• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.10
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• pp.6511-6516
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• 2015

This paper examines the relationship between idiosyncratic volatility(IVOL) puzzle and trading volumes by trader types in the Korean stock market. The data set includes all stock in both KRX and KOSDAQ for the period from January 1999 through December 2013. Idiosyncratic volatility is measured by using the Fama-French's three-factor model. Traders are classified into individual, institution, and foreign trader. We construct (5X5) portfolios based on each trader's net buying and idiosyncratic volatility. We find that there are some special portfolios that show the idiosyncratic volatility puzzle. For individual investors, top net buying portfolios show clear the idiosyncratic volatility puzzle. However, for institution and foreign investors, lowest net buying portfolio show the idiosyncratic volatility puzzle. This results imply that the idiosyncratic volatility puzzle in the Korean stock market is mainly caused by individual investors.

• Computational Structural Engineering
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• v.7 no.3
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• pp.115-122
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• 1994

Design sensitivity analysis of the second order perturbed eigenproblems for random structural system is presented. Dynamic response of random system including uncertainties for the design variable is calculated with the first order and second order perturbation method to original governing equation. In optimal design methods, there is fundamental requirement for design gradients. A method for calculating the sensitivity coefficients is developed using the direct differentiation method for the governing equation and first order and second order perturbed equation.

• Management & Information Systems Review
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• v.33 no.5
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• pp.249-260
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• 2014

This paper explores the relationship between firm-specific volatility and some firm characteristics such as size, the market-to-book ratio of equity, PER, PBR, PCR, PSR and turnover in KOSDAQ market. In addition, I investigate whether portfolios with difference to realized range-based volatility and firm-specific volatility have different investment performance using CAPM and FF-3 factor model. The main findings of this study can be summarized as follows. First, firm-specific volatility have mostly positive relationship between firm-specific volatility and some firm characteristics. Second, this study found that realized range-based volatility and firm-specific volatility are positively related to expected return. It means that portfolios with high idiosyncratic volatility have significantly higher expected return than portfolios with low firm-specific volatility.

• 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.

• Journal of the Korean Data and Information Science Society
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• v.25 no.4
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• pp.799-805
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• 2014

This paper deals with a method for getting the Type III sums of squares on the basis of projections under the assumption of two-way fixed effects model. For unbalanced data in general total sum of squares is not equal to the sum of componentwise Type III sums of squares. There are some differencies between two quantities. The suggested method using projections can detect where the differences occur and how much they are different. The traditional ANOVA method could not explain clearly the differences. It also discusses how eigenvectors and eigenvalues of the projection matrices can be used to get the Type III sums of squares.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2015.07a
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• pp.220-221
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• 2015

플로팅 건물의 변동 풍하중에 대한 시간이력응답을 통한 유효 Sampling의 영향을 분석하기 위하여 200개 풍 파랑 하중조합을 통해 시간이력 동수역학 해석을 수행하여, 유효 표본 Sampling을 선정하여 상부구조물의 고유주기를 변화하여 부분구조해석을 수행하였다. 풍하중은 평균 속력 35m/sec을 가진 von Karman의 변동풍속 파워스펙트럼으로 계산하여 입력하였고 입력 파랑은 Pierson-Moskowitz 스펙트럼으로 계산하여 파고 0.5m에 대하여 입력하였다. 각기 다른 고유주기를 가진 상부 구조물에 대하여 7개 그룹의 하중조합에 대한 유효 Sampling을 선정하여 SRSS와 평균값을 계산하였다. 해석 결과, 최소 7개 이상의 Sampling에 대한 해석이 요구되며 전반적으로 30개 Sampling을 통한 해석이 적절하다고 분석되었다.

• The Korean Journal of Financial Management
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• v.26 no.4
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• pp.191-234
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• 2009

This study examined on the volatility feedback hypothesis through the use of threshold GARCH-in-Mean (GJR-GARCH-M) model developed by Glosten, Jaganathan, and Runkle (1993) in the stock markets of 14 emerging countries during the period of January, 1996 to May, 2009. On this study, I found successful evidences which can support the volatility feedback hypothesis through the following three estimation procedures. First, I found relatively strong positive relationship between the expected market risk premiums and their conditional standard deviations from the GARCH-M model in the basis of daily return on each representative stock market index, which is appropriate to investors' risk-averse preferences. Second, I can also identify the significant asymmetric time-varying volatility originated from the investors' differentiated reactions toward the unexpected market shocks by applying the GJR-GARCH-M model and further find the lasting positive risk aversion coefficient estimators. Third, I derived the negative signs of the regression coefficient of unpredicted volatility on the stock market return by re-applying the GJR-GARCH-M model after I controlled the positive effect of predicted volatility through including the conditional standard deviations from the previous GARCH-M model estimation as an independent explanatory variable in the re-applied new GJR-GARCH-M model. With these consecutive results, the volatility feedback effect was successfully tested to be effective also in the various emerging stock markets, although the leverage hypothesis turned out to be insufficient to be applied to another source of explaining the negative relationship between the unexpected volatility and the ex-post stock market return in the emerging countries in general.

• The Korean Journal of Financial Management
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• v.13 no.1
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• pp.79-99
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• 1996

본 논문의 목적은 한국증권시장에서 주가의 상하한 제한폭이 얼마수준에서 적정한가를 실증적으로 분석하는 것이다. 이 분석을 하기 위해서 주가제한폭이 늘어남에 따라 주가변동성이 얼마나 늘어나는가에 대한 민감도 분석을 하여야 하는데 이를 위해 먼저 주가제한폭하에서의 주가변동성에 대한 공식을 도출하였다. 이 공식에 따르면 주가변동성은 주가제한폭이 존재하지 않을 경우의 고유의 주가변동성과 기대수익률과 그리고 주가제한폭의 함수이다. 이 공식을 이용하여서, 유동성을 아주 적게 저해하면서 비정상적인 주가폭락 및 주가폭등을 조기에 제어할 수 있는 가능한 한 낮은 주가제한 폭으로 15%가 적합하다는 결론을 얻었다.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.26 no.4
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• pp.244-252
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• 2014

EOF (Empirical Orthogonal Function) analysis is applied to investigate the sand movement in Hujeong Beach. For the analysis, the profile data which were observed five times from June 2009 to May 2010 along the 13 baselines were used. To secure the temporal and physical consistency among the 13 profile data, the 13 profile data were combined into one data and using this data the EOF analysis was performed. According to the analysis, the first EOF is related with the mean topography and the second EOF represents the natural variation of sediment migration and the third EOF is related with the along-shore sediment transport arising from storm. The remaining EOFs show no special relation with wave conditions. In conclusion the main factors which are having great effects on Hujeong Beach's sand movement are analyzed as natural variation and along-shore sediment transport owing the wave conditions.

• Journal of the Korean earth science society
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• v.30 no.6
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• pp.683-691
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• 2009

Geomagnetic variation around May 2, 2009 when Angdong earthquake broke out was analyzed using the data recorded at the Cheong-yang geomagnetic observatory, KMA. Firstly, we predict the geomagnetic variation by PCA analysis of geomagnetic data, and then compare the predicted value with the observed data to find any significant differences in residuals. Secondly, wavelet semblance technique is applied to compare the time series before and after the earthquake. Some meaningful change is detected in the Z-field. Thirdly, eigen value analysis for the 3 component geomagnetic data is performed. The location of the observatory was too far from the epicenter and the magnitude was too small to find decisive precursory phenomenon. Nevertheless we can detect some significant correlation between the earthquake and the variation of the geomagnetic field. Various signal processing methods applied in this study will give some opportunity to find precursory effects in the future.