• The Korean Journal of Applied Statistics
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• v.28 no.3
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• pp.393-406
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• 2015

We examine how to model mortality risk using the adaptation of the mean-reverting processes for the two factor model proposed by Cairns et al. (2006b). Mortality improvements have been recently observed in some countries such as United Kingdom; therefore, we assume long-run mortality converges towards a trend at some unknown time and the mean-reverting processes could therefore be an appropriate stochastic model. We estimate the parameters of the two-factor model incorporated with mean-reverting processes by a Metropolis-Hastings algorithm to fit United Kingdom mortality data from 1991 to 2015. We forecast the evolution of the mortality from 2014 to 2040 based on the estimation results in order to evaluate the issue price of a longevity bond of 25 years maturity. As an application, we propose a method to quantify the speed of mortality improvement by the average mean reverting times of the processes.

• Proceedings of the Korean Association for Survey Research Conference
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• 2006.12a
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• pp.239-262
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• 2006

이 연구는 Hewitt과 Flett(1991c), 이기종(2006)이 제안한 완벽주의 척도 연구모형의 타당도를 확인적 요인분석을 통해 검증하고, Hewitt과 Flett(1991c)이 개발한 완벽주의 척도의 문항이 몇 개의 요인으로 구성되는지 알아보기 위해 탐색적 요인분석을 실시하였다. 확인적 요인분석 결과 Hewitt과 Flett(1991c), 이기종(2006)이 각각 제안한 연구모형과 수집된 자료가 잘 합치하지 않았다. 따라서 자료에 모형이 잘 맞도록 모형을 수정해야 하고, 의미 없는 자유모수가 모형에서 나타나지 않도록 모형을 다시 설정해야 함을 알 수 있다. 또한 Hewitt과 Flett(1991c)이 개발한 완벽주의 척도의 탐색적 요인분석을 통해 완벽주의 척도의 각 문항들이 완벽주의를 측정하는데 있어서 단일요인으로 제 기능을 하기 보다는 여러 문항에 걸쳐 공통요인이 존재함을 알 수 있다. 따라서 확인적 요인분석과 탐색적 요인분석을 통해 Hewitt과 Flett(1991c)이 개발한 완벽주의 척도가 측정하는 요인은 3개 요인으로 설명될 수 없다고 판단된다. 그러므로 Hewitt과 Flett(1991c)이 개발한 완벽주의 척도의 측정 문항이 수정되어야 하고, 나가서 우리의 사회 문화적 실정을 고려한 완벽주의 척도의 개발이 시급함을 알 수 있다.

• The Korean Journal of Financial Management
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• v.14 no.2
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• pp.21-55
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• 1997

본 연구는 기업규모, 장부가치/시장가치 비율, 순이익/주가 비율, 현금흐름/주가 비율, 레버리지 등 기본적 변수를 사용하여 주식수익률에 유의적인 변수를 확인하고, 또한 Fama and French(1993) 등에 의해서 제시된 다요인모형(multi-factor model)이 한국주식시장에서 적용가능한 지를 살펴보았다. 이를 위하여 본 연구에서는 Fama and MacBeth(1973)의 횡단면회귀모형과 Black, Jensen, and Scholes (1972)의 시계열모형을 사용하였으며, 실증분석결과를 요약하면 다음과 같다. 먼저 횡단면분석결과에 의하면, 장부가치/시장가치 비율(BE/ME), 현금흐름/주가 비율(C/P) 등이 주식수익률의 횡단면적 차이를 설명할 수 있는 유의적인 변수로 나타났다. 그리고 통계적 의미에서는 1월효과가 존재한다고 보기 어려우나, 경제적 의미에서 1월효과가 존재하는 것으로 생각된다. 시계열분석결과에 의하면, 시장요인, 기업규모요인, 장부가치/시장가치요인(또는 현금흐름/주가요인) 등의 3요인에 의해서 국내 주식수익률의 공통적 변동을 잘 설명할 수 있다. 즉 국내 증권시장에서도 Fama and French(1993)의 3요인모형이 성립될 수 있는 것으로 판단된다.

• The Journal of Society for e-Business Studies
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• v.15 no.2
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• pp.55-75
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• 2010

The primary purposes of this study are to find a proper model for government's selections of Mainbiz and present what are the better weights of the current indexes. We prepared three sets of models：first one using original 10 variables; second one using 9principally composed variables; third one using 7 principally composed variables. Among 3 models, the last one had higher explanation power than the other two models. Therefore, if index weights are adjusted according to the third newly developed model, the credibility in evaluating and selecting Mainbiz will be improved. When transforming the index weights and running the analysis, 5 variables(organization process, marketing management, management process, production-facility states, the level of forecasting) have more direct influences than other 4 variables(innovation strategies, knowledge management, achieving level, operational level) on selecting Main-biz.

