• Journal of Korea Port Economic Association
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• v.31 no.1
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• pp.1-14
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• 2015

The standard GARCH model imposing symmetry on the conditional variance, tends to fail in capturing some important features of the data. This paper, hence, introduces the models capturing asymmetric effect. They are the EGARCH model and the GJR model. 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. This paper shows that there is significant evidence of GARCH-type process in the data, as shown by the test for the Ljung-Box Q statistic on the squared residual data. The estimated unconditional density function for squared residual is clearly skewed to the left and markedly leptokurtic when compared with the standard normal distribution. The observation of volatility clustering is also clearly reinforced by the plot of the squared value of residuals of export volume and values. The unconditional variance of both export volumes and export value indicates that large shocks of either sign tend to be followed by large shocks, and small shocks of either sign tend to follow small shocks. The estimated export volume news impact curve for the GARCH also suggests that $h_t$ is overestimated for large negative and positive shocks. The conditional variance equation of the GARCH model for export volumes contains two parameters ${\alpha}$ and ${\beta}$ that are insignificant, indicating that the GARCH model is a poor characterization of the conditional variance of export volumes. The conditional variance equation of the EGARCH model for export value, however, shows a positive sign of parameter ${\delta}$, which is contrary to our expectation, while the GJR model exhibits that parameters ${\alpha}$ and ${\beta}$ are insignificant, and ${\delta}$ is marginally significant. That indicates that the asymmetric volatility models are poor characterization of the conditional variance of export value. It is concluded that the asymmetric EGARCH and GJR model are appropriate in explaining the volatility of export volume, while the symmetric standard GARCH model is good for capturing the volatility.

• Journal of Digital Convergence
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• v.20 no.3
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• pp.325-331
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• 2022

As IoT devices are used in various ways in an edge network environment, multiple studies are being conducted that utilizes the information collected from IoT devices in various applications. However, it is not easy to apply accurate IoT data immediately as IoT data collected according to network environment (interference, interference, etc.) are frequently missed or error occurs. In order to minimize mistakes in IoT data collected in an edge network environment, this paper proposes a management technique that ensures the reliability of IoT data by randomly generating signature values of IoT data and allocating only Security Information (SI) values to IoT data in bit form. The proposed technique binds IoT data into a blockchain by applying multiple hash chains to asymmetrically link and process data collected from IoT devices. In this case, the blockchainized IoT data uses a probability function to which a weight is applied according to a correlation index based on deep learning. In addition, the proposed technique can expand and operate grouped IoT data into an n-layer structure to lower the integrity and processing cost of IoT data.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.13 no.6
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• pp.521-528
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• 1988

Into the telecommunications industry, which had been monopolistic, a few advanced countries introduced competition through 70's and 80's. And this trend is going on worldwide. The introduction of competition into the industry is made mainly in the long distance, international and enhanced market. This liberalisation results from the fundamental change of the cost function. Suggesting that the cost comprises of that of the facility sector and that of the operation sector there exists the economies of scale in the facility sector in general. The major ground for the monopolistic industrial structure in the past was the natural monopoly depending on the economies of scale. But the rapid advance of the technology by a large margin. This decrease has resulted in the change of the cost function. That is while there exists the economies of scale in the smaller production scale, the average cost increases beyond a certain scale. This means that the natural monopoly collapsed, and that the competitive structure is more efficient than the monopolistic structure. But, because there exists economies of scale in the smaller scale, the desirable number of players, which could result in efficient industry structure depends on the market size. Such correlation between technological level market size and the degree of regulation is found in the case of U.S.A., Japan and U.K., where deregulation policy of the telecommunications market has already been carried out. In U.S.A., which has the largest market and the highest technological level the degree of regulation is lowest. Also in the order of Japan and U.K. the regulation is severer. Japan and U.K. are likely to liberalize still more, as the technology advances and the market grows. This article is just the beginning of the research, and this hypothesis requires more detailed research.