• Asia-Pacific Journal of Business
• /
• v.13 no.3
• /
• pp.183-208
• /
• 2022

Purpose - The main purpose of this study is to widely investigate the impact of recent pandemic crises on the synchronization of the world capital markets through 25 stock indices from major developed countries. Design/methodology/approach - This study collects 25 stock indices from major developed countries and the time period is between January 5, 2001 and February 24, 2022. The data sets used in the study include finance.yahoo.com and Investing.com.. The Granger causality analysis, unit-root test, VAR analysis, and forecasting error variance decomposition were hired in order to analyze the data. Findings - First, there are significant inter-relations among 25 countries around recent major pandemic crises(such as SARS, A(H1N1), MERS, and COVID19), which is consistent result with previous literature. Second, COVID19 shows much stronger impact on the world-wide synchronization than other pandemics. Third, the return volatility of each stock market varies, unit root tests show that daily stock index data are unstable while daily stock index returns are stable, and VAR(Vector Auto Regression) analyses presents significant inter-relations among 25 capital markets. Fourth, from the impulse response function analyses, we find that each market affects the other markets for short term periods, about 2~4 days, and no long term effect was not found. Fifth, Granger causality tests show one-side or two-sides synchronization between capital markets and we estimate, through forecasting error variance decomposition method, that the explanatory portions of each capital market on other markets vary from 10 to 80%. Research implications or Originality - The above results all together show that pandemic crises have strong effects on the synchronization of world capital markets and imply that these synchronizations should be carefully considered both in the investment decisions by individual investors and in the financial and economic policies by governments.

• International Commerce and Information Review
• /
• v.12 no.1
• /
• pp.153-175
• /
• 2010

This study conducts an analysis to verify an existence of co-movement among the exchange rates of Yuan-Dollar, Yen-Dollar and Won-Dollar by using time series data. An analysis period is divided into two periods. Therefore the first analysis period is from Dec. 17, 1997 to Jul. 21th. 20, 2005 and the second analysis period is from Jul. 25th, 2005 to Nov. 20th. 2009. This paper uses VAR model and daily data of exchange rates during the period. According to the result of an empirical analysis, yuan-dollar exchange rate has affected by th other variables ; yen-dollar exchange rate. It can be proved by result of an impulse response test and variance decomposition test in the second period. Therefore the won-dollar, yen-dollar, and Yen-dollar exchange rate has been influenced each other and the relationship will be maintained.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 2007.11a
• /
• pp.477-481
• /
• 2007

The purpose of this study is to provide the ideal forecasting model of cadastral survey work load through the Economeatric Analysis of Time Series, Granger Causality and VAR Model Analysis, it suggested the forecasting reference materials for the total amount of cadastral survey general work load. The main result is that the derive of the environment variables which affect cadastral survey general work load and the outcome of VAR(vector auto regression) analysis materials(impulse response function and forecast error variance decomposition analysis materials), which explain the change of general work load depending on altering the environment variables. And also, For confirming the stability of time series data, we took a unit root test, ADF(Augmented Dickey-Fuller) analysis and the time series model analysis derives the best cadastral forecasting model regarding on general cadastral survey work load. And also, it showed up the various standards that are applied the statistical method of econometric analysis so it enhanced the prior aggregate system of cadastral survey work load forecasting.

• Journal of Service Research and Studies
• /
• v.5 no.1
• /
• pp.91-103
• /
• 2015

We examine the information transmission between the KT Spot and the KT Futures Index, the SK Telecom Spot and the SK Telecom Futures Index, based on the returns data offered by the Korea Exchange. The data includes daily return data from 1 January 2012 to 31 December 2014. Utilizing a dynamic analytical tool-the VAR model, Granger Causality test, Impulse Response Function and Variance Decomposition have been implemented. The results of the analysis are as follows. Firstly, results of Granger Causality test suggests the existence of mutual causality the KT Futures Index and the SK Telecom Futures Index precede and have explanatory power the KT Spot and the SK Telecom Spot However the results also identified a greater causality and explanatory power of the KT Spot and the SK Telecom Spot over the KT Futures Index and the SK Telecom Futures Index. Secondly, the results of impulse response function suggest that the KT Futures Index show immediate response to the KT Spot and are influenced by till time 4. From time 2, the impact gradually disappears. Also the SKT Futures Index show immediate response to the SKT Spot and are influenced by till time 4. From time 2, the impact gradually disappears. Lastly, the variance decomposition analysis shows that the changes of return of the KT Spot and SKT Spot are dependent on those of the KT Futures Index and the SK Telecom Futures Index. This implies that returns on the KT Spot and SKT Spot have a significant influence over returns on the KT Futures Index and the SK Telecom Futures Index. It contributes to the understanding of market price formation function through analysis of detached the KT Spot and the KT Futures Index, the SK Telecom Spot and the SK Telecom Futures Index.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.32 no.11C
• /
• pp.1127-1133
• /
• 2007

This paper proposes one of normalized QR-typed LMS (Least Mean Square) algorithms with computational complexity of O(N). This proposed algorithm shows the normalized property in terms of theoretical characteristics. This proposed algorithm is one of algorithms which normalize variance of input signal in terms of mean because QR-typed LMS is proportional to variance of input signal. In this paper, convergence characteristic analysis of normalized algorithm was made. Computer simulation was made by the algorithms used for echo canceller. Proposed algorithm has similar performance to theoretical value. And, we can see that proposed method shows similar one to performance of NLMS.by comparison among different algorithms.

