• The Journal of Asian Finance, Economics and Business
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• v.8 no.7
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• pp.517-523
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• 2021

Audit quality encompasses the key elements that create an environment that maximizes the likelihood that quality audits are performed consistently. This study aimed to identify the impact of auditing quality on the market value of the manufacturing companies listed on the Amman Stock Exchange (ASE). The analytical method was adopted in this research to extract and collect the necessary data. This study hypothesizes that audit quality leads to an increase in the market value by the offering of high-quality services. The study used the panel data approach to analyze cross-sectional data for 41 industrial companies that included time series data for the period (2019-2019). To test its hypotheses, the study used the fixed-effect model. The study found that the audit quality factors (audit office size, client retention period, auditor's fees, and linking with international audit offices) did not have a significant impact on market value. It found also the positive impact of the audit office size on the market value of the listed companies on the ASE for the period from 2009 to 2019. The study recommended the management of the company realize the importance of contracting with audit offices of large size and good reputation because these offices are more capable of increasing their efficiency, qualifying their employees, and thus be fully prepared for the audit process efficiently and effectively.

• Journal of Distribution Science
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• v.11 no.9
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• pp.5-15
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• 2013

Purpose - The research aim is to shed empirical light on whether quality-focused retailer brands such as Premium brand of Tesco Korea, Prime of Lotte Mart, and Best of E-Mart in the grocery market, make a contribution to developing store loyalty in the Korean market particularly. Research design, data, methodology - After developing sixconstructs, such as higher quality, stock availability, price levels, national brands, retailer brand attitudes, and store loyalty, the authors adopted exploratory factor analysis, confirmatory factor analysis, chi-square test and structural equation modelling as a research technique. Results - It was found that higher quality strongly influences the retailer brand attitude formation, and that retailer brand customers were sensitive to price levels. Buyers are, nevertheless, relatively less aware of price levels, when purchasing quality-oriented retailer brand types. Conclusions - The research implied that quality-oriented retailer brand types make a significant contribution to retailer brands attitude formation, and further, building store loyalty.

• Journal of Industrial Convergence
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• v.2 no.2
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• pp.127-147
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• 2004

This paper examines the time-series relations among expected return, risk, and book-to-market(B/M) at the portfolio level. The time-series analysis is a natural alternative to cross-sectional regressions. An alternative feature of the time-series regressions is that they focus on changes in expected returns, not on average returns. Using the time-series analysis, we can directly test whether the three-factor model explains time-varying expected returns better than the characteristic-based model. These results should help distinguish between the risk and mispricing stories. We find that B/M is strongly associated with changes in risk, as measured by the Fama and French(1993) three-factor model. After controlling for changes in risk, B/M contains little additional information about expected returns. The evidence suggests that the three-factor model explains time-varying expected returns better than the characteristic-based model.

• Journal of the Korea Society of Computer and Information
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• v.25 no.5
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• pp.47-56
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• 2020

The stock index is used not only as an economic indicator for a country, but also as an indicator for investment judgment, which is why research into predicting the stock index is ongoing. The task of predicting the stock price index involves technical, basic, and psychological factors, and it is also necessary to consider complex factors for prediction accuracy. Therefore, it is necessary to study the model for predicting the stock price index by selecting and reflecting technical and auxiliary factors that affect the fluctuation of the stock price according to the stock price. Most of the existing studies related to this are forecasting studies that use news information or macroeconomic indicators that create market fluctuations, or reflect only a few combinations of indicators. In this paper, this we propose to present an effective combination of the news information sentiment analysis and various macroeconomic indicators in order to predict the US Dow Jones Index. After Crawling more than 93,000 business news from the New York Times for two years, the sentiment results analyzed using the latest natural language processing techniques BERT and NLTK, along with five macroeconomic indicators, gold prices, oil prices, and five foreign exchange rates affecting the US economy Combination was applied to the prediction algorithm LSTM, which is known to be the most suitable for combining numeric and text information. As a result of experimenting with various combinations, the combination of DJI, NLTK, BERT, OIL, GOLD, and EURUSD in the DJI index prediction yielded the smallest MSE value.

• IE interfaces
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• v.11 no.3
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• pp.193-207
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• 1998

