• 수산해양교육연구
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• 제28권1호
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• pp.127-136
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• 2016

The purpose of this research is to conduct a comparative study on the characteristics of daily volatility spillovers across the stock markets of Korea, China, and Japan. We employ generalized spillover definition and measurement developed by Diebold & Yilmaz (2009, 2012). The sample period is January 5, 1993 to September 25, 2015. From a static full-sample analysis, we find that 8.60% of forecast error variance comes from volatility spillovers. From a 250-day rolling-sample analysis, we discover that there exist significant volatility fluctuations in the stock markets of Korea, China and Japan, expecially during the Asian Financial Crisis (1998-1999) and the US Credit Crisis (2008-2009) after the collapse of Lehman Brothers. From the net directional spillovers across three countries, we come upon that there is neither a definite leader nor a significant follower during the sample period.

• 무역학회지
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• 제46권5호
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• pp.115-130
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• 2021

The main purpose of this study is to analyze the causal relationship between import-export goods and transportation modes. To this end, five major commodity groups were selected from 2010 to 2018 such as Machinery and transport equipment (SITC 7), manufactured goods classified chiefly by material (SITC 6), chemicals and related products, n.e.s. (SITC 5), mineral, fuels, lubricants, and related materials (SITC 3), and miscellaneous manufactured articles (SITC 8). And using the panel VECM, the difference between transportation modes such as ports and airports was compared and analyzed through panel granger causality, Impulse response function, Forecasting error variance decomposition. As a result, it is confirmed that the causal relationship between major product groups and transportation modes showed different causal relationships depending on the characteristics of port and air transportation.

• Communications for Statistical Applications and Methods
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• 제7권1호
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• pp.97-106
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• 2000

In time series analysis we generally use Box-Cox power transformation for variance stabilization. In this paper we show that order estimator and one step ahead forecast of transformed AR(1) model are approximately invariant to those of the original model under some assumptions. A small Monte-Carlo simulation is performed to support the results.

• 한국항만경제학회지
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• 제19권2호
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• pp.55-67
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• 2003

The purpose of this study is to estimate and forecast the marine trading volumes based on the structural model. We employ GPH cointegration test since the structural model must be stationary to get the accurate predicted values. The empirical results show that our model is stationary. This paper also applies variance decompositions and impulse-response functions to the structural model composed of exchange rate, domestic industrial activity, and world business. The results indicate that while both loading and unloading volumes respond positively to the shocks in income and then decay very slowly, their responses are different to the shocks in exchange tate.

• 문화기술의 융합
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• 제7권4호
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• pp.607-612
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• 2021

본 연구는 주택가격 상승 충격이 저출산에 미치는 영향과 각 변수들의 합계출산율 변동 기여도를 추정하였다. 본 연구는 기존 연구들이 시도하지 않았던 샤플리 분해와 패널 VAR의 예측오차분산분해를 통해 과거 출산율 하락 경험치에 대한 각 변수들의 기여도와 각 변수의 향후 기여도를 추정하여 차별성이 있다. 본 연구의 주요 분석결과는 다음과 같다. 우리나라 합계출산율의 하락은 최근 합계출산율 하락 흐름에 강한 영향을 받았으며, 이 영향력은 향후 미래에도 지속될 것으로 전망되었다. 주거비의 경우는 과거 주택 매매가격은 전세가격에 비해 상대적으로 합계출산율변동에 미친 기여도가 작았으나, 향후 미래에는 장기적으로 그 영향력이 커질 것으로 전망되었다. 주택 매매가격, 전세가격 이외 사교육비 역시 합계출산율 하락에 주요 원인으로 작동하였음을 실증하였고, 높은 사교육비 부담이 장기적으로도 합계출산율을 낮출 것으로 전망되었다.

• 재무관리연구
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• 제13권1호
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• pp.341-357
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• 1996

Some empirical studies have shown that asset prices respond to announcements of economic news, however, others also have found little evidence. This study assesses how market participants of the S&P 500 Index Futures reacted to the U.S. economic news announcements. For this purpose, using a GARCH (Generalized Autoregressive Conditional Heteroscedasticity) model, we use several U.S. news variables, its each surprise component and interest rates. We find that some economic news variables affected significantly on the S&P 500 Index Futures. In other words, we find that weekend variable, lagged volatility, and surprise component of trade deficit increased level of volatility. However, interest rate, M1, unemployment announcements caused the variance of the S&P 500 Index Futures to reduce, and each of the surprise component of M1 and trade deficit increased it. The result suggests that resolution of uncertainty, through economic news announcement, while, in some cases, causes market participants to reduce their forecast of volatility, a large difference between the market's forecast and the realization of the series causes the volatility to increase.

