칼빈의 언약사상과 세례

강성대 고신대학 신학대학원 신학전공 1984 국내석사

Box-Jenkins模型과 Pandit-Wu模型의 比較硏究

강성대 啓明大學校 1986 국내석사

(The)numerical study of primitive equations on the cumulus

강성대 釜山大學校 1990 국내석사

A Numerical Study on the Mesoscale Disturbance in the Lee of an Isolated Mountain

강성대 University of Tsukuba 1997 해외박사

본 연구는 산악지역에서 중규모 요란에 의해 잘 발달하는 두 종류의 중간규모현상(Karman vortex와 Cloud streets)을 두 종류의 중규모수치모델(LCM과 RAMS)을 사용하여 연구하였다. 산악지역에서 밀도 성층화를 이루고, 유입측의 Froude number가 0.22일 때 매우 잘 발달된 Karman vortex가 LCM (Local Circulation Model)에 의해 Simulation되었다. 주요한 결과들은 다음과 같이 요약된다. 1) 지표면의 마찰이 없는 대기에서도 Karman vortex가 simulation되었다. 이것은 대기에서의 Karman vortex형성 메카니즘이 고전적인 이론으로는 설명할 수 없음을 의미한다. 2) (1)은 Schar와 Durran(1997, 이하 SD라고 칭함)의 발견과 일치한다. Karman vortex가 형성되기 위해서는 산악의 풍하측에서 풍속감쇄(deceleration)에 의한 shear instability가 매우 중요하다. 본 연구에서는 shear instability가 mountain drag에 의한 연직방향의 total momentum flux의 발산에 기인함을 보였으며, 이것은 SD에 의해 설명되지 못한 매우 중요한 결과이다. 3) 연직방향의 total momentum flux의 발산은 Lindzen(1981)의 포화중력파(saturation of gravity wave)이론에 약간의 수정을 가하여 설명될 수 있다. 본 연구의 결과에 의하면, 지표면 부근의 total momentum flux가 대기상층(약 2.5Km고도로서 내부중력파가 포화에 이르는 고도)에서의 flux보다 크게됨을 보였다. 이것은 지표면과 약 2.5Km고도 사이에 total momentum flux의 발산이 존재함을 의미한다. 이러한 발산에 의해 산악지역 풍하측에서 shear instability가 발생한다. 이 shear instability가 충분히 클 때 SD에 의해 언급된바와 같이 absolute instability에 의해 Karman vortex의 형성이 가능하게 된다. 4) 3차원 고립된 산인 경우 wave breaking은 Froude number가 0.22일 때 발생한다. 5) Karman vortex는 number가 0.22일때 형성된다. 6) Vortex의 형성은 수평방향의 확산계수로서 표현된 Reynold number에도 의존한다. 7) 산의 수평규모가 10Km 정도일때 hydrostatic과 nonhydrostatic 역학에 기초하여 계산된 momentum budget의 연직 분포는 거의 동일하였다. Cloud street를 해안부근에 위치한 산, 해수면으로부터의 강한 현열, 그리고 Froude number가 0.25인 조건하에서 RAMS(Regional Atmosphere Modeling System, Colorado State University의 중규모모델)로 simulation하였다. 해수면으로부터 약 1Km고도에 위치하며, 한쌍의 convective roll사이에서 존재하는 잘 발달된 cloud streets가 simulation되었다. 다음과 같이 5가지의 결과를 얻었다. 1) convective roll의 쌍이 형성되기 위해서는 강한 static instability와 지형에 의한 mechanical disturbance가 필요하다. 2) 해수면으로 부터의 강한 현열이 convective roll의 주요한 에너지원이며, 구름내에서의 응결에 의한 잠열은 minor였다. 3) convective roll의 쌍은 2개의 sub-roll들로 구성되어 있었다. 하나는 outer roll로서 순환의 반경은 크지만 순환의 세기가 약하고, 나머지 하나는 순환의 반경은 작지만 순환의 세기가 강하다. Outer roll은 해수면에서 outer roll에 의해 수렴된 수증기를 cloud streets가 형성될 수 있는 상층으로 전송시킨다. 4) inner roll은 cloud streets를 line 형태로 보존될 수 있게 한다. 5) Cloud street는 정수및 비정수역학에서 모두 simulation 가능하다.

구획화된 담수호에서의 용수량 산정

강성대 동국대학교 대학원 2002 국내석사

Many reservoirs have been constructed and operated for utilizing and controlling water in main rivers of Korea since 1960's. New reservoirs are planned to satisfy increasing water demands according to the National Long-Term Water Resources Development Plan. But, constructing new reservoirs may cause some problems; they include residents for destroying the ecosystem and change of living environment. This thesis attempts to estimate water supply capacity for a reservoir with zonation. Lake Sihwa was chosen for a study site. Inflow to the lake was estimated using the Monte Carlo method utilizing the climate data for the part 40 years at Inchon Meteorological Station. With the Inflow estimated, the water level was calculated for the period of future ten years under the constraint of keeping the water level above the dead level. For 95% reliability, the estimated water supply capacity was 50,500㎥/day. This means the water supply from the reservoir covers 28% of the water demand at the Southern part of the reclaimed industrial complex to be developed.