The agriculture and fishery share in the Korean GDP is continuously decreasing after 1960s. Furthermore the proportion of these industries in the GDP has diminished as low as 10 percent in recent years. However, the stockbreeding sector in these industries are considerably expanded. More than 50 percent of the whole farmhouses are involved in the livestock farming, and the stock farming portion is steadily increased in its size and scope. Thus, the mechanization and the automization of stockbreeding equipments are greatly required to reduce down production cost, as well as to win the competitiveness in the global market. From this aspect, developed in this paper is a stockbreeding management system (SMS) for dairy cattle, which can be used in small and medium sized dairy farms. First, the basic schema of the stockbreeding management system are addressed in view of stockbreeding management for individual dairy cattle. Electronic identification (EI) systems and sensory devices have changed stockbreeding management strategy from group stock control into individual stock control manner. The SMS receives stock body measurement data through the sensory devices such as weight, temperature, and milk conductivity meters. A common database then integrates those measuring data together so that the SMS can determine the appropriate solution on each stock's breeding such as feeding and milking. Thus, each stock can be supervised by a sophisticated SMS that provides the best solution to the stockbreeding throughout the stock's whole life-cycle. Secondly. six major submodules of the SMS, based on the EI and sensory devices, are proposed. They are individual stock management, disease management, health management, feeding management, milking management, and a propagation management submodule. Finally, a prototype system for the SMS is demonstrated. The system is developed using Delphi 2 client-server system run under the Windows 95 environment.

• The Journal of Industrial Distribution & Business
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• v.10 no.12
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• pp.35-42
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• 2019

Purpose : This study examines The impact of human resource investment in internal control on stock price crash risk. Effective internal control ensures that information provided is complete and accurate, financial statements are reliable. By overseeing management, internal control systems can reduce agency costs between management and outside parties. In Korea, firms have to disclose information about internal control systems. The working experience of human resources in internal control systems is also provided for interested parties. If a firm hires more experienced internal control personnel, it can better facilitate the disclosure of information. Prior studies reported that information asymmetry between managers and investors increases future stock price crash risk. Therefore, the longer working experience internal control personnel have, the lower probability stock crashes have. Research design, data and methodology : This study analyzed the association between the working experience of internal control personnel and crash risk using regression analysis on KOSPI listed companies for fiscal years 2016 through 2017. The sample consists of 1,034 firm-years of non-financial firms whose fiscal year end on December 31. Career spanning data of internal control personnel was collected from internal control reports. The professionalism(IC_EXP) was measured as the logarithm of the average working experience of internal control personnel in months. Negative conditional skewness(NSKEW) and down-to-up volatility (DUVOL) are used to measure firm-specific crash risk. Both measures are based on firm-specific weekly returns derived from the expanded market model. Results : We find that work experience in internal control environment is negatively related to stock price crashes. Specifically, skewness(NSKEW) and volatility (DUVOL) are reduced when firms have longer tenure of human resources in internal control division. The results imply that firms with experienced internal control personnel are less likely to experience stock price crashes. Conclusions : Stock price crashes occur when investors realize that stock prices have been inflated due to information asymmetry. There is a learning effect when internal control processes are done repetitively. Thus, firms with more experienced internal control personnel could manage their internal control more effectively. The results of this study suggest that firms could decrease information asymmetry by investing in human resources for their internal control system.

• 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 the Korean Data and Information Science Society
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• v.22 no.1
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• pp.37-47
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• 2011

Stock price index option market has various investment strategies that have been developed. Specially, arbitrage strategies are very important to be efficient in option market. The purpose of this study is to improve profit using rough set and Box spread by using past option trading data. Option trading data was based on an actual stock exchange market tick data ranging from 2001 to 2006. Validation process was carried out by transferring the tick data into one-minute intervals. Box spread arbitrage strategies is low risk but low profit. It can be accomplished by back-testing of the existing strategy of the past data and by using rough set, which limit the time line of dealing. This study can make more stable profits with lower risk if control the strategy that can produces a higher profit module compared to that of the same level of risk.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.12
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• pp.5671-5676
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• 2011

Volatility Index is the index that represents future volatility of underlying asset implied in option price and expected value of market that measures the possibility of stock price's change expected by investors. The Korea Exchange announces a volatility Index, VKOSPI, since April, 13, 2009. This paper used daily data from January, 2002 through December, 2008 and tested power of Volatility index for future returns of portfolios sorted by size, book-to-market equity and beta. As a result, VKOSPI has the predictive power to future returns and then VKOSPI may be determinants of returns. Also if beta is included when sorting portfolio, the predictive power of VKOSPI is stronger for future portfolio returns.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.1
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• pp.123-133
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• 2021

This research aims to examine the effect of carbon emission disclosure on firm value and to reveal environmental performance and industrial type as the moderating variables. This study used 82 samples of companies listed on the Indonesia Stock Exchange (IDX) and receiving awards in the Indonesian Sustainability Reporting Award (ISRA) in 2014-2018. This study used a multiple linear regression analysis to test the hypotheses. The results showed that carbon emission disclosure had a positive and significant effect on firm value as carbon emission disclosure is a form of corporate concern on environment positively responded by the market and becomes the basis for investors to make their considerations in assessing the company sustainability. Besides, environmental performance and industrial type can strengthen the influence relationship of carbon emission disclosure on firm value since environmental performance was assessed based on ISO 14001 certification ensuring that the company has tried to preserve the environmental sustainability by creating a good environmental management system. Moreover, companies categorized into high profile industrial type have tried to change their unfavorable image and avoid lawsuits by performing carbon emission disclosure to gain positive responses from the market.