• 통상정보연구
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• 제12권1호
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• pp.99-121
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• 2010

This paper reviews the categories and properties of risk measures, analyzes the classes and structural equations of volatility forecasting models, and presents the practical methodologies and their expansion methods of estimating and forecasting the volatilities of exchange rates using Excel spreadsheet modeling. We apply the GARCH(1,1) model to the Korean won(KRW) denominated daily and monthly exchange rates of USD, JPY, EUR, GBP, CAD and CNY during the periods from January 4, 1998 to December 31, 2009, make the estimates of long-run variances in the returns of exchange rate calculated as the step-by-step change rate, and test the adequacy of estimated GARCH(1,1) model using the Box-Pierce-Ljung statistics Q and chi-square test-statistics. We demonstrate the adequacy of GARCH(1,1) model in estimating and forecasting the volatility of exchange rates in the monthly series except the semi-variance GARCH(1,1) applied to KRW/JPY100 rate. But we reject the adequacy of GARCH(1,1) model in estimating and forecasting the volatility of exchange rates in the daily series because of the very high Box-Pierce-Ljung statistics in the respective time lags resulting to the self-autocorrelation. In conclusion, the GARCH(1,1) model provides for the easy and helpful tools to forecast the exchange rate volatilities and may become the powerful methodology to overcome the application difficulties with the spreadsheet modeling.

• 한국산림과학회지
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• 제99권4호
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• pp.573-579
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• 2010

본 연구는 국립공원 탐방수요와 경제변수인 산업생산지수와 소비자물가지수 간의 관계를 분석하였다. 인과 관계검정 결과 산업생산지수와 소비자물가지수는 국립공원 탐방수요에 영향을 미치는 것으로 나타났다. 또한 충격반응분석 결과 산업생산지수와 소비자물가지수가 단기적으로 큰 반응을 보이기 시작하여 장기적으로 파급효과를 미치는 것으로 나타났다. 그리고 분산분해분석 결과 국립공원 탐방수요는 자체변수에 가장 영향을 많이 받는 것으로 나타났다. 이상의 연구 결과 경제변수는 휴양의 수요를 예측하고 정책을 수립하는데 유용하게 활용될 수 있을 것으로 판단된다.

• 산업경영시스템학회지
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• 제22권49호
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• pp.43-57
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• 1999

The recent trend is that risk management has more and more its importance. Neverthless, Korea's risk management is not developed. Even most banks does gap, duration in ALM for risk management, development and operation of VaR stressed at BIS have elementary level. In the case of Fallon and Pritsker, Marshall, gamma model is superior to delta model and Monte Carlo Simulation is improved at its result, as sample number is increased. And, nonparametric model is superior to parametric model. In the case of Korea's stock portfolio, VaR of Monte Carlo Simulation and Full Variance Covariance Model is less than that of Diagonal Model. The reason is that VaR of Full Variance Covariance Model is more precise than that of Diagonal Model. By the way, in the case of interest rate, result of monte carlo simulation is less than that of delta-gamma analysis on 95% confidence level. But, result of 99% is reversed. Therefore, result of which method is not dominated. It means two fact at forecast on volatility of stock and interest rate portfolio. First, in Delta-gamma method and Monte Carlo Simulation, assumption of distribution affects Value at Risk. Second, Value at Risk depends on test method. And, if option price is included, test results will have difference between the two. Therefore, If interest rate futures and option market is open, Korea's findings is supposed to like results of other advanced countries. And, every banks try to develop its internal model.

• East Asian Economic Review
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• 제22권3호
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• pp.371-400
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• 2018

Although asset price is an important factor in determining changes in external balances, no studies have investigated it from the Chinese perspective. In this study, I empirically examine the underlying driving forces of China's trade balances, particularly the role of asset price and the real exchange rate. To this end, I estimate a sign-restricted structural vector autoregressive model with quarterly time series data for China, using the Bayesian method. The results show that changes in asset price affect China's trade balances through private consumption and investment. Also, an appreciation of the real exchange rate tends to deteriorate trade balances in China. Furthermore, forecast error variance decomposition results indicate that changes in asset price (stock price and housing price) explain about 20% variability of trade balances, while changes in the real exchange rate can explain about 10%.