투자심리 작용 과정에서 거시위험이 횡단면 주식수익률에 미치는 영향

강성대 동국대학교 일반대학원 2022 국내박사

With conventional risk-return theory, the stocks that carry high risk should yield higher returns than those that carry relatively low risk. However, at real stock markets, it is not rare to witness anomalies, situations in which stocks with low risk perform better than stocks with relatively high risk. Studies have been widely progressed to explain anomalies by utilizing the concept of investor sentiment. In this study, we explore whether the sensitivity(risk) of individual stock returns to macroeconomic factors is associated, as firm characteristics such as firm-size are, with investor-sentiment-induced mispricing. One previous research related to this topic is Junyan Shen et al.(2017) which examined the U.S. stock markets and confirmed the different workings of investor sentiment depending on the sensitivity(risk) of portfolios to macroeconomic factors. Domestically, Kang and Yoon(2020) examined the KOSPI market using Junyan Shen et al.(2017)’s methodology. However, contrary to the U.S. stock market, Kang and Yoon(2020) could not find any evidence of a correlation between the investor sentiment and the risks of individual stock prices to macroeconomic factors. In this study, I try to go a step further with Kang and Yoon(2020)’s subject of study and explore more in depth and in breadth. An empirical cross-sectional analysis using time-series data of portfolios is conducted. First, I sort individual stocks into two categories depending on the level of their sensitivity to macroeconomic variables. Next, I sub-categorize them according to their level of investor sentiment. The analysis takes into account 9 macro variables including Index of All Industry Production, and 1 additional risk factor which is an average thereof. 32 investor sentiment indices are used including the Bank of Korea’s Consumer Sentiment Index, which is the one investment sentiment index selected by Kang and Yoon(2020) to capture the effect of investor sentiment on macro risk portfolio returns. With these 32 investor sentiment indices, I investigate the following three hypotheses. First, following low-sentiment periods, portfolios with high macro risks should reap higher returns mainly due to the stronger effect of classic risk-return tradeoff and the weaker effect of investor sentiment(higher-risk, higher-return). Second, following high-sentiment periods, the return spread between high and low macro risk portfolios should be smaller than that of the low-sentiment periods mainly due to the stronger effect of investor sentiment and the weaker effect of classic risk-return tradeoff(higher-risk, lower-return). Third, high macro risk portfolios are more likely to be influenced by investor sentiment than low macro risk portfolios. I found that the results were inconsistent with all three hypotheses, and came to similar results even after using the risk portfolio returns adjusted by the Fama-French three-factor model(1993, FF model). However in the course of testing Hypotheses Three, I acquired evidence of investor sentiment in high and low risk portfolio returns captured by one of the 32 indices, the Composite Investor Sentiment Index(CISI), which is measured by combining future-option indicator and deposit indicator using principal component analysis. Especially, adjusted by the FF model, the evidence was more clear. But even the CISI couldn‘t capture how the investor sentiment varies depending on the different levels of portfolios’ macroeconomic risk factors. Alternatively, to clarify the relation between investor sentiment and macroeconomic risk factors more directly and numerically, I conduct an analysis using predictive regressions which shows whether the level of the CISI predicts risk portfolio returns in ways consistent with three hypotheses. Results show that for most of the coefficients of the CISI, the independent variable is negative as I conjectured on the basis of the three hypotheses, and statistically significant - although all 10 spreads between returns on high- and low-risk portfolios, which conjecturally imply that the level of investor sentiment varies according to different levels of risk are not statistically significant. In the predictive regression analysis, the evidence of investor sentiment is more vivid after adjusting for portfolios’ returns by the FF model. In robustness tests, I investigated whether these results were improved by the reorganization of portfolios by their re-estimated stocks’ betas for macroeconomic factors, or dividing total sample period to two periods of ante and post Global Financial Crisis(2007∼2008), the results were not changed. I also tried to verify the efficacy of the one-month lag period of the CISI, which is to account for the adjusting period of mispricing caused by investor sentiment. Upon substituting the one-month lag period with two- or three-month, it was confirmed that the one-month lag period is most effective. Lastly I used the market-value-weighted average return as those of risk portfolios instead of equally weighted average return, I could not get the improved result. In sum, only one investor sentiment index - the CISI - among the 32 captured the effects of high or low investor sentiment in macroeconomic risk portfolios, but it failed to capture the varied levels of investor sentiment impact depending on the risk levels of risk portfolios. This study distinguishes itself from previous studies in view of its following findings and implications. First, it broadened the area in which investor sentiment is applied to macro risk factors, whereas previous studies focused on micro risks such as firm characteristics, individual investment behavior and so on. Second, It is found that high and low investor sentiment, in response to macroeconomic risk factors, in turn affects stocks’ returns. Third, to ensure the stationarity of the regression coefficients, rolling regression was actively used in the course of removing business cycle variations from each of the indicators used as individual investor sentiment index or market proxies for various composite sentiment indices. Fourth, the results of this study suggest that the effect of the FF model may not run in the same direction as investor sentiment. In contrast with many previous literatures in which the effect of investor sentiment on returns showed little change or became weaker after the FF model adjusting, in this study the effect of investor sentiment becomes more apparent after adjusting. The results of this study found the workings of investor sentiment. However, a key question remains unanswered, and without answering the question, the results of this study can’t be of much interest to investors - especially institutional investors. The new information analysis frame that market participants expect at this kind of research is the measurability of the impact of investor sentiment and the predictability of the varied levels of impact of the cross-sectional stocks returns corresponding to the varied levels of macro risks. In this context, it might be useful to verify whether the difficulties in finding the varied impact of investor sentiment is due to the complicated relationship among macroeconomic risk factors, market proxy indicators and stock returns, or due to possibility that investor sentiment, unlike firm characteristics, has little to do with fundamental factors such as macro risks in determining financial prices and returns.

Nature and control of apple scaldduring cold storage : 저온 저장시 발생하는 사과 scald의 특성과 방제에 관한 연구

강성대 서울대학교 대학원 1988 국내박사