• Journal of Information Technology Applications and Management
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• v.29 no.2
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• pp.17-25
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• 2022

Although the two types of currencies compete, the possibility of a virtual currency price bubble is diagnosed by assuming an economic model with currencies (won, virtual currency) that are intrinsically worthless. The won is supplied by the central bank to achieve the price stability target, while the supply of virtual currency increases by a fixed number. According to the basic price theory equation, as a simple proposition, cryptocurrency prices form a Martin Gale process [Schilling and Uhlig, 2019, p.20]. Based on the existing theoretical proposition, we applied the variance ratio verification method [Linton and Smetanina, 2016] and a simple technical chart method for empirical analysis. For the purpose of this study, the possibility of a bubble was empirically analyzed by analyzing the price volatility formed in the Korean virtual currency market over the past year, and brief policy implications for this were presented.

• Ocean and Polar Research
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• v.40 no.1
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• pp.49-58
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• 2018

This study aimed to analyze the causality of hairtail prices among import and domestic distribution channels using a Vector Error Correction Model(VECM). The results are as follows. First, since the ADF unit-root test suggests that each of the price variables, apart from retail price, has a unit root, the price variables should be 1st-differenced to secure the stability of the prices. Next, through the Johansen co-integration test, it was discovered that there are long-term relationships among the price variables. On the basis of the co-integration test, VECM analysis shows that the producer price has a long-run balance with the import and wholesale prices. In particular, when the prices deviate from the balance, the producer price dynamically adjusts to return to the long-term relationship among prices. It also indicates that the producer price has an impact on the import, wholesale, and retail prices in the short-term, and the import price has an influence on the producer and wholesale prices. In addition, the impulse response analysis demonstrates that the impulse of import and producer prices has a lasting impact on each of the prices.

• JOURNAL OF ELECTRICAL WORLD
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• no.10 s.154
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• pp.16-22
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• 1989

• Ocean and Polar Research
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• v.36 no.4
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• pp.327-341
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• 2014

This study aims to analyze causality among Wando abalone producer prices by size using a vector autoregressive model to expiscate the leading-price of Wando abalone in various price classes by size per kg. This study, using an analytical approach, applies a unit-root test for stability of data, a Granger causality test to learn about interaction among price classes by size for Wando abalone, and a vector autoregressive model to estimate the statistical impact among t-1 variables used in the model. As a result of our leading-price analysis of Wando abalone producer prices by shell size using a VAR model, first, DF, PP, and KPSS tests showed that the Wando abalone monthly price change rate by size differentiated by logarithm were stable. Second, the Granger causality relationship analysis showed that the price change rate for big size abalone weakly led the price change rate for the small and medium sizes of abalone. Third, the vector autoregressive model showed that three price change rates of t-1 period variables statistically, significantly impacted price change rates of own size and other sizes in t period. Fourth, the impulse response analysis indicated that the impulse responses of structural shocks for price change rate for big size abalone was relatively more powerful in its own size and in other sizes than shocks emanating from other sizes. Fifth, the variance decomposition analysis indicated that the price change rate for big size abalone was relatively more influential than the price change rates for medium and small size abalone.

• The Journal of Asian Finance, Economics and Business
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• v.6 no.4
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• pp.139-145
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• 2019

This study examines the dynamic linkages between food price inflation and its volatility in the context of Sri Lanka. The empirical evidence derived from the monthly data for the period from 2003M1 to 2017M12 for Sri Lanka. The relationship between inflation rate and inflation volatility has attracted more attention by theoretical and empirical macroeconomists. Empirical studies on the relationship between food inflation and food inflation variability is scarce in the literature. Food price inflation is defined as log difference of food price series. The volatility of a food price inflation is measured by conditional variance generated by the FIGARCH model. Preliminary analysis showed that food inflation is stationary series. Granger causality test reveals that food inflation seems to exert positive impact on inflation variability. We find no evidence for inflation uncertainty affecting food inflation rates. Hence, the findings of the study supports the Friedman-Ball hypothesis in both cases of consumer food price inflation and wholesale food price inflation. This implies that past information on food inflation can help improve the one-step-ahead prediction of food inflation variability but not vice versa. Our results have some important policy implications for the design of monetary policy, food policy thereby promoting macroeconomic stability.

• Ocean and Polar Research
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• v.37 no.4
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• pp.357-368
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• 2015

This study analyzed structural changes and asymmetry of price volatility during the period before and after a point of structural change in price volatility, using the Korean fresh common squid daily retail price data from January 1, 2004 to September 30, 2015. This study utilized the following analytical methods: the unit-root test was applied to ensure the stability of the data, the Quandt-Andrews breakpoint test was applied to find the point of structural change, and the Glosten-Jagannathan-Runkle GARCH and EGARCH models were applied to investigate the asymmetry of price volatility. The empirical results of this study are as follows. First, ADF, PP, KPSS and Zivot-Andrews tests showed that the daily retail price change rate of the Korean fresh common squid differentiated by logarithm was stable. Secondly, the ARIMA (2,1,2) model was selected by information criteria such as AIC, SC, and HQ. Thirdly, the Quandt-Andrews breakpoint test found that a single structural change in price volatility occurred on June 11, 2009. Fourthly, the Glosten-Jagannathan-Runkle GARCH and EGARCH models showed that estimates of coefficients within the models were statistically significant before and after structural change and also that asymmetry as a leverage effect existed before and after structural change.