• Journal of Korea Game Society
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• v.13 no.3
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• pp.69-76
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• 2013

The financial value of early stage start-up has a tendency to depend more on the non-financial factors, but these are not efficiently reflected in the traditional valuation models. Therefore, most of valuation practices for early stage start-ups heavily relied on the guts of experts. To remedy this, this study suggests a model to directly reflect the non-financial factors especially for the real options approach. Actual process of valuation and the adjustment way were developed considering the characteristics of early stage start-ups in the game industry.

• The Journal of the Korea Contents Association
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• v.18 no.10
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• pp.490-497
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• 2018

In this study, we examined whether common idiosyncratic volatility(CIV), a risk factor for idiosyncratic volatility, can be evaluated as a pricing factor. The sample is listed on the Korea Exchange. The analysis period is 288 months from July 1992 to June 2016. The main results of this study are as follows. First, in the empirical verification of the market excess returns of the testing portfolios, the difference in the return on the CIV factor sensitivity difference was statistically significant. In other words, we confirmed that there is a risk premium for CIV factors. Second, CAPM, FF3 factor model, and FF5 factor model do not explain the risk premium for CIV factors, whereas factor models that add CIV factors explain the risk premium for CIV factors. In other words, the CIV factor can be evaluated in terms of pricing factors.

• Environmental and Resource Economics Review
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• v.27 no.3
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• pp.545-567
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• 2018

This study applied and compared Poisson model, negative binomial model, zero inflated Poisson model, and zero inflated negative binomial model to estimate determinants of employed labour quantity. To estimate each of models, this study used fisheries census data which were obtained at microdata integrated service running by Statistics Korea. The study selected zero inflated negative binomial model according to the Vuong test and Likelihood-ratio test. In addition, the study estimated fishing village's practical changes on employed labour quantity as analyzing changes from 2010 to 2015. The results showed that the household with fishing vessels and high selling price had a significant effect on decrease of the labour quantities. Meanwhile, the longer work experience of the household, the more significant the increase in the labour quantities. In conclusion, this study presented that capitalized fishing household and the acceleration of aging had a significant impact on the change in the labour quantities.

• The Korean Journal of Applied Statistics
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• v.31 no.3
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• pp.329-342
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• 2018

Nomogram is a statistical tool that visualizes the risk factors of the disease and then helps to understand the untrained people. This study used risk factors of chronic obstructive pulmonary disease (COPD) and compared with logistic regression model and naïve Bayesian classifier model. Data were analyzed using the Korean National Health and Nutrition Examination Survey 6th (2013-2015). First, we used 6 risk factors about COPD. We constructed nomogram using logistic regression model and naïve Bayesian classifier model. We also compared the nomograms constructed using the two methods to find out which method is more appropriate. The receiver operating characteristic curve and the calibration plot were used to verify each nomograms.

• Communications of Mathematical Education
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• v.29 no.2
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• pp.255-279
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• 2015

Educating for character was emphasized in 2009 reformed Korea national mathematics curriculum. Thus, in this study we basically conducted to realize the character education. This study aimed to develop the teaching and learning materials for character education in middle school. For the purpose of this study, the following study was carried out. First, we investigated the concept of character education. Second, based on this, we extracted the three factor(altruism, rationality, course orientation) for character education in mathematics teaching and learning. Third, we developed five teaching and learning models for character education. The five kinds of models are 'Respect model', 'Self-directed model', 'Cooperation-centered model', 'Self-interest model, 'Story sympathy model'. Finally, We have developed a teaching and learning materials in accordance with the models. And, we applied to the classroom and confirmed its effectiveness.

• Journal of Korea Technology Innovation Society
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• v.13 no.2
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• pp.231-251
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• 2010

The numbers of SCI paper or patent in science and technology are expected to be related with the number of researcher and knowledge stock (R&D stock, paper stock, patent stock). The results of the regression model showed that severe multicollinearity existed and errors were made in the estimation and testing of regression coefficients. To solve the problem of multicollinearity and estimate the effect of the independent variable properly, principal component regression model were applied for three cases with S&T knowledge production. The estimated principal component regression function was transformed into original independent variables to interpret properly its effect. The analysis indicated that the principal component regression model was useful to estimate the effect of the highly correlate production factors and showed that the number of researcher, R&D stock, paper or patent stock had all positive effect on the production of paper or patent.