• The Korean Journal of Applied Statistics
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• v.21 no.5
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• pp.801-811
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• 2008

Modeling financial phenomena with diffusion processes is a commonly used methodology in the area of modern finance. Recently, various types of diffusion models have been suggested to explain the specific financial processes, and their related inference methodology have been also developed. In particular, likelihood methods for the efficient and accurate inference have been explored in various ways. In this paper, we review the mathematical properties of an approximated likelihood method, which is obtained by linearizing the drift coefficient of a diffusion process.

• The Korean Journal of Applied Statistics
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• v.24 no.6
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• pp.1007-1020
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• 2011

Since the research of Black and Scholes (1973), modeling methods using diffusion processes have performed principal roles in financial engineering. In modern financial theories, various types of diffusion processes were suggested and applied in real situations. An estimation of the model parameters is an indispensible step to analyze financial data using diffusion process models. Many estimation methods were suggested and their properties were investigated. This paper reviews the statistical properties of the, Euler approximation method, New Local Linearization(NLL) method, and Generalized Methods of Moment(GMM) that are known as the most practical methods. From the simulation study, we found the NLL and Euler methods performed better than GMM. GMM is frequently used to estimate the parameters because of its simplicity; however this paper shows the performance of GMM is poorer than the Euler approximation method or the NLL method that are even simpler than GMM. This paper shows the performance of the GMM is extremely poor especially when the parameters in diffusion coefficient are to be estimated.

• The Korean Journal of Applied Statistics
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• v.28 no.5
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• pp.895-906
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• 2015

Diffusion is a mathematical tool to explain the fluctuation of financial assets and the movement of particles in a micro time scale. There are ongoing statistical trials to develop an estimation method for diffusion models based on likelihood. When we estimate diffusion models by applying the maximum likelihood estimation method on data observed at discrete time points, we need to know the transition density of the diffusion. In order to approximate the transition densities of diffusion models, we suggests the method to approximate the path integral of the random process with normal random variables, and compare the numerical properties of the method with other approximation methods.

• The Korean Journal of Applied Statistics
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• v.26 no.5
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• pp.767-783
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• 2013

Generalized Method of Moment(GMM) is a popular estimation method to estimate model parameters in empirical financial studies. GMM is frequently applied to estimate diffusion models that are basic techniques of modern financial engineering. However, recent research showed that GMM had poor properties to estimate the parameters that pertain to the diffusion coefficient in diffusion models. This research corrects the weakness of GMM and suggests alternatives to improve the statistical properties of GMM estimators. In this study, a simulation method is adopted to compare estimation methods. Out of compared alternatives, NGMM-Y, a version of improved GMM that adopts the NLL idea of Shoji and Ozaki (1998), showed the best properties. Especially NGMM-Y estimator is superior to other versions of GMM estimators for the estimation of diffusion coefficient parameters.

• The Korean Journal of Applied Statistics
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• v.31 no.6
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• pp.801-810
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• 2018

Diffusion is a random process used to model financial and physical phenomena. When we construct statistical models for repeatedly observed diffusion processes, the idea of random effects needs to be considered. In this research, we introduce random parameters for an Ornstein-Uhlenbeck diffusion model and geometric Brownian motion diffusion model. In order to apply the maximum likelihood estimation method, we tried to build likelihoods in closed-forms, by assuming appropriate distributions for random effects. We applied the random effect models to data consisting of Dow Jones Industrial Average indices recorded daily over 27 years from 1991 to 2017.

• International Area Studies Review
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• v.20 no.1
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• pp.105-125
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• 2016

The expansionary monetary policy was practiced after 2001 in Japan to treat the deflation spiral, and reduced only the nominal interest rates and domestic household demand. One of the most serious factors for this failure was the change of private sector's expectancy. This paper has studied the effect of Japanese monetary policy in 21c., with empirical research based on a renewed macroeconomic model and the VAR. The empirical analysis shows that the effect of monetary policy on the national income during 2001.01-2015.03 is weaker than that of 1985.01-1994.04. Money volume has a diminutive effect on the growth of GDP within a short term after 2001. The change in the expectations of the private sectors might have been the cause of ineffectiveness of the expansive monetary policy. Economic agents learned from the past Japanese financial crisis that an expansive monetary policy increased the inflation rate and caused the 'bubbles to burst' afterwards. The VAR analysis says that the effectiveness of monetary policy on the economic depression declined over the past 20 years and the expansion of money volume has no influence on exchange rate and net export. This means that the expansive monetary policy lost its effect on net export and national income steadily. Monetary policy makers have to recognize this fact, and to consider another anti-cycle political instrument, i.e. the fiscal policy with government debt.

