• 농업과학연구
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• 제38권2호
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• pp.383-391
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• 2011

Traditional international trade theory assumes that import goods and domestically produced goods of the same industry are equal in quality. However the substitutability of the two goods is imperfect. This article estimated the import functions of pulp and paper using econometric and vector autoregressive models, and calculated the elasticities of substitution between imported and domestically produced pulp and paper. The import of pulp is inelastic to import price and domestic price, and elastic to national income in econometric model. And it is inelastic to import price, domestic price and national income in vector autoregressive model. On the other hand, the import of paper is inelastic to domestic price, and elastic to import price and national income in econometric model. And it is inelastic to import price and domestic price, and elastic to national income in vector autoregressive model. The elasticity of substitution between imported and domestically produced pulp was positive, and the elasticity was respectively 0.42 and 0.20 in econometric and vector autoregressive models. This may be because of the high proportion of imports. On the other hand, the elasticity of substitution between imported and domestically produced paper was positive, and the elasticity was respectively 0.75 and 0.81 in econometric and vector autoregressive models. This may be because the quality of imported paper is different from that of domestically produced paper.

• Journal of Information Technology Applications and Management
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• 제19권2호
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• pp.217-231
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• 2012

In the past, companies should make enormous facility investment and acquire a right to do business in order to join communication markets, but now they can do business without important facilities, such as communication networks. Such a movement to ease regulations about companies which want to newly join the communication industry is expected not only to change a competition frame of the mobile communication market but also to greatly affect the entire communication industry. Through this study aiming to look into a way to calculate a reasonable wholesale price related to the government's introduction of the Mobile Virtual Network Operator (MVNO) system, I came up with a following result. I applied the operating profit percentage and the ratio of operating gain to cost to the cost plus model and retail minus model, respectively, to calculate the wholesale price and found that when I calculated with the cost plus model applying the operating profit percentage, I could get the highest wholesale price. On the other hand, I got the lowest wholesale price with the retail minus model by applying the operating profit percentage. Division of expenses and calculation of profit percentage are important factors in calculating the wholesale price and such results are expected to help accurate calculation of the MVNO wholesale price.

• 부동산연구
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• 제27권1호
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• pp.45-57
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• 2017

본 연구에서는 물류부동산의 가격결정에 영향을 미치는 요인에 대하여 헤도닉 가격 모형을 이용하여 분석하였다. 연구의 분석을 위하여, 2006년부터 2015년까지 10년간 경기도지역에서 거래된 물류센터의 실거래 사례를 전수 조사하였다. 또한 매매가격 형성요인으로 건물특성, 경제특성, 투자특성 및 시간특성을 설정하였고, 헤도닉 가격 모형을 활용하여 다중회귀분석을 실시하였다. 분석결과, 첫째, 규모의 경제에 대한 선호도 경향으로 인하여 대형면적의 매매가격이 높게 형성되었고, 둘째, 간접투자의 경우에 더욱 적극적인 투자성향으로 인하여 직접투자의 경우보다 매매가격이 상대적으로 높게 나타났으며, 셋째, 물류센터의 투자에 대한 다양한 노하우를 보유한 외국인투자자가 매매가격을 주도하고 있는 것으로 판단된다. 본 연구를 통하여 물류센터에 대한 투자의사 결정의 판단기준을 제시하고자 한다.

• International journal of advanced smart convergence
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• 제12권1호
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• pp.18-30
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• 2023

We compared empirically the forecast accuracies of the LSTM model, and the ARIMA model. ARIMA model used auto.arima function. Data used in the model is 100 days. We compared with the forecast results for 50 days. We collected the stock closing prices of the top 4 companies by market capitalization in Korea such as "Samsung Electronics", and "LG Energy", "SK Hynix", "Samsung Bio". The collection period is from June 17, 2022, to January 20, 2023. The paired t-test is used to compare the accuracy of forecasts by the two methods because conditions are same. The null hypothesis that the accuracy of the two methods for the four stock closing prices were the same were rejected at the significance level of 5%. Graphs and boxplots confirmed the results of the hypothesis tests. The accuracies of ARIMA are higher than those of LSTM for four cases. For closing stock price of Samsung Electronics, the mean difference of error between ARIMA and LSTM is -370.11, which is 0.618% of the average of the closing stock price. For closing stock price of LG Energy, the mean difference is -4143.298 which is 0.809% of the average of the closing stock price. For closing stock price of SK Hynix, the mean difference is -830.7269 which is 1.00% of the average of the closing stock price. For closing stock price of Samsung Bio, the mean difference is -4143.298 which is 0.809% of the average of the closing stock price. The auto.arima function was used to find the ARIMA model, but other methods are worth considering in future studies. And more efforts are needed to find parameters that provide an optimal model in LSTM.