• ETRI Journal
• /
• v.28 no.1
• /
• pp.59-66
• /
• 2006

Learning behaviors of a radial basis function network (RBFN) using a singular value decomposition (SVD) and stochastic gradient (SG) algorithm, together named RBF-SVD-SG, for odor sensing systems are analyzed, and a fast training method is proposed. RBF input data is from a conducting polymer sensor array. It is revealed in this paper that the SG algorithm for the fine-tuning of centers and widths still shows ill-behaving learning results when a sufficiently small convergence coefficient is not used. Since the tuning of centers in RBFN plays a dominant role in the performance of RBFN odor sensing systems, our analysis is focused on the center-gradient variance of the RBFN-SVD-SG algorithm. We found analytically that the steadystate weight fluctuation and large values of a convergence coefficient can lead to an increase in variance of the center-gradient estimate. Based on this analysis, we propose to use the least mean square algorithm instead of SVD in adjusting the weight for stable steady-state weight behavior. Experimental results of the proposed algorithm have shown faster learning speed and better classification performance.

• East Asian Economic Review
• /
• v.19 no.4
• /
• pp.357-379
• /
• 2015

We investigate interconnectedness and the contagion effect of default risk in Asian sovereign CDS markets since the global financial crisis. Using dynamic conditional correlation analysis, we find that there are significant co-movements in Asian sovereign CDS markets; that such co-movements tend to be larger between developing countries than between developed and developing countries; and that in the co-movements intra-regional nature is stronger than inter-regional nature. With the Spillover Index model, we measure contagion probabilities of sovereign default risk in CDS markets of seven Asian countries and find evidence of contagion effects among six of them; Japan is the exception. In addition, we find that these six countries are affected more by cross-market spillovers than by their own-market spillovers. Furthermore, a rolling-sample analysis reveals that contagion in the Asian sovereign CDS markets expands during episodes of extreme economic and financial distress, such as the Lehman Brothers bankruptcy, the European financial crisis, and the US-credit downgrade.

• Journal of Information Processing Systems
• /
• v.20 no.1
• /
• pp.76-84
• /
• 2024

This study constructed a VAR model with cotton futures and spot price data from April 30, 2009 to November 16, 2022, for empirical analysis utilizing the Granger causality test to analyze the dynamic relationship between cotton futures and spot market prices in China. The impulse response function and variance decomposition analysis showed that the cotton spot prices at flowering have a causal relationship with each other; in terms of mutual influence and impact, futures prices are higher than spot prices. Finally, it proposed countermeasures and suggestions from the perspective of establishing a standardized cotton spot market, improving the laws and regulations of the cotton futures market and trading system, and optimizing the structure of investment subjects.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.26 no.6
• /
• pp.1461-1470
• /
• 2016

In side channel analysis, signal processing techniques can be used as preprocessing to enhance the efficiency and performance of analysis by reducing the noise or compressing the dimension. As signal processing techiniques using singular value decomposition can increase the information of main signal and reduce the noise by using the variance and tendency of signal, it is a great help to improve the performance of analysis. Typical techniques of that are PCA(Principal Component Analysis), LDA(Linear Discriminant Analysis) and SSA(Singular Spectrum Analysis). PCA and LDA can compress the dimension with increasing the information of main signal, and SSA reduces the noise by decomposing the signal into main siganl and noise. When applying each one or combination of these techniques, it is necessary to compare the performance. Therefore, it needs to suggest methodology of that. In this paper, we compare the performance of the three technique and propose using Sinal-to-Noise Ratio(SNR) as the methodology. Through the proposed methodology and various experiments, we confirm the performance and efficiency of each technique. This will provide useful information to many researchers in the field of side channel analysis.

• Journal of Korean Society of Forest Science
• /
• v.88 no.1
• /
• pp.1-10
• /
• 1999

The dynamic relationships among import prices of roundwood are analyzed using the time series approach. A vector autoregression(VAR) model is estimated for six import prices(New Zealand, Chile, Russia, U.S.A., PNG, and Malaysia). Then Granger's causality test, variance decomposition analysis, and impulse response function analysis are also conducted. The major results are summarized as follows : (1) The prices of New Zealand and Russia are caused by only own lagged prices. (2) The prices of Chile and PNG are effected by New Zealand, the price of PNG is effected by New Zealand and Russia, and the price of U.S.A. is effected by those of Chile and PNG, respectively. (3) An exogenous shock in New Zealand will affect the prices of New Zealand, PNG, U.S.A., Chile, Russia. (4) An exogenous shock in Chile may also affect the prices of Chile, U.S.A., Russia.