• Communications for Statistical Applications and Methods
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• v.15 no.6
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• pp.925-937
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• 2008

In this study, we considered the clustering analysis for stock return traded in the stock market. Most of financial time-series data, for instance, stock price and exchange rate have conditional heterogeneous variability depending on time, and, hence, are not properly applied to the autoregressive moving-average(ARMA) model with assumption of constant variance. Moreover, the variability is font and center for stock investors as well as academic researchers. So, this paper focuses on the generalized autoregressive conditional heteroscedastic(GARCH) model which is known as a solution for capturing the conditional variance(or volatility). We define the metrics for similarity of unconditional volatility and for homogeneity of model structure, and, then, evaluate the performances of the metrics. In real application, we do clustering analysis in terms of volatility and structure with stock return of the 11 Korean companies measured for the latest three years.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.5
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• pp.55-66
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• 2023

This study analyzes the characteristics of customer's preferences on banking channels (branches, automated machines, telebanking, internet banking, and mobile banking) and examines the factors influencing channel usage. To accomplish this, ANOVA and multiple regression analysis are performed using customer data from Bank A. The analysis reveals that customers primarily utilizing branch counter transactions have a significant impact on the profitability of 1st and 2nd grade banks, particularly among the age group of 50 years and above. Additionally, it is observed that as customers' loan, deposit, and financial product holdings increase, branch counter transactions also increase. On the other hand, it is found that as the usage of mobile banking decreases in terms of loans and deposits, transaction volume increases.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.241-265
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• 2023

A corporate insolvency prediction model serves as a vital tool for objectively monitoring the financial condition of companies. It enables timely warnings, facilitates responsive actions, and supports the formulation of effective management strategies to mitigate bankruptcy risks and enhance performance. Investors and financial institutions utilize default prediction models to minimize financial losses. As the interest in utilizing artificial intelligence (AI) technology for corporate insolvency prediction grows, extensive research has been conducted in this domain. However, there is an increasing demand for explainable AI models in corporate insolvency prediction, emphasizing interpretability and reliability. The SHAP (SHapley Additive exPlanations) technique has gained significant popularity and has demonstrated strong performance in various applications. Nonetheless, it has limitations such as computational cost, processing time, and scalability concerns based on the number of variables. This study introduces a novel approach to variable selection that reduces the number of variables by averaging SHAP values from bootstrapped data subsets instead of using the entire dataset. This technique aims to improve computational efficiency while maintaining excellent predictive performance. To obtain classification results, we aim to train random forest, XGBoost, and C5.0 models using carefully selected variables with high interpretability. The classification accuracy of the ensemble model, generated through soft voting as the goal of high-performance model design, is compared with the individual models. The study leverages data from 1,698 Korean light industrial companies and employs bootstrapping to create distinct data groups. Logistic Regression is employed to calculate SHAP values for each data group, and their averages are computed to derive the final SHAP values. The proposed model enhances interpretability and aims to achieve superior predictive performance.

• Asia Marketing Journal
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• v.10 no.3
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• pp.103-125
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• 2008

After having changed its corporate brand from LG Fire & Marine Insurance to LIG Non-life Insurance in 2006, LIG Insurance has successfully built the corporate image as the leading insurance financial group by engaging in extensive corporate social responsibility activities. LIG, as 'a partner for sharing precious moments of life', intended to provide customers a new value of an insurance by building up the new corporate brand. It established three values to be shared internally. First was to instill a brand value orientation within the organization. Second, the firm identified the brand's value to be delivered to the customers. Third, they defined the image objective to be communicated to them. Based on these set of objectives, the company designed and implemented an integrated marketing communication(IMC) strategy over several years. The result was a successful transition to the new corporate brand name.