• 대한지리학회지
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• 제48권2호
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• pp.272-287
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• 2013

본 연구는 부동산 가격 추정을 위해 자주 활용되는 헤도닉 가격모형(Hedonic Pricing Model)에서의 설명변수, 즉 지가형성요인의 선별 중요성에 대해 기술하고, 이러한 지가형성요인 및 그 효과가 시간의 경과에 따라 어떻게 변화하는지 실증적으로 검토하였다. 전주시를 사례 지역으로 하여 17년간 반복 측정된 표준지 공시지가를 분석 대상으로 하였으며, 자료가 가지는 포섭구조(nested structure) 및 종단성(longitudinal characteristics)을 고려하여 3개 수준으로 구성된 다수준모형(multi-level model)을 설정하여 적합 정도를 평가하였다. 지가형성요인은 공시지가 산정시 활용되는 헤도닉 가격모형의 일종인 비준표(比準表)에 포함된 항목을 중심으로 살펴보았다. 분석 결과, 17년간의 지가 변동 추세는 전주시 세부지역별로 상승 또는 하락하는 등 지역마다 다른 추이를 보였으며, 따라서 종단효과의 모델 반영이 필요함이 확인되었다. 또한 일반적으로 중요하다고 여겨지는 지가형성요인 중 유의하지 않은 요인이 발견되었으며, 특정 시점에서 영향력이 상당히 큰 것으로 판명된 지가형성요인도 시간의 경과에 따라 그 영향력이 약해지는가 하면, 반대로 지가에 미치는 영향력이 초기에는 미약하였으나 점차 뚜렷해지는 요인이 파악되었다. 향후 헤도닉 모형 적용시 이러한 지가형성요인의 동태성을 모델의 구성요소로 고려할 경우 보다 정확한 가격 추정이 가능해질 것이다.

• 대한전기학회논문지:전력기술부문A
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• 제52권2호
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• pp.79-89
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• 2003

A research about finding a new electricity load model that is sensitive to the price of electricity is conducted. This new model i5 polynomial type price sensitive electricity consumption model, while former electricity consumption models have exponential terms or statistic terms. The pattern of electricity consumption of each electricity using devices were identified first, then the proportion of the devices at buses or nodes are investigated, finally weighted sum of electricity consumption and the proportion makes the load model or consumption model of electricity at one bus or node. This new model is easy to use in the simulations or calculations of the electricity consumption, because the arithmetic of functions with polynomial terms are easy compared to the functions with transcendental terms.

• 한국콘텐츠학회논문지
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• 제6권6호
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• pp.26-32
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• 2006

주식투자의 대중화, 관심의 증가에 따라 주가예측의 중요성이 증대되고 있다. 주가의 변화는 어떤 경향이나 패턴에 의해 움직인다고 가정할 때, 과거의 주가분석을 통해 이들의 변화를 잘 설명할 수 있는 모델의 구성이 가능할 것이다. 동적인 현상을 반영하는 최적의 모델이 구성된다면 이를 통해 향후의 일정기간의 주가의 운동양태의 예측이 가능할 것이다. 본 연구에서는 주가와 같은 템포랄(temporal) 데이터를 잘 설명할 수 있는 모델결정에 대한 방법론으로서 오토마타 기반의 모델을 가정한다. 모델의 최적 상태 수를 결정하기 위한 기준으로서 베이지안정보기준(BIC : Bayesian Information Criterion) 근사법을 사용한다. 베이지안정보기준의 유효성을 살펴보고 베이지안정보기준을 실제 주가데이터 모델의 상태 수 결정과정에 적용하여 모델을 생성한 후 결정된 모델을 통하여 일정 기간의 일별주가곡선의 운동양태를 예측한다. 실제의 주가곡선에 적용하여 모델의 유효성을 확인하였고 예측 주가곡선의 운동양태가 실제 주가 곡선과 유사함을 확인하였다.

