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학술저널
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한국호텔관광학회 호텔관광연구 호텔관광연구 제18권 제4호 (통권 제67권)
발행연도
2016.7
수록면
45 - 61 (17page)

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The importance of a correctly specified volatility model is clear from the range of applications requiring estimates of conditional volatilities. That is because volatility can be regarded as a measure of information flow. We employ three models of predictable volatility and present a news impact curve which characterizes the impact of past shocks on the visitor volatility implicit in a volatility model. This paper suggests several diagnostic tests based on the news impact curve and compares the GARCH model with other volatility models that allow for asymmetry in the impact of news on volatility. This paper initially regresses the change rate of tourists on a constant and the seasonal dummies to obtain a measure of unpredictable element of outbound and inbound tourists. The volatility of unpredictable element, however, displays the clustering phenomenon associated with GARCH processes. Large shocks of either sign tend to be followed by large shocks, and small shocks of either sign tend to follow small shocks. There is also some negative skewness in unconditional variance of outbound tourists and zero excess kurtosis is confidently rejected. From the Ljung-Box test statistic for twelfth-order serial correlation, we find significant serial correlation left in the unpredictable series after our adjustment procedure. The sign bias test and size bias test are highly significant. These statistics mean that GARCH-type model is appropriate for estimating volatility. We, hence, employ symmetric the GARCH model and asymmetric EGARCH and GJR models to estimate conditional heteroskedasticity. We find that GARCH and EGARCH model are appropriate for modeling the conditional volatility of outbound as well as inbound tourists, but there is a difference between them. The news impact curve estimates for outbound tourists suggests that the conditional volatility of EGARCH model is smaller than that of GARCH model and there is a little volatility difference of bad and good news. The news impact curve of inbound tourists shows that the conditional volatility of the EGARCH model is smaller that of the other models but relative to the other volatility models, the EGARCH model tend to overstate the variance for bad news and to underestimate the variance for good news.

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