• The Korean Journal of Financial Studies
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• v.9 no.1
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• pp.245-268
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• 2003

전통적인 방법에 의한 PER는 단순히 그 지표의 일반적인 높고 낮음에 따라 소위 '저평가 종목'이라는 이름으로 투자자들에게 추천되고 있다. 그러나 이런 방법은 개별기업의 구체적 내용을 정확하고 종합적으로 고려하지 못하고 있다. 본 연구는 전통적인 방법으로 사용되는 PER지표의 문제점을 개선코자 배당평가 모형으로부터 도출한 PER지표의 구성요소들을 독립변수로 활용 회귀분석을 했다. 그리고 이를 근거로 이론 지표를 만든 후, 그 이론 지표를 투자의사결정에 적용하였을 때의 유효성을 검증했다. PER지표를 구성하는 독립변수는 Kisor & Whitbeck(1963), Malkiel & Cragg(1970), A. Damodaran(1996)에 의해 연구된 것을 원용, PER지표의 구성요소들로 기업의 배당성향, 이익 성장을, 그리고 위험변수로서의 베타계수를 선정했다. 투자성과는 포트폴리오 투자가 일반적인 현실을 감안해 가치가중수익률을 사용한 포트폴리오의 투자성과를 측정했고, 표본은 국내 거래소 시장에 1991년부터 2001년까지 계속 상장된 금융업종을 제외한 전종목을 대상으로 했다. 실증분석에 사용된 기간은 1997년부터 2001년까지 5년 동안의 자료이며, 투자성과를 검증하기 위한 검증모형으로 위험 프리미엄 모형을 사용했다. 먼저 동 분석기간 중 전통적인 방법에 의한 PER효과는 나타나지 않았고, 아울러 기업규모 효과도 찾을 수 없었다. 그러나 회귀분석을 통해 구해진 이론 지표를 활용할 경우, 이론 지표에 비해 시장 지표가 과소 평가된 그룹이 과대 평가된 그룹과 비교할 때 투자성과가 더 우수한 것으로 나타났다. 또한 이론 지표를 통해 PER수준이 낮아짐에 따라 투자성과가 더 높아지는 PER효과도 발견됐다. 이와 같이 이론 지표에 의해 나타나는 PER효과는 기업규모 효과와는 독립적인 것으로 보인다. 외환위기 이후 우리시장에 나타난 차별화 장세 속에 아직도 PER효과나 기업규모 효과와 같은 시장이례 현상이 존재하는지는 관심의 대상이 됐다고 본다. 본 연구에 의하면 기업규모 효과와는 별개의 PER효과가 여전히 존재하며, 다만 이 PER 효과는 전통적 의미의 일반적으로 낮은 PER종목이 초과수익률을 내는 것이 아니라, 기업규모가 크더라도 그 기업의 개별특성을 고려했을 때 이와 비교해 상대적으로 PER가 낮은 종목에 투자하면 초과수익을 낼 수 있음을 의미한다.

• International Area Studies Review
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• v.12 no.3
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• pp.69-88
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• 2008

Firms or internal exchanges exist to eliminate or at least reduce transaction costs from the separating process in many firms by dealing more efficiently with bounded rationality, complexity, and tendency towards opportunism faced by the markets so that vertical integration is supposed to have a positive relationship with performance. The organizational structure of Korean economy in the latter part of the $20^{th}$ century is much related with this transaction costs' view. I propose to estimate the effect of vertical integration on the firm's performance using the data of the Korean listed corporations from 1991 to 1995, therefore. The estimated results show that vertical integration at firm level is negatively and significantly related with the firm's performance: the higher level of vertical integration the worse performance. However, the group level integration is not related with performance at all.

• Journal of Convergence for Information Technology
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• v.12 no.4
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• pp.205-211
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• 2022

Various radioactive materials exist around us. In recent years, as interest in health has increased along with the improvement of the quality of life, examinations using radiation are also increasing. This research defined aforementioned radiation as a living radiation and developed a measurement to measure general knowledge people have on it. Eighteen reliable items were developed; current status on general knowledge regarding the safety of living radiation was analyzed using the items. As a result, a group with radiation-related education got statistically higher score than a group without such education. Correlation analysis and regression analysis showed that higher attention on usual safety leads into the greater knowledge on safety of living radiation. Therefore, this research shed lights on the necessity of radiation safety-related education in current educational course in schools.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.5
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• pp.352-362
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• 2019

The study investigates one of the long-standing, but still controversial issues in modern finance from the international and domestic perspectives. That is, financial components and differences on corporate profitability are identified and compared under the primary hypotheses. Empirical research settings include the sample data as KOSPI-listed chaebol firms, time reference covering the post-era of the global financial turmoil and two differently defined profitability indices measured by the market- and the book-value bases. A majority of total 7 explanatory variables except firm size and leverage ratio reveal their statistically significant power to explain profitability indices for the chaebol firms in the first hypothesis. The results are generally compatible with those obtained from their counterparts of non-chaebol firms. In the second hypothesis applying multinomial logistic model, the chaebol firms are classified into three groups according to the level of profitability. It is then confirmed that variables to represent the market-valued debt ratio, business risk and growth potential are financially discriminating factors among the three groups. The study may provide a new vision to identify financial factors of corporate profitability for Korean chaebol firms after the global financial crisis, which can enhance the benefits of interested parties at the government or corporate level in a virtuous cycle.

• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.71-90
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• 2020

Recently, the global insurance industry is rapidly developing digital transformation through the use of artificial intelligence technologies such as machine learning, natural language processing, and deep learning. As a result, more and more foreign insurers have achieved the success of artificial intelligence technology-based InsurTech and platform business, and Ping An Insurance Group Ltd., China's largest private company, is leading China's global fourth industrial revolution with remarkable achievements in InsurTech and Digital Platform as a result of its constant innovation, using 'finance and technology' and 'finance and ecosystem' as keywords for companies. In response, this study analyzed the InsurTech and platform business activities of Ping An Insurance Group Ltd. through the ser-M analysis model to provide strategic implications for revitalizing AI technology-based businesses of domestic insurers. The ser-M analysis model has been studied so that the vision and leadership of the CEO, the historical environment of the enterprise, the utilization of various resources, and the unique mechanism relationships can be interpreted in an integrated manner as a frame that can be interpreted in terms of the subject, environment, resource and mechanism. As a result of the case analysis, Ping An Insurance Group Ltd. has achieved cost reduction and customer service development by digitally innovating its entire business area such as sales, underwriting, claims, and loan service by utilizing core artificial intelligence technologies such as facial, voice, and facial expression recognition. In addition, "online data in China" and "the vast offline data and insights accumulated by the company" were combined with new technologies such as artificial intelligence and big data analysis to build a digital platform that integrates financial services and digital service businesses. Ping An Insurance Group Ltd. challenged constant innovation, and as of 2019, sales reached $155 billion, ranking seventh among all companies in the Global 2000 rankings selected by Forbes Magazine. Analyzing the background of the success of Ping An Insurance Group Ltd. from the perspective of ser-M, founder Mammingz quickly captured the development of digital technology, market competition and changes in population structure in the era of the fourth industrial revolution, and established a new vision and displayed an agile leadership of digital technology-focused. Based on the strong leadership led by the founder in response to environmental changes, the company has successfully led InsurTech and Platform Business through innovation of internal resources such as investment in artificial intelligence technology, securing excellent professionals, and strengthening big data capabilities, combining external absorption capabilities, and strategic alliances among various industries. Through this success story analysis of Ping An Insurance Group Ltd., the following implications can be given to domestic insurance companies that are preparing for digital transformation. First, CEOs of domestic companies also need to recognize the paradigm shift in industry due to the change in digital technology and quickly arm themselves with digital technology-oriented leadership to spearhead the digital transformation of enterprises. Second, the Korean government should urgently overhaul related laws and systems to further promote the use of data between different industries and provide drastic support such as deregulation, tax benefits and platform provision to help the domestic insurance industry secure global competitiveness. Third, Korean companies also need to make bolder investments in the development of artificial intelligence technology so that systematic securing of internal and external data, training of technical personnel, and patent applications can be expanded, and digital platforms should be quickly established so that diverse customer experiences can be integrated through learned artificial intelligence technology. Finally, since there may be limitations to generalization through a single case of an overseas insurance company, I hope that in the future, more extensive research will be conducted on various management strategies related to artificial intelligence technology by analyzing cases of multiple industries or multiple companies or conducting empirical research.

• The Journal of the Korea Contents Association
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• v.8 no.4
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• pp.173-182
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• 2008

It is hard environment to get a profit without active invest due to the low interest. In this kind of environment, however, it is also difficult to find good company directly. So private investors is hard to succeed in comprehensive financial environment. Analyzing efficiency is necessary to enhance the competitive power of fund companies. This paper analyze the efficiency of fund company using DEA models. We evaluate the CCR and BCC efficiency and RTS(return to scale) of 33 Korean fund companies. We also suggest the fund company which can be benchmarked based on analyzed information.