• Korean Journal of Agricultural Science
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• v.45 no.4
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• pp.859-870
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• 2018

Dried red peppers are a staple agricultural product used in Korean cuisine and as such, are an important aspect of agricultural producers' income. Correctly forecasting both their supply and demand situations and price is very important in terms of the producers' income and consumer price stability. The primary objective of this study was to compare the performance of time series forecasting models for dried red peppers in Korea. In this study, three models (an autoregressive model with exogenous variables [ARX], AR-exponential generalized autoregressive conditional heteroscedasticity [EGARCH], and ARX-EGARCH) are presented for forecasting the wholesale price of dried red peppers. As a result of the analysis, it was shown that the ARX model and ARX-EGARCH model, each of which adopt both the rolling window and the adding approach and use the agricultural cooperatives price as the exogenous variable, showed a better forecasting performance compared to the autoregressive model (AR)-EGARCH model. Based on the estimation methods and results, there was no significant difference in the accuracy of the estimation between the rolling window and adding approach. In the case of dried red peppers, there is limitation in building the price forecasting models with a market-structured approach. In this regard, estimating a forecasting model using only price data and identifying the forecast performance can be expected to complement the current pricing forecast model which relies on market shipments.

• Proceedings of the Safety Management and Science Conference
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• 2005.11a
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• pp.537-557
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• 2005

The estimate on volatility of stock price is related with optimum of portfolio and Important for allocation of capital asset. If the volatility of stock price is varied according to macroeconomic variables on monetary policy and industrial production, it will assist capital asset to allocate. This paper is related with stock market volatilities on macroeconomic variables in U.S. and Europe, Korea. And, it Is pertain to vary in time of this variables. Thus, this paper is related with volatilities of monetary and physical macroeconomic variables on basis of statistics. And, it is ranged front capital investment to portfolio allocation. Also, this paper takes out of sample forecast and study more after this. In case Germany, France, Italy and the Netherlands, the relative importance of monetary policy and Industrial production Is different from these countries. In case Italy and the Netherlands, monetary policy is primary factor at stabilizing for volatility of stock price. In case Korea, increasing monetary policy and industrial production is positively affected stock market. It is that the positive effect of stock price is caused by mollifying monetary policy and economic growth. Specially, this conclusion is similar to US. In Korea, gradual increase in monetary and industrial production is necessary to stability of stock market. It is different to previous results on basis of increasing stock price of money in long period.

• Journal of The Korean Society of Agricultural Engineers
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• v.54 no.2
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• pp.7-14
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• 2012

To analyze any given situation, it is necessary to have information on elements which affect the situation. Particularly, there is greater variability in both frequency and magnitude of agricultural product prices as they are affected by various unpredictable factors such as weather conditions etc. This is the reason why it is difficult for the farmers to maintain their stable income through agricultural production and marketing. In this research, attempts are made to quantify the entropy of various situations inherent in the price changes so that the stability of farmers' income can be increased. Through this research, we developed an entropy model which can quantify the uncertainties of price changes using the probability distribution of price changes. The model was tested for its significance by comparing its simulation outcomes with actual ranges and standard deviations of price variations of the past using monthly agricultural product prices data. We confirmed that the simulation results reflected the features of the ranges and standard deviations of actual price variations. Also, it is possible for us to predict standard deviations for changed prices which will occur after a certain time using the information entropy obtained from relevant agricultural product price data before the time.

• Journal of the Korean Operations Research and Management Science Society
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• v.29 no.1
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• pp.31-41
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• 2004

This study analyzes the structure of the variations In the domestic bank earnings and examines their dynamic features by estimating the short-run response and the long-run adjustment Process after the changes in financial market variables. A system of the equations for the bank stock price index and KOSPI is formulated to utilize the whole information in the market and simultaneously estimated to identify the relationships between the market variables and the bank earnings. Since the bank stock price is found to be responsive to changes in none of the market variables in the short run, while being relatively responsive to dollar exchange rate and business state, It implies that a good economic conditions and a stable foreign exchange rate should be maintained to Improve the level of the stock price In the long run. In addition, the dynamic structure of the responses of the bank stock price index and KOSPI to the initial changes in the market variable are compared and anlayzed. The response of the bank stock price appears to take much longer in adjusting to the long-run eouilibrium level than that of KOSPI. As a result, the cumulative response of the bank stock price index over time is found much bigger than that of HOSPI.