• Communications for Statistical Applications and Methods
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• v.17 no.4
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• pp.599-609
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• 2010

Many of financial data are explained via diffusion models in modern financial research. Various types of estimation methods of diffusion processes were suggested by many authors. In this paper, we tested the properties of the NLL estimation method, suggested by Shoji and Ozaki (1998), of diffusion processes in the view of the bias and variance of the estimators and applied the method to estimate the model parameters for the U.S. fedral funds rate data and Korean inter-bank exchange rate data. By simulation study we showed that the NLL method provides relatively good estimators, in the meaning that the estimator has less bias than the Euler method, while keeping the variance similar level. We also provide the NLL estimates of U.S fedral funds rate data and Korean inter-bank exchange rate data.

• The Korean Journal of Applied Statistics
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• v.23 no.2
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• pp.383-392
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• 2010

Modelling financial phenomena with diffusion processes is frequently used technique. This study reviews the earlier researches on the approximation problem of transition densities of diffusion processes, which takes important roles in estimating diffusion processes, and consider the method to obtain the coefficients of series efficiently, in series approximation method of transition densities. We developed a new efficient algorithm to compute the coefficients which are represented by repeated Dynkin operator on Hermite polynomial.

• The Journal of Society for e-Business Studies
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• v.20 no.3
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• pp.11-28
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• 2015

Due to the mobil-centered lifestyle following the wider use of Smartphones, Mobile services, including mobile banking and mobile shopping business have increased rapidly. Also with the emergence of "Fintech", which finance combined with technology, IT based financial market is going to be highly promising. In this trend, interests mobile credit cards are increasing. But diffusion of the mobile credit card services is still in the low level. In this situation, to identify factors that influencing satisfaction and continuous usage intention on mobile credit card, this study applied innovation diffusion theory (IDT) and post acceptance model (PAM). To conducting this research, survey data were collected, and we used SmartPLS to analyze survey data. As a result of the study, perceived easy of use, image, compatibility and facilitation positively affect user's satisfaction in mobile credit cards and that such satisfaction have a positive impact on continuous intention to use. The facilitation influences user satisfaction more strongly for those who use mobile credit cards more than plastic credit cards. Also, perceived of use and image influence user satisfaction more strongly for those who use plastic credit cards more than mobile credit cards. It is expected that this study can be a guideline for credit card service providers and policy makers to invigorate mobile credit card business. Also it worths as a early-stage research on Fintech-related studies.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.31-33
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• 2008

산업사회에서의 전력공급 계통은 설비고장이 발생할 경우 해당지역에 국한되어 정전이 발생하기 때문에 피해가 확산되거나 사회적인 이슈가 되지는 않았다. 광케이블을 이용한 정보통신사회가 구축되어 금융과 언론을 비롯한 대부분의 생활이 인터넷을 중심으로 진행되고 있고 향후 지식기반 사회로의 진전이 급속히 진전될 것에 대비하여 전력계통 설비와 운영 방법의 고도화가 필요하게 되었다. 전력IT는 현재의 전력설비와 네트워크, IT를 이용하여 더욱 심층적인 연구가 진행되고 있으며 본 논문에서는 전력IT 연구과제 결과물의 활용성을 높이고 기술개발 과정에서의 시행착오를 최소화하기 위해 총 10개 과제를 하나로 운영할 경우를 상정하여 연구에 필요한 기술체계 모형을 개발하였고 이 모형을 토대로 향후 분산형 전원을 포함한 전력계통의 최적운영과 고장예측기법을 이용한 설비관리로 정전을 예방하여 최고품질의 전력을 공급하는데 기여하고자 하였다. 이 논문은 전력IT의 도입배경과 현재까지의 연구 성과분석을 토대로 실 계통 검증 5단계와 기술체계 모형 그리고 통합운영시스템 개념도 제시 순으로 작성하였다.