• The Journal of Asian Finance, Economics and Business
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• v.8 no.4
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• pp.1-9
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• 2021

UAE has rapidly developed into one of the leading global financial hubs, with significant transformations in its stock exchanges. In its attempt at economic diversification in the last two decades, the country has also taken a lead in the GCC region in introducing extensive reforms to attract FDI to the Emirates. However, oil price volatilities have posed a significant challenge to all oil-exporting countries. The main aim of this study is to explore the impact of economic diversification and oil price on the UAE stock market. The study applies Granger Causality and Vector Autoregressive Model on monthly Abu Dhabi stock exchange index, Dubai Fateh crude oil spot price, and FDI inflows during 2001-19. The short-term interbank rate has been included as a monetary policy variable. The results show a substantial difference between the two phases of reforms. Oil price and Abu Dhabi stock index show bidirectional relationship during 2001-09 but no causality was found during 2010-19. Furthermore, the second phase was characterized by unidirectional causation from FDI to ADX index. This study highlights FDI inflows as a key driver of stock market performance during the last decade and emphasizes the success of the intense reforms in the UAE initiated for the diversification of its economy.

• Management Science and Financial Engineering
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• v.14 no.2
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• pp.89-104
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• 2008

Growth curves including Bass, Logistic and Gompertz functions are widely used in forecasting the market demand. Nonlinear least square method is often adopted for estimating the model parameters but it is difficult to set up the starting value for each parameter. If a wrong starting point is selected, the result may lead to erroneous forecasts. This paper proposes a method of selecting starting values for model parameters in estimating some growth curves by nonlinear least square method through grid search and transformation into linear regression model. Resealing the market data using the national economic index makes it possible to figure out the range of parameters and to utilize the grid search method. Application to some real data is also included, where the performance of our method is demonstrated.

• Journal of Digital Convergence
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• v.11 no.2
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• pp.175-182
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• 2013

In this paper, the simulation model of house price is presented on the basis of pricing mechanism between the demand and the supply of apartments in seoul. The algorithm of house price simulation model for calculating the rate of price over time includes feedback control theory. The feedback control theory consists of stock variable, flow variable, auxiliary variable and constant variable. We suggest that the future price of apartment is simulated using mutual interaction variables which are demand, supply, price and parameters among them. In this paper we considers three items which include the behavior of apartment price index, the size of demand and supply, and the forecasting of the apartment price in the future economic scenarios. The proposed price simulation model could be used in public needs for developing a house price regulation policy using financial and non-financial aids. And the quantitative simulation model is to be applied in practice with more specific real data and Powersim Software modeling tool.

• The Journal of the Korea Contents Association
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• v.8 no.9
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• pp.234-241
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• 2008

The feature of the hotel business as a labor intensive industry and its heavy dependence on man power is relatively bigger than other industries. the important factors influencing the customer`s decision making are tangible facilities and intangible service qualities. however, the changes in economic situation are also seriously influencing them. So hotels are started to find other IT(information technology) systems. BSC which has been recognized as one of barometers to establish management performance is one of them. The purpose of this study was to develop KPI(key performance indicator) by using the BSC(Balanced Scorecard) for evaluating hotel management performance. This thesis presents customer performance, inner process performance, learning and growing performance as non-financial factors and tries to examine the cause and effect in the hotel industry. Hotels have to know nonfinancial performance which has positively relate to financial performance. To introduce BSC system is not to lead increasing income and bettermenting service quality, satisfacting customer needa for hotels, But to lead developing value enhancement to hotel enterprises and present process.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.157-176
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• 2018

