• Journal of Industrial Convergence
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• v.2 no.2
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• pp.127-147
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• 2004

This paper examines the time-series relations among expected return, risk, and book-to-market(B/M) at the portfolio level. The time-series analysis is a natural alternative to cross-sectional regressions. An alternative feature of the time-series regressions is that they focus on changes in expected returns, not on average returns. Using the time-series analysis, we can directly test whether the three-factor model explains time-varying expected returns better than the characteristic-based model. These results should help distinguish between the risk and mispricing stories. We find that B/M is strongly associated with changes in risk, as measured by the Fama and French(1993) three-factor model. After controlling for changes in risk, B/M contains little additional information about expected returns. The evidence suggests that the three-factor model explains time-varying expected returns better than the characteristic-based model.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.32 no.2
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• pp.43-49
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• 1983

In this study, model simplification problem using singular perturbation technique is considered. The correctness and errors of simplified model which is obtained by the use of this technique, depends upon the order and the time scaling factor of the simplified model But, unfortunately, there is no explicit criteria for selections of these parameters. In this paper, error equations are derived and expanded by using the useful properties of $L_2$-norm. Then, new criteria for selecting the order of the simplified model and time scaling factor with respect to error bound are suggested. Since these criteria, newly proposed in this study, have strong concern about error bound, it can be used to choose the minimum order of the simplified model and time scaling factor with respect to given error bound. Conversely, if the order of the simplified model and time scaling factor are given, the error induced by the simplification can also be computed easily.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.10
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• pp.513-521
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• 2020

In this paper, we have developed a Fama - French five factor model (FF5 model) from Fama & French (2015) by using concept of time-varying coefficient. For a data set, we have used monthly data form Kenneth R. French home page, it include Japan portfolios (classified by using size and book-to-market) and 5 factors from July 1990 to April 2020. The first analysis, we used Augmented Dickey-Fuller test (ADF test) for the stationary test, from the result, all Japan portfolios and 5 factors are stationary. Next analysis, we estimated a coefficient of Fama - French five factor model by using a generalized additive model with a thin-plate spline to create the time-varying coefficient Fama - French five factor model (TV-FF5 model). The benefit of this study is TV-FF5 model which can capture a different effect at different times of 5 factors but the traditional FF5 model can't do it. From the result, we can show a time-varying coefficient in all factors and in all portfolios, for time-varying coefficients of Rm-Rf, SMB, and HML are significant for all Japan portfolios, time-varying coefficients of RMW are positively significant for SM, and SH portfolio and time-varying coefficients of CMA are significant for SM, SH, and BM portfolio.

• The Journal of Information Technology
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• v.9 no.3
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• pp.77-89
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• 2006

The event study analyzes returns around event date at a time. Event study provides estimation periods and cumulative returns. Stock split announcements are generally associated with positive abnormal returns. It is important to investigate the responses of stocks to new information contained in the announcements of stock splits. So It is important to study the long term performance in the case of Stock Split. This Study forced to two approach method in evaluating the performance, the event time portfolio approach and calendar time portfolio approach. The event time portfolio approach exists the CAR model, BHAR model and WR model. And the calendar time portfolio approach has the 3 factor model, 4 factor model, CTAR model, and RATS model.

• The KIPS Transactions:PartD
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• v.13D no.7 s.110
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• pp.923-930
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• 2006

In this paper we design the system test model for the weapon system embedded software based on the Time Factor Method(TFM) considering time factors and suggest the results through the case study. For doing this, we discuss the features, system tests and the object-oriented model based UML notations of the weapon system embedded software. And we give a test method considering time factors, a measuring method to time factors, and a test case selection algorithm as an approach to the TFM for designing the system test model. The TFM based system test model consists of three factors (X, Y, Z) in the weapon system embedded software. With this model, we can extract test cases through the selection algorithm for a maximum time path in 'X', identify the objects related to the Sequence Diagram in 'Y' and measure the execution time of each objects which is identified by the Timing Diagram in 'Z' Also, we present the method of extracting the system test cases by applying the proposed system test model to the 'Multi-function missile defense system'.

• The Journal of Information Technology
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• v.9 no.4
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• pp.75-85
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• 2006

This study is to test the influence of stock option granting information on the firm's performance. The important issue in stock option is that agent cost is the important determinant factor for the long term performance. The agent cost arises between the manager and shareholders. So many study are concentrated in diminishing the agent cost, and develop some substitute tools to measure the agent cost. The event study about stock option analyzes returns around event date at a time. Event study provides estimation periods and cumulative returns. Announcements about stock option are generally associated with positive abnormal returns in short term period, but not showing positive effect in long term period. It is important to investigate the responses of stocks to new information contained in the announcements of stock option. Therefore it is important to study the long term performance in the case of stock option. The event time portfolio approach exists the CAR model, BHAR model and WR model. And the calendar time portfolio approach has the 3 factor model, 4 factor model, CTAR model, and RATS model. This study is forced to develop and arrange two approach method in evaluating the performance, the event time portfolio approach and calendar time portfolio approach.

• Communications for Statistical Applications and Methods
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• v.15 no.6
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• pp.825-835
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• 2008

Multivariate GARCH(MGARCH) has been useful in financial studies and econometrics for modeling volatilities and correlations between components of multivariate time series. An obvious drawback lies in that the number of parameters increases rapidly with the number of variables involved. This thesis tries to resolve the problem by using dimension reduction technique. We briefly review both factor models for dimension reduction and the MGARCH models including EWMA (Exponentially weighted moving-average model), DVEC(Diagonal VEC model), BEKK and CCC(Constant conditional correlation model). We create meaningful portfolios obtained after reducing dimension through statistical factor models and fundamental factor models and in turn these portfolios are applied to MGARCH. In addition, we compare portfolios by assessing MSE, MAD(Mean absolute deviation) and VaR(Value at Risk). Various financial time series are analyzed for illustration.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.3
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• pp.8-14
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• 2019

Most of the data envelopment analysis (DEA) models evaluate the relative efficiency of a decision making unit (DMU) based on the assumption that inputs in a specific period are consumed to produce the output in the same period of time. However, there may be some time lag between the consumption of input resources and the production of outputs. A few models to handle the concept of the time lag effect have been proposed. This paper suggests a new multi-period input DEA model considering the consistent time lag effects. Consistency of time lag effect means that the time delay for the same input factor or output factor are consistent throughout the periods. It is more realistic than the time lag effect for the same output or input factor can vary over the periods. The suggested model is an output-oriented model in order to adopt the consistent time lag effect. We analyze the results of the suggested model and the existing multi period input model with a sample data set from a long-term national research and development program in Korea. We show that the suggested model may have the better discrimination power than existing model while the ranking of DMUs is not different by two nonparametric tests.

• Proceedings of the KIPE Conference
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• 1998.10a
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• pp.642-647
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• 1998

A new small-signal model for the controlled on-time boost power factor correction (PFC) circuit is presented. The proposed small-signal model is valid up to high frequencies over lKHz. The model can be used in designing the voltage feedback compensation of PFC circuits, the control bandwidth of which is maximized with auxiliary means of removing the low-frequency ripple from the output. The accuracy of the model is confirmed by a 200W experimental hardware

• Proceedings of the KIPE Conference
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• 1999.07a
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• pp.126-129
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• 1999

This paper presents a new averaged model for controlled on time boost power factor correction (PFC) circuit. The proposed model accurately predicts the average behavior of the PFC circuit, and offers a good alternative in studying the large signal dynamics of the circuit. The accuracy of the model is verified through both computer simulation and experiments.