• Asia-Pacific Journal of Business
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• v.11 no.4
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• pp.37-48
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• 2020

Purpose - This study empirically investigates whether the risk property included in fat-tails of return distributions is systematic or unsystematic based on the devised statistical methods. Design/methodology/approach - This study devised empirical designs based on two traditional methods: principal component analysis (PCA) and the testing method of portfolio diversification effect. The fatness of the tails in return distributions is quantitatively measured by statistical probability. Findings - According to the results, the risk property in the fat-tails of return distributions has the economic meanings of eigenvalues having a value greater than 1 through PCA, and also systematic risk that cannot be removed through portfolio diversification. In other words, the fat-tails of return distributions have the properties of the common factors, which may explain the changes of stock returns. Meanwhile, the fatness of the tails in the portfolio return distributions shows the asymmetric relationship of common factors on the tails of return distributions. The negative tail in the portfolio return distribution has a much closer relation with the property of common factors, compared to the positive tail. Research implications or Originality - This empirical evidence may complement the existing studies related to tail risk which is utilized in pricing models as a common factor.

• Journal of the Korean Data and Information Science Society
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• v.23 no.2
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• pp.235-245
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• 2012

Logistic discrimination is an useful statistical technique for quantitative analysis of financial service industry. Especially it is not only easy to be implemented, but also has good classification rate. Generalized additive model is useful for credit scoring since it has the same advantages of logistic discrimination as well as accounting ability for the nonlinear effects of the explanatory variables. It may, however, need too many additive terms in the model when the number of explanatory variables is very large and there may exist dependencies among the variables. Mixtures of factor analyzers can be used for dimension reduction of high-dimensional feature. This study proposes to use the low-dimensional factor scores of mixtures of factor analyzers as the new features in the generalized additive model. Its application is demonstrated in the classification of some real credit scoring data. The comparison of correct classification rates of competing techniques shows the superiority of the generalized additive model using factor scores.

• The Korean Journal of Applied Statistics
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• v.37 no.2
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• pp.255-263
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• 2024

GDP represents the total market value of goods and services produced by all economic entities, including households, businesses, and governments in a country, during a specific time period. It is a representative economic indicator that helps identify the size of a country's economy and influences government policies, so various studies are being conducted on it. This paper presents a GDP growth rate forecasting model based on a dynamic factor model using key macroeconomic indicators of G20 countries. The extracted factors are combined with various regression analysis methodologies to compare results. Additionally, traditional time series forecasting methods such as the ARIMA model and forecasting using common components are also evaluated. Considering the significant volatility of indicators following the COVID-19 pandemic, the forecast period is divided into pre-COVID and post-COVID periods. The findings reveal that the dynamic factor model, incorporating ridge regression and lasso regression, demonstrates the best performance both before and after COVID.

• Clinical and Experimental Pediatrics
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• v.49 no.8
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• pp.821-829
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• 2006

Hemophilia is the most common coagulation disorder. It has a long history. Hemophilia A is caused by FVIII gene mutation, and hemophilia B by FIX gene mutation. Those genes are located on X chromosome long arm. Bleedings in hemophiliacs predominantly occur in joints and muscles. Because those site are insufficient in tissue factor to induce hemostasis. Among joints knee, ankle and elbow are most frequently affected because their synovial structure is vulnerable to injury compared to other joints. Hemophilia is diagnosed with factor assay. Severe hemophilia is below 1% of FVIII : C, moderate between 1% and 5%, mild over 5%. Carrier detection and prenatal diagnosis have been conducted with RFLP-based linkage analysis and DNA sequencing. Mainstay of treatment is factor replacement therapy so far. Bleedings can be controlled by infusion of factor concentrates. Hemophilc arthropathy and muscle contracture are representative sequelae. Complications of facotor replacement therapy are inhibitor development and infections. Hemophiliacs with inhibitor should be managed with large dose factor concentrate, bypassing agent, ITI and immunosuppression. Ultimately, hemophilia could be cured by gene therapy.

• Asian-Australasian Journal of Animal Sciences
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• v.21 no.3
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• pp.309-313
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• 2008

The insulin-like growth factor binding protein 3 (IGFBP3) has been investigated as a candidate gene for growth promoting effects in beef cattle and a modulator of IGF bioactivity. Previously, we have reported twenty two sequence variants discovered in Korean native cattle (Hanwoo). In this study, we examined the association between gene-specific polymorphisms of IGFBP3 and cold carcass weight (CW) and marbling score (MS) among Korean native cattle. Among twenty two polymorphisms, four common polymorphic sites (-854G>C, -100G>A, +421G>T and +3863C>A) were genotyped in our beef cattle (n = 437). Statistical analysis revealed that one common polymorphism in the promoter region (-854G>C) showed putative associations with MS (p = 0.03). IGFBP3 variation/haplotype information analyzed in this study will provide valuable information into strategies for the production of a commercial line of beef cattle.