The purpose of this research is to develop a detection model for companies designated as administrative issue in KOSDAQ market using financial data. Administration issue designates the companies with high potential for delisting, which gives them time to overcome the reasons for the delisting under certain restrictions of the Korean stock market. It acts as an alarm to inform investors and market participants of which companies are likely to be delisted and warns them to make safe investments. Despite this importance, there are relatively few studies on administration issues prediction model in comparison with the lots of studies on bankruptcy prediction model. Therefore, this study develops and verifies the detection model of the companies designated as administrative issue using financial data of KOSDAQ companies. In this study, logistic regression and decision tree are proposed as the data mining models for detecting administrative issues. According to the results of the analysis, the logistic regression model predicted the companies designated as administrative issue using three variables - ROE(Earnings before tax), Cash flows/Shareholder's equity, and Asset turnover ratio, and its overall accuracy was 86% for the validation dataset. The decision tree (Classification and Regression Trees, CART) model applied the classification rules using Cash flows/Total assets and ROA(Net income), and the overall accuracy reached 87%. Implications of the financial indictors selected in our logistic regression and decision tree models are as follows. First, ROE(Earnings before tax) in the logistic detection model shows the profit and loss of the business segment that will continue without including the revenue and expenses of the discontinued business. Therefore, the weakening of the variable means that the competitiveness of the core business is weakened. If a large part of the profits is generated from one-off profit, it is very likely that the deterioration of business management is further intensified. As the ROE of a KOSDAQ company decreases significantly, it is highly likely that the company can be delisted. Second, cash flows to shareholder's equity represents that the firm's ability to generate cash flow under the condition that the financial condition of the subsidiary company is excluded. In other words, the weakening of the management capacity of the parent company, excluding the subsidiary's competence, can be a main reason for the increase of the possibility of administrative issue designation. Third, low asset turnover ratio means that current assets and non-current assets are ineffectively used by corporation, or that asset investment by corporation is excessive. If the asset turnover ratio of a KOSDAQ-listed company decreases, it is necessary to examine in detail corporate activities from various perspectives such as weakening sales or increasing or decreasing inventories of company. Cash flow / total assets, a variable selected by the decision tree detection model, is a key indicator of the company's cash condition and its ability to generate cash from operating activities. Cash flow indicates whether a firm can perform its main activities(maintaining its operating ability, repaying debts, paying dividends and making new investments) without relying on external financial resources. Therefore, if the index of the variable is negative(-), it indicates the possibility that a company has serious problems in business activities. If the cash flow from operating activities of a specific company is smaller than the net profit, it means that the net profit has not been cashed, indicating that there is a serious problem in managing the trade receivables and inventory assets of the company. Therefore, it can be understood that as the cash flows / total assets decrease, the probability of administrative issue designation and the probability of delisting are increased. In summary, the logistic regression-based detection model in this study was found to be affected by the company's financial activities including ROE(Earnings before tax). However, decision tree-based detection model predicts the designation based on the cash flows of the company.

• Journal of information and communication convergence engineering
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• v.9 no.5
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• pp.577-582
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• 2011

EMR(Electronic Medical Record) is an emerging technology that is highly-blended between non-IT and IT area. One of methodology to link non-IT and IT area is to construct databases. Nowadays, it supports before and after-treatment for patients and should satisfy all stakeholders such as practitioners, nurses, researchers, administrators and financial department and so on. In accordance with the database maintenance, DAS (Data as Service) model is one solution for outsourcing. However, there are some scalability and strategy issues when we need to plan to use DAS model properly. We constructed three kinds of databases such as plain-text, MS built-in encryption which is in-house model and custom AES (Advanced Encryption Standard) - DAS model scaling from 5K to 2560K records. To perform custom AES-DAS better, we also devised Bucket Index using Bloom Filter. The simulation showed the response times arithmetically increased in the beginning but after a certain threshold, exponentially increased in the end. In conclusion, if the database model is close to in-house model, then vendor technology is a good way to perform and get query response times in a consistent manner. If the model is DAS model, it is easy to outsource the database, however, some technique like Bucket Index enhances its utilization. To get faster query response times, designing database such as consideration of the field type is also important. This study suggests cloud computing would be a next DAS model to satisfy the scalability and the security issues.

• ETRI Journal
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• v.25 no.4
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• pp.258-265
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• 2003

In our study, we extracted the market, finance, and government factors determining R&D investment of individual firms in the IT industry in Korea. We collected the financial data of 515 individual firms belonging to IT and non-IT industries between 1980 and 1999 from the Korea Investors Service's database and investigated the empirical relationship between the factors using an ordinary regression model, a fixed effects model, and a random effects model. The main findings of our study are as follows: i) The Herfindahl Index variable representing the degree of market concentration is statistically insignificant in explaining R&D expenditures in the IT manufacturing industry. ii) Assets, which is used as a proxy variable for firm size, have a positive and statistically significant coefficient. These two results suggest that the Schumpeterian Hypothesis may be only partially applied to the IT manufacturing industry in Korea. iii) The dividend variable has a negative value and is statistically significant, indicating that a tendency of high dividends can restrict the internal cash flow for R&D investment. iv) The sales variable representing growth potential shows a positive coefficient. v) The subsidy as a proxy variable for governmental R&D promotion policies is positively correlated with R&D expenditure. This suggests that government policy has played a significant role in promoting R&D activities of IT firms in Korea since 1980. vi) Using a dummy variable, we verified that firms reduced their R&D investments to secure sufficient liquidity under the restructuring pressure during Korea's 1998 and 1999 economic crisis.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.9
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• pp.105-115
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• 2020

