• The Korean Journal of Applied Statistics
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• v.34 no.4
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• pp.611-622
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• 2021

With a wide recognition that financial time series typically exhibits asymmetry patterns in volatility so called leverage effects, various asymmetric GARCH(1, 1) processes have been introduced to investigate asymmetric volatilities. A lot of researches have also been directed to non-stationary volatilities to deal with frequent high ups and downs in financial time series. This article is concerned with both asymmetric and non-stationary GARCH-type models. As a subsequent paper of Choi et al. (2020), we review various asymmetric and non-stationary GARCH(1, 1) processes, and in turn propose how to compare competing models using a parametric bootstrap methodology. As an illustration, Dow Jones Industrial Average (DJIA) is analyzed.

• The Journal of the Korea Contents Association
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• v.13 no.12
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• pp.369-378
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• 2013

The Korean Won-Dollar exchange markets showed radical price movements in the late 1990s and 2008. Therefore it provides good sources for studying volatility phenomena. Using the GARCH option models, I analysed how the prices of foreign exchange options react volatilities in the foreign exchange spot prices. For this I compared the explanatory power of three option models(Black and Scholes, Duan, Heston and Nandi), using the Won-Dollar OTC option markets data from 2006 to 2013. I estimated the parameters using MLE and calculated the mean square pricing errors. According to the my empirical studies, the pricing errors of Duan, Black and Scholes models are 0.1%. And the pricing errors of the Heston and Nandi model is greatest among the three models. So I would like to recommend using Duan or Black and Scholes model for hedging the foreign exchange risks. Finally, the historical average of spot volatilities is about 14%, so trading the options around 5% may lead to serious losses to sellers.

• The Journal of the Korea Contents Association
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• v.17 no.9
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• pp.300-309
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• 2017

This paper examines the cyclical fluctuation of 'construction orders' and 'construction investment' using HP filter, Bandpass filter and Beveridge-Nelson decomposition methods. The main results are as follows. As a result of the analysis of the cyclical fluctuation of construction orders, it was analyzed that there were about 7 cyclical fluctuations from 1976 to the first quarter of 2017. Construction orders for cyclical fluctuations peaked in the second quarter of 2015 and turned to a downward trend. On the other hand, construction investment has experienced about 6 cycles of fluctuations during the same period, and it has been rising continuously since the bottom of 3Q12. This is consistent with the general theory that construction orders precede construction investments. In addition, the comparison of the construction orders, construction investment, and GDP amplitude shows that the GDP amplitude is the smallest and stable, and the construction orders have the greatest variation in amplitude. Therefore, construction orders should be adjusted by government policy depending on economic fluctuations.

• Industry Promotion Research
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• v.6 no.3
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• pp.19-24
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• 2021

There should be no problem in the measurement system for scientific quality management. In this paper, we want to correctly identify the factors that can affect the measurement results during the measurement process and identify what causes them when the measurement results cause problems in terms of location and variation. Variations in the measurement system are largely described in terms of location and dispersion. Location-related attributes are accuracy, stability, and linearity while dispersion-related attributes are reproducibility and repeatability. Analyzing the factors associated with dispersion is an R&R analysis, in which the size of repeatability and reproducibility is represented by a range of differences between multiple measurements and a range of differences between measurements, and 99% of dispersion is determined. Experimental design can also be used for measurement system analysis. Proper analysis is performed only when the factors causing the fluctuation, the worker and the product, are correctly identified as random or fixed factors.

• Journal of Korea Port Economic Association
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• v.26 no.4
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• pp.88-100
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• 2010

This paper investigates the influence of industrial activity volatility and exchange rate volatility on import container volume of the Korea during the 1999:1- 2010:9. Conditional variance from the GARCH(1, 1) model is applied as the volatility. The Johansen multivariate cointegration method and the error correction (general-to-specific) method are applied to study the relationship between import volume and its determinants. The empirical results show that volatility has statistically significant negative effect on import volume.

• The Korean Journal of Applied Statistics
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• v.28 no.3
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• pp.429-442
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• 2015

Volatility forecasting in financial markets is an important issue because it is directly related to the profit of return. The volatility is generally modeled as time-varying conditional heteroskedasticity. A generalized autoregressive conditional heteroskedastic (GARCH) model is often used for modeling; however, it is not suitable to reflect structural changes (such as a financial crisis or debt crisis) into the volatility. As a remedy, we introduce the Markov regime switching GARCH (MRS-GARCH) model. For the empirical example, we analyze and forecast the volatility of the daily Korea Composite Stock Price Index (KOSPI) data from January 4, 2000 to October 30, 2014. The result shows that the regime of low volatility persists with a leverage effect. We also observe that the performance of MRS-GARCH is superior to other GARCH models for in-sample fitting; in addition, it is also superior to other models for long-term forecasting in out-of-sample fitting. The MRS-GARCH model can be a good alternative to GARCH-type models because it can reflect financial market structural changes into modeling and volatility forecasting.

