• Title/Summary/Keyword: Returns

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Efficiency Analysis of Credit Guarantee Institutions in North-eastern Asian Countries and Its Implication : Comparison Analysis of Credit Guarantee Corporations of Japan, Taiwan, and Korea (동북아시아지역 신용보증기관의 효율성 분석과 정책적 함의: 일본, 대만, 한국 신용보증기관의 비교분석)

  • Park, Chang il
    • International Area Studies Review
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    • v.22 no.2
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    • pp.61-91
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    • 2018
  • Credit Guarantee scheme is one of the most effective tools for the small business policy. The performance analysis on domestic institution level is relevant in terms of various factors of assisting tools factor. This study measured comparative global efficiency by DEA model and Super-efficiency model among 70 credit guarantee institutions in Japan, Taiwan, and Korea who are operating the schemes. At the result of the analysis, Korean credit guarantee institutions are comparatively efficient than Japanese institutions, and the DMU shows moderate in operation efficiency. The Super-efficiency ranked by Hiroshima, Taiwan SMEG, Pusan, Chiba, Shizuoka, Ulsan, and KOTEC. Most of the Credit Guarantee Institutions showed increasing returns to scale, and it indicates increasing input strategy. The statistical difference of efficiency level in Japan and Korea shows very meaning numbers. This research suggest that (1)Periodical Analysis are needed on Japanese Schemes, (2)The analysis on the impact of credit guarantee scale to the national economy and SME policy, (3) Analysis on the conclusive factors of the efficiency, (4)The policy direction has to be made by inefficient factor analysis, (5) The measurement tools of efficiency of the schemes in various aspects.

Estimation of Volatility among the Stock Markets in ASIA using MRS-GARCH model (MRS-GARCH를 이용한 아시아 주식시장 간의 변동성 추정)

  • Lee, Kyung-Hee;Kim, Kyung-Soo
    • Management & Information Systems Review
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    • v.38 no.1
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    • pp.181-199
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    • 2019
  • The purpose of this study is to examine whether or not the volatility of the 1997~1998 Asian crisis still affects the monthly stock returns of Korea, Japan, Singapore, Hong Kong and China from 1980 to 2018. This study investigated whether the volatility has already fallen to pre-crisis levels. To illustrate the possible structural changes in the unconditioned variance due to the Asian financial crisis, we use the MRS-GARCH model, which is a regime switching model. The main results of this study were as follows: First, the stock return of each country was weak in the high volatility regime except Japan resulted by the Asian financial crisis from 1997 to 1998 until March 2018, and the Asian stock market has not yet calmed down except for the global financial crisis period of 2007 and 2008. Second, the conditional volatility has been significantly and persistently decreased and eliminated after the Asian financial crisis. Thus, we could be judged that the Asian stock market was not fully recovered(stable) due to the Asian crisis including the capital liberalization high inflation, worsening current account deficit, overseas low interest rates and expansion of credit growth in 1997 and 1998, but the Asian stock market was largely settled down, except for the 2007 and 2008 in Global financial crises. Considering the similarity between the Asian stock markets and the similar correlation of the regime switching, it may be worthwhile to analyze the MRS-GARCH model.

Transaction Pattern Discrimination of Malicious Supply Chain using Tariff-Structured Big Data (관세 정형 빅데이터를 활용한 우범공급망 거래패턴 선별)

  • Kim, Seongchan;Song, Sa-Kwang;Cho, Minhee;Shin, Su-Hyun
    • The Journal of the Korea Contents Association
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    • v.21 no.2
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    • pp.121-129
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    • 2021
  • In this study, we try to minimize the tariff risk by constructing a hazardous cargo screening model by applying Association Rule Mining, one of the data mining techniques. For this, the risk level between supply chains is calculated using the Apriori Algorithm, which is an association analysis algorithm, using the big data of the import declaration form of the Korea Customs Service(KCS). We perform data preprocessing and association rule mining to generate a model to be used in screening the supply chain. In the preprocessing process, we extract the attributes required for rule generation from the import declaration data after the error removing process. Then, we generate the rules by using the extracted attributes as inputs to the Apriori algorithm. The generated association rule model is loaded in the KCS screening system. When the import declaration which should be checked is received, the screening system refers to the model and returns the confidence value based on the supply chain information on the import declaration data. The result will be used to determine whether to check the import case. The 5-fold cross-validation of 16.6% precision and 33.8% recall showed that import declaration data for 2 years and 6 months were divided into learning data and test data. This is a result that is about 3.4 times higher in precision and 1.5 times higher in recall than frequency-based methods. This confirms that the proposed method is an effective way to reduce tariff risks.