The study empirically examines the effects of loan portfolio diversification on bank risk and return in the nascent banking market of Vietnam. Loan portfolio diversification is captured through the Hirschman-Herfindahl index and the Shannon Entropy with sectoral exposures. We access each bank's financial reports to collect the required data, especially the breakdown of sectoral loan portfolios, thus constituting a unique dataset. To compute bank return, we use the traditional accounting indicators, including return-on-assets, return-on-equity, and net-interest margin. For bank risk, we utilize the loan-loss provisions and non-performing loans relative to gross customer loans. Using a sample of 30 commercial banks over the period from 2008 to 2019 and the system generalized method of moments estimator for the dynamic panel, we indicate the downsides of portfolio diversification. Concretely, we observe that all diversification measures exhibit significantly negative signs in all regressions across different bank return proxies. At the same time, the estimates display the significant and positive impact of diversification on the non-performing loan ratio. Hence, sectoral loan portfolio diversification significantly hampers bank performance in both aspects of lower return and higher credit risk. The results are robust across a rich set of bank performance and portfolio diversification measures.

• Journal of Distribution Science
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• v.13 no.9
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• pp.95-101
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• 2015

Purpose - This study provides evidence of the impact of the mandatory adoption of Korean equivalents to International Financial Reporting Standards (K-IFRS) on accounting quality. K-IFRS uses fair value as a basis of measurement and is characterized by principle-based standards. These characteristics can lead to a decrease in conservatism. Therefore, this study aims to examine whether or not there is a change in the level of conservatism before and after the enforcement of K-IFRS (2007~2014). By comparing 2007 through 2008 and 2013 through 2014 (excluding 2009 to 2012), we test "the temporary adjustment phenomenon" and document an overall decline in the degree of conservatism after the adoption of K-IFRS. Research design, data, and methodology - Our sample is comprised of data of all listed Korea Composite Stock Price Index (KOSPI) manufacturing distribution companies in Korea from 2007 to 2014, which yields the pooled sample of 4,412 (panel A) and 1,915 (panel B) firm-year observations for hypotheses 1 and 2. In line with recent literature, we adopt the Givoly and Hayn (2000) model, which recomputes the non-operating accruals, excluding two components that are most likely to capture the effect of restructuring activities: special items and gains or losses from discontinued operations. In addition, we also use these variables: SIZE, LEV, INV_CYCLE, ROA, OWN, and FOR. Results - Our sample period spans 2007 to 2014. This offers evidence on the effect of the mandatory adoption of IFRS on conservatism. Our findings can be summarized as follows. First, in panel A, for mandatory K-IFRS adoption (2011), we do not find any significant evidence of conservatism. We can guess that the "temporary adjustment phenomenon" is the reason that we do not find significant evidence of conservatism. Second, we investigate panel B from 2009 to 2012. We document an overall decline in the degree of conservatism after the adoption of K-IFRS. We can assume that these results are due to "the temporary adjustment phenomenon." Conclusions - This study finds that conservatism significantly decreased after IFRS adoption. In particular, this study makes the initial effort to elucidate "the temporary adjustment phenomenon" to analyze the effect of K-IFRS on conservative accounting. We argue that K-IFRS are conceptually conservative but that inappropriate application of the conservatism principles is likely to prevent financial reporting from reaching the level of conservatism targeted by the IASB. Overall, this paper contributes to the literature on IFRS and can be useful to capital market supervisors who are monitoring the trends of the firms implementing K-IFRS. Additionally, our results inform stakeholders of the potentially negative effect of the greater flexibility permitted by IFRS and/or lack of appropriate enforcement on key dimensions of accounting quality. This has important implications for Korean regulators and standard setters as they review the cost and benefits of IFRS. Our study also sheds light on the importance of the institutional environment in achieving the targeted objectives for improving financial reporting quality.

• The Korean Journal of Archival Studies
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• no.48
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• pp.45-92
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• 2016

Corporations report their economical, environmental, social influences and achievements through sustainability reports. Apart from the financial reports, which are subject to legal restrictions, sustainability reports inform non financial achievements of a corporation, thus the reliability of the information is solely dependent on the corporation itself. The current sustainability reports are of types that cannot include proof or source of the index data, thus they are tended to be regarded as means of publicity. The reliability of the reports is often questioned. This research applied the concept of Evidence-Based Accountability, which will allow the confirmation of accountability through records including contents and context of the tasks. Evidence-Based Accountability means producing and accumulating witness records of actions, then managing the records as usable information and use them as accountability information. Index data from sustainability reports of domestic corporations and web based reports of Vodafone was reviewed. Measures to link task records as proof of index data was studied. To make this possible, record production and acquisition system was redesigned in order to secure required records as evidence. Linked build-up of SR system and RMS was proposed. The proposed system will allow collection and management of records as SR accountability information, and provide the data when necessary. Also, corporate infrastructure was proposed. This infrastructure will build a professional records management system in stages, through organizational system and regulations. Cooperation of staff in this infrastructure will support reliable corporate accountability.