• Journal of the Korean Data and Information Science Society
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• v.21 no.6
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• pp.1041-1049
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• 2010

In Korean professional baseball, attendance is the largest source of revenue for development of professional baseball and the highest concern of professional baseball teams. So, if there is demand forecasting model, it will be helpful for pennant chasers to work out the strategies for drawing attendance. For this reason, this research intends to suggest the model which estimates Korean professional baseball's attendance and uses all usable variables which have an effect on attendance in limited circumstances. We supposed that dependent variable is attendance as well as several independent variables and error term are homoscedastic variance. And then, we compared the models which assume conditional heteroscedastic variance like GARCH and EGARCH with GARCH-t models which use the assumption that error term's distribution follows student-t distribution. In result of that, we could confirm that the models which were made by using GARCH(1,1)-t made estimates the most accurately among the several models considered.

• The Korean Journal of Financial Management
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• v.17 no.2
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• pp.211-227
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• 2000

본 연구는 외환위기 이후 1998년 10월부터 2000년 3월까지의 일별 데이터를 사용하여 원/달러 역내시장과 역외시장간의 가격정보 이전에 관한 동조화여부를 실증분석 하였다. 원/달러 역내시장의 가격대용으로 원/달러 현물환율을 사용하였으며, 원/달러 역외시장의 가격대용으로 원/달러 역외선물환율인 NDF 1개월물을 사용하였다. 수익률이 중심이 된 기존의 많은 인과관계 연구들과는 달리 본 연구에서는 환율의 변화율에 대한 그랜져 인과관계 분석과 함께 이변량 GARCH모형을 이용하여 두 시장간에 있어서의 환율의 변화율과 변동성의 인과관계를 분석하였다. 그랜져 인과관계분석 결과 현물환율은 역외선물환율에 대해 강한 선도관계를 가지며 상대적으로 약하지만 역외선물환율 또한 현물환율에 대해 선도관계를 가지는 것으로 나타났다. 본 연구에 사용된 이변량 GARCH모형은 AR(1)-GARCH(1,1)모형으로서 분식 결과를 보면 조건부 변동성이 두 시장간에 상호의존적이며 한 시장의 변화율충격이 다른 시장의 변동성에 영향을 미치는 것이 양 시장간에 유의적으로 나타났다. 이는 현물환시장의 거래정보가 역외선물환시장의 가격형성에 영향을 미치며 역외선물환시장 거래정보 또한 현물환시장으로 이전되어 원/달러 역내시장과 역외시장이 잘 동조화 되어 있다고 말할 수 있다. 즉 정보가 먼저 한 시장에 반영 된 후 다른 시장에 전달되는 정보의 일방 통행적 흐름이 아니라 정보의 반영이 두 시장에서 동시에 이루어지고 정보의 흐름이 양방향으로 이루어짐을 알 수 있다.

• East Asian Journal of Business Economics (EAJBE)
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• v.1 no.1
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• pp.17-21
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• 2013

Purpose: Forecasting of petroleum consumption is useful in planning and management of petroleum production and control of air pollution. Research Design, Data and Methodology: ARMA models, sometimes called Box-Jenkins models after the iterative Box-Jenkins methodology usually used to estimate them, are typically applied to auto correlated time series data. Results: Petroleum consumption modeling plays a role key in big urban air pollution planning and management. In this study three models as, MLFF, MLFF with GARCH (1,1) and ARMA(1,1), have been investigated to model the petroleum consumption forecasts. Certain standard statistical parameters were used to evaluate the performance of the models developed in this study. Based upon the results obtained in this study and the consequent comparative analysis, it has been found that the MLFF with GARCH (1,1) have better forecasting results.. Conclusions: Survey of data reveals that deposit of government policies in recent yeas, petroleum consumption rises in Tehran and unfortunately more petroleum use causes to air pollution and bad environmental problems.

• Journal of Korea Port Economic Association
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• v.30 no.3
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• pp.1-14
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• 2014

This paper aims at measuring how new information is incorporated into volatility estimates. Various GARCH models are compared and estimated with daily BDI(Baltic Dry Index) data. While most researchers agree that volatility is predictable, they differ on how this volatility predictability should be modelled. This study, hence, introduces the asymmetric or leverage volatility models, in which good news and bad news have different predictability for future. We provide the systematic comparison of volatility models focusing on the asymmetric effect of news on volatility. Specifically, three diagnostic tests are provided: the sign bias test, the negative size bias test, and the positive size bias test. From the Ljung-Box test statistic for twelfth-order serial correlation for the level we do not find any significant serial correlation in the unpredictable BDI. The coefficients of skewness and kurtosis both indicate that the unpredictable BDI has a distribution which is skewed to the left and significantly flat tailed. Furthermore, the Ljung-Box test statistic for twelfth-order serial correlations in the squares strongly suggests the presence of time-varying volatility. The sign bias test, the negative size bias test, and the positive size bias test strongly indicate that large positive(negative) BDI shocks cause more volatility than small ones. This paper, also, shows that three leverage models have problems in capturing the correct impact of news on volatility and that negative shocks do not cause higher volatility than positive shocks. Specifically, the GARCH model successfully reveals the shape of the news impact curve and is a useful approach to modeling conditional heteroscedasticity of daily BDI.

