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정규혼합모형의 오차를 갖는 GARCH 모형을 이용한 옵션가격결정에 대한 실증연구
정승환,이태욱,Jeong, Seung Hwan,Lee, Tae Wook 한국데이터정보과학회 2017 한국데이터정보과학회지 Vol.28 No.2
The option pricing of Black와 Scholes (1973) and Merton (1973) has been widely reported to fail to reflect the time varying volatility of financial time series in many real applications. For example, Duan (1995) proposed GARCH option pricing method through Monte Carlo simulation. However, financial time series is known to follow a fat-tailed and leptokurtic probability distribution, which is not explained by Duan (1995). In this paper, in order to overcome such defects, we proposed the option pricing method based on GARCH models with normal mixture errors. According to the analysis of KOSPI200 option price data, the option pricing based on GARCH models with normal mixture errors outperformed the option pricing based on GARCH models with normal errors in the unstable period with high volatility.
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정승환,최익,최주엽,Jung, Seung-Hwan,Choy, Ick,Choi, Ju-Yeop 한국전자통신학회 2013 한국전자통신학회 논문지 Vol.8 No.7
Generally, the buck converter controller was designed to control output voltage of the converter. However, design of the controller in photovoltaic power conditioning system is different from general design. the controller in photovoltaic power conditioning system controls input voltage of the converter(output voltage of the solar cell) for MPPT(Maximum Power Point Tracking). This paper proposes novel buck converter model which can control input voltage of the converter. We integrate this model with a model of solar cell. and linearize at the operating point(MPP). In addition, we determine whether or not suitable for the general linear controller design into small and large signal analysis.
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선물시장에서 러프집합 기반의 유전자 알고리즘을 이용한 최적화 거래전략 개발
정승환,오경주,Chung, Seung Hwan,Oh, Kyong Joo 한국데이터정보과학회 2014 한국데이터정보과학회지 Vol.25 No.2
As the importance of algorithm trading is getting stronger, researches for artificial intelligence (AI) based trading strategy is also being more important. However, there are not enough studies about using more than two AI methodologies in one trading system. The main aim of this study is development of algorithm trading strategy based on the rough set theory that is one of rule-based AI methodologies. Especially, this study used genetic algorithm for optimizing profit of rough set based strategy rule. The most important contribution of this study is proposing efficient convergence of two different AI methodology in algorithm trading system. Target of purposed trading system is KOPSI200 futures market. In empirical study, we prove that purposed trading system earns significant profit from 2009 to 2012. Moreover, our system is evaluated higher shape ratio than buy-and-hold strategy.
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적분 이득의 비선형 적응 백스텝핑 제어 기법을 적용한 IPMSM의 속도 제어
정승환,최익,전용호,Jung, Seung-Hwan,Choy, Ick,Jeon, Yong-Ho 한국전자통신학회 2013 한국전자통신학회 논문지 Vol.8 No.6
본 논문은 IPMSM(Interior Permanent Magnet Synchronous Motor)의 속도 제어를 위한 비선형 백스텝핑 제어 기법을 제안한다. 비선형 백스텝핑 제어기법의 이득은 정상상태 에러를 제거하고, 좀 더 안정한 결과를 얻을 수 있도록 에러의 적분 이득을 포함하여 설계하였다. 또한, 부하 토크를 추정할 수 있도록 설계하여 부하의 변동에 대하여 빠른 적응성을 가지도록 하였다. 모의 실험을 통하여 적분 이득을 가지는 백스텝핑 제어기가 일정한 토크 운전영역에서 안정한 제어기임을 검증하고, 적분 이득이 없는 백스텝핑 제어기와 성능을 비교하였다.
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정승환,김민석,이한수,김종근,김성신,Jung, Seunghwan,Kim, Minseok,Lee, Hansoo,Kim, Jonggeun,Kim, Sungshin 한국정보통신학회 2020 한국정보통신학회논문지 Vol.24 No.2
Multivariate processes, such as large scale power plants or chemical processes are operated in very hazardous environment, which can lead to significant human and material losses if a fault occurs. On-line monitoring technology, therefore, is essential to detect system faults. In this paper, the ICA-based fault detection method is conducted using three different multivariate process data. Fault detection procedure based on ICA is divided into off-line and on-line processes. The off-line process determines a threshold for fault detection by using the obtained dataset when the system is normal. And the on-line process computes statistics of query vectors measured in real-time. The fault is detected by comparing computed statistics and previously defined threshold. For comparison, the PCA-based fault detection method is also implemented in this paper. Experimental results show that the ICA-based fault detection method detects the system faults earlier and better than the PCA-based method.
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실도로 주행 조건 기반의 자율주행자동차 고위험도 평가 시나리오 개발 및 검증에 관한 연구
정승환,유제명,정낙승,유민상,편무송,김재부 사단법인 한국자동차안전학회 2018 자동차안전학회지 Vol.10 No.4
Currently, a lot of researches about high risk test scenarios for autonomous vehicle and advanced driver assistance systems have been carried out to evaluate driving safety. This study proposes new type of test scenario that evaluate the driving safety for autonomous vehicle by reconstructing accident database of national automotive sampling system crashworthiness data system (NASS-CDS). NASS-CDS has a lot of detailed accident data in real fields, but there is no data of accurate velocity in accident moments. So in order to propose scenario generation method from accident database, we try to reconstruct accident moment from accident sketch diagram. At the same step, we propose an accident of occurrence frequency which is based on accident codes and road shapes. The reconstruction paths from accident database are integrated into evaluation of simulation environment. Our proposed methods and processor are applied to MILS (Model In the Loop Simulation) and VILS (Vehicle In the Loop Simulation) test environments. In this paper, a reasonable method of accident reconstruction typology for autonomous vehicle evaluation of feasibility is proposed.
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