A Study on the Changes of Literary Thought in the Middle of the Yi Dynasty through Seo Kyung Duk (서경덕(徐敬德)을 통해 본 조선 중기 근기(近畿) 문학 사상의 변화)

  • Kim, Seong-ryong
    • Journal of Korean Classical Literature and Education
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    • no.39
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    • pp.181-220
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    • 2018
  • I analyze Seo Kyung Duk's (徐敬德, 1489-1546) phonetic essay and deduce whether it is related to the Tang poetry style [唐詩風], which was popular in the 16th century. Seo Kyung Duk was known as a Ki[氣]-oriented scholar and a kind of numerologist. He taught people regardless of their status differences, which gave them an open-minded attitude. Most of them were active in the areas near Seoul. Around this time, the Tang poetry style began to be popular in the Yi dynasty. Most of the leading writers of this literary trend were his students. He thought that the universe was made up of the movement of Ki[氣] and that the movement followed the correct order of numbers. Ki[氣] is active, automatic, and inevitably creates the universe in the order of numbers. The reasons for their existence are clear. All present existences, including human beings, fit together and collectively harmonize by themselves. Beyond the present discrimination, the Great Body [本體] returns to a clean and transparent unity. As such, the school presented the political stance of taking the differences of the present world into harmony and the literary position of trying to experience the clean and transparent unity of the Great Body through an aesthetic experience.

The Effects of Advertising Expense on Brand Loyalty, Profitability, and Firm Value (광고비가 마케팅 및 재무적 성과에미치는 영향: 브랜드 애호도, 수익성, 기업가치를 중심으로)

  • LEE, EUN JU;Paik, Tae-Young;Sin, Hyeon-Jun;Jeon, Kyeongmin;Cha, Gyeong-Cheon
    • (The) Korean Journal of Advertising
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    • v.27 no.4
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    • pp.71-90
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    • 2016
  • Managers of firms often wonder whether advertising expenditure is a mere expense or an investment with foreseeable future returns. When top management makes a decision on the level of advertising expense, it must consider whether an increase in advertising spending will positively affect brand loyalty and the increased brand loyalty will positively affect profitability and firm value. We investigate the industry-specific effects of advertising spending on marketing and the effect of loyalty on financial performances using top companies in Korea, specifically, 184 firms' data from year 1998 to 2014. The empirical results of a fixed effect model indicate that the effects of advertising on customer satisfaction index and loyalty on the firms' financial performance are positive. In service industry, unlike manufacturing industry, advertising has a significantly positive effect Brand Loyalty. In addition, Brand Loyalty had positive impacts on ROA and ROE as profitability index, and Tobin's q, a market-value index. The research results suggest that advertising in service industry should be considered as customer satisfaction investment and the increased Brand Loyalty as a profit for present and a business investment for the future respectively.

Seniority Based Pay System and the Relational basis of Workplace Inequality (연공성임금을 매개로 한 조직내 관계적 불평등: 내부자-외부자 격차에 대한 분석)

  • Kwon, Hyunji;Ham, Sunyu
    • Korean Journal of Labor Studies
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    • v.23 no.2
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    • pp.1-45
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    • 2017
  • This study aims at explaining organizational mechanisms of inequality that has been rising rapidly alongside the proliferation of irregular employment in the post-crisis Korean labor market. It argues that inequality is not sufficiently explained by individual gap in human capital or widespread marketization as such. Social categories into which each individual worker falls seems more important as a source of labor market inequality. Employment types that are composed of regular and irregular employment do not simply indicate the different economic meanings of employment contracts but have rather been institutionalized as a social category of status in the context of inequality over the past two decades. They are also often matched with other social categories such as gender that have created and reproduced greater labor market inequality. We pay attention to the organizational practice of dominant incumbents who make claims for advantages of return based on their exclusive accessibility to limited organizational resources and explain how that particular practice plays a role to increase relational inequality between those insiders who achieve advantageous returns and outsiders mostly irregular workers who are excluded from those resources because of the social categories that they belong to. In this study, we identify seniority based pay as the key organizational practice that justifies categorical differences within the workplace and examine how that particular practice contributes to organizational level segmentation and income ineqaulity.

The Effect of the National Pension Service' Activism on Earning Management after Adoption of the Korea Stewardship Code

  • Kwon, Ye-Kyung
    • Journal of the Korea Society of Computer and Information
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    • v.27 no.1
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    • pp.183-191
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    • 2022
  • The Korea Stewardship Code 'Principles on the Fiduciary Responsibilities of Institutional Investors' was introduced in 2016 and the National Pension Service adopted it in 2018. the National Pension Service casted 'dessent' vote on the agenda which is able to reduce the ownership interest of shareholder in general meeting. This paper examines whether 'dissent' voting affected on the ownership interest of shareholder or not. The 'dissent' vote on the agenda are related to revision artical of corperation, appointment or compensation of director and auditor, approval of financial statements ect. The proxies of earnings management is discretionary accruals calculated by modified Jones model. The control variablies are size of assets, liabilities per assets, returns on assets. The results of this study are as followings. First, the 'dissent' voting on the agenda are related to revision artical of corperation, M&A, approval of financial statements ect. are not significant because their sample size is too small, Second, the 'dissent' voting on appointment of director and auditor affected on reduction of discretionary accruals. So the National Pension Service activism shall affect on increasing the ownership interest of shareholder. Third, the 'dissent' voting on compensation of director and auditor is not affected on reduction of discretionary accruals. This results show that 'unconditional dissent voting' on the agenda in general meeting is not to reduce the ownership interest of shareholder.

