, using historical stock return data, and empirically evaluates the performance of the proposed algorithm in the U.S. and the Hong Kong stock markets. The proposed investment algorithm is empirically tested with the 30 constituents of Dow Jones Industrial Average in the U.S. stock market, and the 30 constituents of Hang Seng Index in the Hong Kong stock market. During the 6-year investment period, starting on the first trading day of 2006 and ending on the last trading day of 2011, growth rates of 12.63% and 23.25% were observed for Dow Jones Industrial Average and Hang Seng Index, respectively, while the proposed investment algorithm achieved substantially higher cumulative returns of 35.7% in the U.S. stock market, and 150.62% in the Hong Kong stock market. When compared in terms of Sharpe ratio, Dow Jones Industrial Average and Hang Seng Index achieved 0.075 and 0.155 each, while the proposed investment algorithm showed superior performance, achieving 0.363 and 1.074 in the U.S. and Hong Kong stock markets, respectively. Further, performance in the U.S. stock market is shown to be less sensitive to an investor's risk preference, while aggressive performance goals are shown to achieve relatively higher performance in the Hong Kong stock market. In conclusion, this paper empirically demonstrates that an investment based on a mathematical model using objective historical stock return data for constructing optimal portfolios achieves outstanding performance, in terms of both cumulative returns and Sharpe ratios.