• Fashion & Textile Research Journal
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• v.6 no.1
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• pp.102-108
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• 2004

The anthropometric measurement and the photometric measurement for have been conducted 358 children from 4 years old to 6 years old to design children's clothing. The characteristics of body type were grasped among total 44 measurement items according to the aging, being extracted seven factors from factor analysis. From cluster analysis among the seven factors the three body types were classified. Type 1 shows low fat body with a small figure and short upper body. The body has a round belly and waist. Type 2 shows the fattest body with an average height. The body has been backed with lower shoulders. Type 3 shows common fat body with a high height and a big figure. The body shows crooked round back with a big upper body and rising shoulders.

• Journal of Navigation and Port Research
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• v.39 no.6
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• pp.553-559
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• 2015

The Korean Ship Supply market scale estimated at 5.7 trillion won in 2014. Much activated and related 400 of companies located in Busan, Ulsan near Busan area. But there have many companies had lower average revenue like a 2 billion won, Also the economic slump of world maritime port industry and low priced ship supply manufacture like as China and Other developing countries, those things made a gloomy situation in domestic industry. Therefore, in this study focused on Ship Supply Common Logistics for activation plan of Ship Supply Industry. And also determine which factor is most important to Ship Supply Common Logistics and analyzed AHP and IP analysis on 16 factors based on literature review. The result, most important factor was cost for Ship Supply Common Logistics.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.6
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• pp.1837-1844
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• 2014

The study of safety culture estimate has received a wide attentions in many other industries, rather in the contexture of railroad stands at an initial phase. A factor analysis and internal reliability test were conducted to check if the survey results are reliable by looking at how the factors are dimensioned and how the questionnaires are sub-grouped in accordance with such factors, and further if there are any other common attributes being extracted as a new factor. The designed 5 factors were expanded to 7 through the test, and they were renamed accordingly. The questionnaires are reorganized according to the new 7 factors. It implicates that thorough investigation of the common attributes is important in reducing the gaps between interviewers' and interviewees' understanding. Moreover, the results of internal reliability test represent the new design of questionnaire is reasonably acceptable with the high reliable values. We expect such approaches can be applied for the railway culture survey study to be more reliable and applicable.

• Journal of Environmental Health Sciences
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• v.48 no.4
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• pp.236-243
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• 2022

Background: In the case of multiple exposures to different types of heavy metals, such as the conditions faced by residents living near a smelter, it would be preferable to group hazardous substances with similar characteristics rather than individually related substances and evaluate the effects of each group on the human body. Objectives: The purpose of this study is to evaluate the utility of factor analysis in the assessment of health effects caused by exposure to two or more hazardous substances with similar characteristics, such as in the case of residents living near a smelter. Methods: Heavy metal concentration data for 572 people living in the vicinity of the Janghang smelter area were grouped based on several subfactors according to their characteristics using factor analysis. Using these factor scores as an independent variable, multiple regression analysis was performed on health effect markers. Results: Through factor analysis, three subfactors were extracted. Factor 1 contained copper and zinc in serum and revealed a common characteristic of the enzyme co-factor in the human body. Factor 2 involved urinary cadmium and arsenic, which are harmful metals related to kidney damage. Factor 3 encompassed blood mercury and lead, which are classified as related to cardiovascular disease. As a result of multiple linear regression analysis, it was found that using the factor index derived through factor analysis as an independent variable is more advantageous in assessing the relevance to health effects than when analyzing the two heavy metals by including them in a single regression model. Conclusions: The results of this study suggest that regression analysis linked with factor analysis is a good alternative in that it can simultaneously identify the effects of heavy metals with similar properties while overcoming multicollinearity that may occur in environmental epidemiologic studies on exposure to various types of heavy metals.

• Journal of Environmental Science International
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• v.17 no.3
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• pp.315-323
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• 2008

Based on the result of extraction of common factors executed in order to elucidate the visual attributes of street scenery by types through the rotation of 23 adjective variables by Varimax, the visual attributes expressed after the construction of the facilities using street scenery were anylized to be 4 factors including factor 1 through factor 4. Theexplanation of the 4 factor groups to explain the entire distribution was 65.3% and these factor groups are the psychological attributes felt when using facilities are constructed by securing the street spaces in downtowns and the factors were named as naturalness(factor 1), locality(factor 2), identity(factor 3) and clarity(factor 4) respectively. Based on the result of one-way layout distribution analysis, the preferences for street scenery by types were found out to show considerable differences at 1 % significance level. Based on the result of multiple regression analysis, all of the factors explaining preferences including factor 1 through factor 4 were significant at 1 % significance level. In case other conditions are constant, if the values of the adjective variables related to locality(factor 2) increase by 1 unit, the preferences which are the values of dependent variables will increase by 0.709. The variable with the largest relative contribution among the 4 factor groups was the locality(factor 2) factor group and on the contrary, it was found that the independent variable with least influences was the clarity(factor 4) factor group.