• The Korean Journal of Applied Statistics
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• v.29 no.1
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• pp.1-12
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• 2016

Contrasted with the standard linear ARMA models, financial time series exhibits non-standard features such as fat-tails, non-normality, volatility clustering and asymmetries which are usually referred to as "stylized facts" in financial time series context (Terasvirta, 2009). We are accordingly led to ad hoc models (apart from ARMA) to accommodate stylized facts (Andersen et al., 2009). The paper aims to give a contemporary overview on financial and special time series models based on the recent literature and on the author's publications. Various models are illustrated including asymmetric models, integer valued models, multivariate models and high frequency models. Selected statistical issues on the models are discussed, bringing some perspectives to the future works in this area.

• 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 Korean Journal of Applied Statistics
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• v.28 no.6
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• pp.1163-1170
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• 2015

Various computational methods for obtaining volatilities for financial time series are reviewed and compared with each other. We reviewed model based GARCH approach as well as the data based method which can essentially be regarded as a smoothing technique applied to the squared data. The method for high frequency data is focused to obtain the realized volatility. A hybrid method is suggested by combining the model based GARCH and the historical volatility which is a data based method. Korea stock prices are analysed to illustrate various computational methods for volatilities.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.2
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• pp.15-23
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• 2021

This study investigates the presence of the day-of-the-week anomaly in exchange rate for 30 developing countries with free floating exchange rate regimes using daily data from January 2, 2011 to December 31, 2019. First, we apply the GARCH panel to estimate the intraday effect for all the sampled countries. Second, we run poolability test to check whether the coefficients of the GARCH panel are the same for all countries sampled. The result of poolability test rejects the homogeneity assumption. This implies that our sample countries contain heterogeneity. Third, we apply mean-group estimation by averaging the coefficients for all individual GARCH estimations. Fourth, we divided our sample of developing countries into three groups based on capital restriction index for the reason that the effect of monetary policy on the exchange rate depends on the degree of capital account liberalization. The empirical evidence for the return equation suggests that Mondays are connected with lower volatility whereas Thursdays experiences higher return compared to Tuesdays. The lowest estimated coefficient for full sample, group 1 and group 2, is Friday, but for group 2 is Thursday. We find similar result for the volatility equations, which show that Monday returns are lower compared to Tuesday.

• International Area Studies Review
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• v.13 no.1
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• pp.103-122
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• 2009

The paper is basically designed to investigate any existence of co-movement among foreign exchange market, goods market, and monetary market implemented by relative PPP and interest rate parity. And, rational expectation and GARCH-M model are employed for an empirical application. The result revealed that since the co-movement among the markets is hardly found, an efficiency of foreign exchange market is independent from any shocks from the goods market and the monetary market. Whereas, the exchange rate is strongly effected by a real interest rate parity. To this end, the real interest rate should be a key policy instrument to stabilize the foreign exchange market.

• The Korean Journal of Financial Management
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• v.24 no.4
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• pp.107-134
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• 2007

This paper tests the relationship among returns, volatilities, contracts and open interests of KOSPI 200 futures markets with the various dynamic models such as granger-causality, impulse response, variance decomposition and ARMA(1, 1)-GJR-GARCH(1, 1)-M. The sample period is from July 7, 1998 to December 29, 2005. The main empirical results are as follows; First, both contract change and open interest change of KOSPI 200 futures market tend to lead the returns of that according to the results of granger-causality, impulse response and variance decomposition with VAR. These results are likely to support the KOSPI 200 futures market seems to be inefficient with rejecting the hypothesis 1. Second, we also find that the returns and volatilities of the KOSPI 200 futures market are effected by both contract change and open interest change of that due to the results of ARMA(1,1)-GJR-GARCH(1,1)-M. These results also reject the hypothesis 1 and 2 suggesting the evidences of inefficiency of the KOSPI 200 futures market. Third, the study shows the asymmetric information effects among the variables. In addition, we can find the feedback relationship between the contract change and open interest change of KOSPI 200 futures market.