• International Area Studies Review
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• v.15 no.3
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• pp.175-188
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• 2011

This study aims to examine how the U.S. economic shocks affect the Japanese economy. It is widely believed that the U.S. economy has a significant effect on the Japanese economy. Actually, the U.S. accounts for a considerable amount of Japan's exports and imports. To the economic policymakers, it is very important to know how economic disturbances generated by the U.S. are transmitted to the Japanese economy. A vector autoregression(VAR) model is employed to investigate the international transmission channel of economic disturbances. The interactions of the U.S.-Japansese economy are investigated by using variance decompositions(VDCs). The results of this study provided the evidence that the U.S. economic shocks were important for the Japanese economy during the sample period. This study supports the notion of economic dependence of smaller open economy such as Japan as compared with larger economy such as the U.S.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.380-380
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• 2020

가뭄 피해 극복을 위한 인공 함양지 통합관리시스템의 일부로써 지표수-지하수 연계 특성 분석용 의사결정을 전달하는 인공지능 스마트 계측기의 필요성이 꾸준히 제기되어 왔으나 실용성과 효율성을 동시에 갖춘 계측기는 시장에 출시되지 않았다. 기존의 계측기는 단순 측정이 목적이었으며 분석을 위해서는 일정 기간 직접 계측하여 분석하거나, 계측데이터를 원격 망을 통하여 서버로 전송하고 관리자가 데이터를 해석하는 방식을 취하였다. 또한, 수질 계측과 수질의 미소 변동성을 동시에 계측하여 수질 변화상태를 판단 할 수 있는 수질 계측기는 상품화되지 않아 다목적 수질 분석에 한계점을 갖고 있다. 이러한 한계점이 기존의 지하수 수질 계측기로는 불가능한 수중 라돈을 채수 없이 계측 가능하도록 하고, 순간 수질 변화 및 수질 변화 요인분석이 가능한 계측을 위하여 라돈, 전도도, 수위, 수온 및 필름형 pH 센서를 개발하여 적용한 다항목 계측기로 통합하는 연구가 필요한 이유이다. 개발한 계측기는 빅데이터 기반의 지능형 수질 변동성 분석 알고리즘을 내장하고 수직 깊이 방향의 다중심도 계측이 가능하도록 핵심적인 통신 연결성을 확보하였고 다양한 수질에서 견딜 수 있으며 특히 인공함양에서 발생하는 철, 망간에 부식되지 않는 재질을 이용하여 설계한 '지표수-지하수 연계 특성 분석용 다심도 및 인공지능 스마트 계측장치'이다. 본 장치는 기존 지하수 수질 계측기에서는 불가능하였던 순간 수위변화 및 수위변화 요인분석이 가능한 계측을 위하여 초당 측정 샘플링 주파수(10Hz)를 높인 계측회로를 개발하여 적용하였다.

• Journal of Convergence for Information Technology
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• v.10 no.3
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• pp.67-75
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• 2020

This paper investigated the information spillover effect between stock market and bond market with the KOSPI daily index and MMF yield data. The overall analysis period is from May 2, 1997 to August 30, 2019. The empirical analysis was conducted by dividing the period from May 2, 1997 to December 30, 2008 before the global financial crisis, and from December 30, 2008 to August 30, 2019 after the global financial crisis, and the overall analysis period. The analysis shows that the EGARCH model considering asymmetric variability is suitable. The price spillover effect and volatility spillover effect existed in both directions between the stock market and the bond market, and the price transfer effect was greater in the period before the global financial crisis than in the period after the global financial crisis. Asymmetric volatility in information between stock and bond markets appears to exist in both markets.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.474-474
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• 2015

Horton 지수는 유역에 대한 수문순환의 특성을 정량화하는 지수로서 유역의 습윤량과 기화량의 비로 산출된다. 습윤량과 기화량은 토양 수분과 밀접한 관계를 가지므로 추계학적 거동에 따른 토양수분의 동역학모형을 파악하여 Horton 지수를 산출할 수 있다. 본 연구에서는 추계학적인 토양수분수지 모형을 이용하여 서울, 부산, 대구, 제주 지역을 대상으로 30년간 일 기상자료(강우량, 일 평균기온, 풍속, 상대습도, 일조시간)을 이용하여 Horton 지수를 각각 산출하였으며 Horton 지수에 대한 변동성 분석을 실시하였다. 분석 결과, 모든 대상 유역에서 기후의 계절성에 의하여 Horton 지수가 작아짐을 확인할 수 있었다. 하지만 습윤한 기후를 가진 서울과 건조한 기후를 가진 대구에서는 각각 연 강우량이 많거나 연 강우량이 적은 해에 Horton 지수에 미치는 기후의 계절성의 영향력이 줄어듦을 살펴볼 수 있었다.