뉴스충격과 대산항의 물동량

News Impact and the Throughputs of Daesan Port in Korea

This paper aims at measuring how new information is incorporated into volatility estimates. Various GARCH models are compared and estimated with monthly throughputs of Daesan port located in Korea. 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 the 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 throughputs. The coefficients of skewness and kurtosis both indicate that the unpredictable throughputs have 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) throughput shocks cause more volatility than small ones. This paper, also, reveals that three leverage models have no problems in capturing the correct impact of news on volatility and that bad news do cause higher volatility than good news. The impulse response technique shows that the standard GARCH model underpredicts volatility and the asymmetric volatility models are useful approaches to modeling conditional heteroscedasticity of throughputs in Daesan port.