Linear programming models using a Dantzig type risk for portfolio optimization (Dantzig 위험을 사용한 포트폴리오 최적화 선형계획법 모형)

  • Ahn, Dayoung;Park, Seyoung
    • The Korean Journal of Applied Statistics
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    • v.35 no.2
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    • pp.229-250
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    • 2022
  • Since the publication of Markowitz's (1952) mean-variance portfolio model, research on portfolio optimization has been conducted in many fields. The existing mean-variance portfolio model forms a nonlinear convex problem. Applying Dantzig's linear programming method, it was converted to a linear form, which can effectively reduce the algorithm computation time. In this paper, we proposed a Dantzig perturbation portfolio model that can reduce management costs and transaction costs by constructing a portfolio with stable and small (sparse) assets. The average return and risk were adjusted according to the purpose by applying a perturbation method in which a certain part is invested in the existing benchmark and the rest is invested in the assets proposed as a portfolio optimization model. For a covariance estimation, we proposed a Gaussian kernel weight covariance that considers time-dependent weights by reflecting time-series data characteristics. The performance of the proposed model was evaluated by comparing it with the benchmark portfolio with 5 real data sets. Empirical results show that the proposed portfolios provide higher expected returns or lower risks than the benchmark. Further, sparse and stable asset selection was obtained in the proposed portfolios.

Analysis of Research Trends in Tax Compliance using Topic Modeling (토픽모델링을 활용한 조세순응 연구 동향 분석)

  • Kang, Min-Jo;Baek, Pyoung-Gu
    • The Journal of the Korea Contents Association
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    • v.22 no.1
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    • pp.99-115
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    • 2022
  • In this study, domestic academic journal papers on tax compliance, tax consciousness, and faithful tax payment (hereinafter referred to as "tax compliance") were comprehensively analyzed from an interdisciplinary perspective as a representative research topic in the field of tax science. To achieve the research purpose, topic modeling technique was applied as part of text mining. In the flow of data collection-keyword preprocessing-topic model analysis, potential research topics were presented from tax compliance related keywords registered by the researcher in a total of 347 papers. The results of this study can be summarized as follows. First, in the keyword analysis, keywords such as tax investigation, tax avoidance, and honest tax reporting system were included in the top 5 keywords based on simple term-frequency, and in the TF-IDF value considering the relative importance of keywords, they were also included in the top 5 keywords. On the other hand, the keyword, tax evasion, was included in the top keyword based on the TF-IDF value, whereas it was not highlighted in the simple term-frequency. Second, eight potential research topics were derived through topic modeling. The topics covered are (1) tax fairness and suppression of tax offenses, (2) the ideology of the tax law and the validity of tax policies, (3) the principle of substance over form and guarantee of tax receivables (4) tax compliance costs and tax administration services, (5) the tax returns self- assessment system and tax experts, (6) tax climate and strategic tax behavior, (7) multifaceted tax behavior and differential compliance intentions, (8) tax information system and tax resource management. The research comprehensively looked at the various perspectives on the tax compliance from an interdisciplinary perspective, thereby comprehensively grasping past research trends on tax compliance and suggesting the direction of future research.

A Study on Stock Trading Method based on Volatility Breakout Strategy using a Deep Neural Network (심층 신경망을 이용한 변동성 돌파 전략 기반 주식 매매 방법에 관한 연구)

  • Yi, Eunu;Lee, Won-Boo
    • The Journal of the Korea Contents Association
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    • v.22 no.3
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    • pp.81-93
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    • 2022
  • The stock investing is one of the most popular investment techniques. However, since it is not easy to obtain a return through actual investment, various strategies have been devised and tried in the past to obtain an effective and stable return. Among them, the volatility breakout strategy identifies a strong uptrend that exceeds a certain level on a daily basis as a breakout signal, follows the uptrend, and quickly earns daily returns. It is one of the popular investment strategies that are widely used to realize profits. However, it is difficult to predict stock prices by understanding the price trend pattern of stocks. In this paper, we propose a method of buying and selling stocks by predicting the return in trading based on the volatility breakout strategy using a bi-directional long short-term memory deep neural network that can realize a return in a short period of time. As a result of the experiment assuming actual trading on the test data with the learned model, it can be seen that the results outperform both the return and stability compared to the existing closing price prediction model using the long-short-term memory deep neural network model.