• 한국IT서비스학회지
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• 제19권6호
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• pp.131-144
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• 2020

As the blockchain technology attracts attention, interest in cryptocurrency that is received as a reward is also increasing. Currently, investments and transactions are continuing with the expectation and increasing value of cryptocurrency. Accordingly, prediction for cryptocurrency price has been attempted through artificial intelligence technology and social sentiment analysis. The purpose of this paper is to develop a deep learning ensemble model for predicting the price fluctuations and one-day lag price of cryptocurrency based on the design science research method. This paper intends to perform predictive modeling on Ethereum among cryptocurrencies to make predictions more efficiently and accurately than existing models. Therefore, it collects data for five years related to Ethereum price and performs pre-processing through customized functions. In the model development stage, four LSTM models, which are efficient for time series data processing, are utilized to build an ensemble model with the optimal combination of hyperparameters found in the experimental process. Then, based on the performance evaluation scale, the superiority of the model is evaluated through comparison with other deep learning models. The results of this paper have a practical contribution that can be used as a model that shows high performance and predictive rate for cryptocurrency price prediction and price fluctuations. Besides, it shows academic contribution in that it improves the quality of research by following scientific design research procedures that solve scientific problems and create and evaluate new and innovative products in the field of information systems.

• 농업과학연구
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• 제50권4호
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• pp.629-643
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• 2023

The purpose of this study was to examine the effectiveness and efficiency of a policy by comparing and analyzing the impact of the rice market isolation system and production adjustment system (strategic crops direct payment system that induces the cultivation of other crops instead of rice) on rice supply, rice price, and government's financial expenditure. To achieve this purpose, a rice supply and demand forecasting and policy simulation model was developed in this study using a partial equilibrium model limited to a single item (rice), a dynamic equation model system, and a structural equation system that reflects the casual relationship between variables with economic theory. The rice policy analysis model used a recursive model and not a simultaneous equation model. The policy is distinct from that of previous studies, in which changes in government's policy affected the price of rice during harvest and the lean season before the next harvest, and price changes affected the supply and demand of rice according to the modeling, that is, a more specific policy effect analysis. The analysis showed that the market isolation system increased government's financial expenditure compared to the production adjustment system, suggesting low policy financial efficiency, low policy effectiveness on target, and increased harvest price. In particular, the market isolation system temporarily increased the price during harvest season but decreased the price during the lean season due to an increase in ending stock caused by increased production and government stock. Therefore, a decrease in price during the lean season may decrease annual farm-gate prices, and the reverse seasonal amplitude is expected to intensify.

• 수산경영론집
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• 제32권1호
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• pp.1-14
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• 2001

The research on the price-volume relation in the market is very important because it examines into regular phenomenon revealed by market participants including producers and middlemen. The purpose of this study is to investigate the relationship between price and trading volume in the oyster producing market. In order to accomplish the purpose of this study, the contents of empirical analysis include the time series properties of price and trading volume, the short-term and long-term relationships between price and trading volume, and the determinants of trading volume. The data used in this study correspond to daily price and trading volume covering the time period from January 1998 to April 2001. The empirical results can be summarized as follows : First, price and trading volume follow random walks and they are integrated of order 1. The first difference is necessary for satisfying the stationary conditions. Second, price and trading volume are cointegrated. This long-run relationship is stronger from trading volume to price. Third, error correction model suggests that feedback effect exists in the long-run and that price tends to lead trading volume by about five days in the short run, that is, to be required period by digging, conveying, and peeling oystershell for selling oyster. Fourth, price and price volatility is a determinant of trading volume. In particular, trading volume is a negative function of price. It is believed that the conclusion drawn from this study would provide a useful standard for the policy makers in charge of reducing the oyster price volatility risk caused by trading volume(selling quantities).