• Journal of the Korea Society of Computer and Information
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• v.28 no.2
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• pp.201-207
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• 2023

In this paper, we propose an optimal model for mid to long-term price prediction of agricultural products using LGBM, MLP, LSTM, and GRU to compare and analyze the three strategies of the Multi-Step Time Series. The proposed model is designed to find the optimal combination between the models by selecting methods from various angles. Prior agricultural product price prediction studies have mainly adopted traditional econometric models such as ARIMA and LSTM-type models. In contrast, agricultural product price prediction studies related to Multi-Step Time Series were minimal. In this study, the experiment was conducted by dividing it into two periods according to the degree of volatility of agricultural product prices. As a result of the mid-to-long-term price prediction of three strategies, namely direct, hybrid, and multiple outputs, the hybrid approach showed relatively superior performance. This study academically and practically contributes to mid-to-long term daily price prediction by proposing an effective alternative.

• Industry Promotion Research
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• v.7 no.4
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• pp.97-108
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• 2022

This paper examined the impact of financing structure on the innovation efficiency of SMEs by constructing an econometric model using panel data of SMEs listed on the SME board from 2010 to 2020 as the research sample. The innovation efficiency of SMEs was measured by the Stochastic Frontier Analysis (SFA), the relationship between financing structure and innovation efficiency of SMEs was examined with the help of the Tobit model, and the corresponding heterogeneity analysis was conducted. Finally, the robustness of the model was tested. It was concluded that the effects of debt and equity financing on the quantitative efficiency of innovation were non-linear and mainly showed an inverted "U" shaped relationship. For innovation quality efficiency, bond financing could positively contribute, while equity financing negatively inhibits. Finally, the corresponding advice was given.

• Economic Analysis
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• v.17 no.2
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• pp.27-55
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• 2011

Although many theoretical studies have tried to explain the volatility in financial markets using models of herd behavior, there have been few empirical studies on dynamic herding due to the technical difficulty of detecting herd behavior with time-series data. Thus, this paper theoretically extends a continuous beliefs system belonging to an agent based economic model by introducing a term representing agents'mutual dependence into each agent's utility function and derives a SV(stochastic volatility)-type econometric model. From this model the time-varying herding parameters are efficiently estimated by a Markov chain Monte Carlo method. Using monthly data of KOSPI and DOW, this paper provides some empirical evidences for stronger herding in the Korean stock market than in the U.S. stock market, and further stronger herding after the global financial crisis than before it. More interesting finding is that time-varying herd behavior has weak autocorrelation and the global financial crisis may increase its volatility significantly.

• The KIPS Transactions:PartB
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• v.14B no.7
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• pp.531-540
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• 2007

In this research, we proposed a two-phase hybrid stock price forecasting model with cointegration tests and artificial neural networks. Using not only the related stocks to the target stock but also the past information as input features in neural networks, the new model showed an improved performance in forecasting than that of the usual neural networks. Firstly in order to extract stocks which have long run relationships with the target stock, we made use of Johansen's cointegration test. In stock market, some stocks are apt to vary similarly and these phenomenon can be very informative to forecast the target stock. Johansen's cointegration test provides whether variables are related and whether the relationship is statistically significant. Secondly, we learned the model which includes lagged variables of the target and related stocks in addition to other characteristics of them. Although former research usually did not incorporate those variables, it is well known that most economic time series data are depend on its past value. Also, it is common in econometric literatures to consider lagged values as dependent variables. We implemented a price direction forecasting system for KOSPI index to examine the performance of the proposed model. As the result, our model had 11.29% higher forecasting accuracy on average than the model learned without cointegration test and also showed 10.59% higher on average than the model which randomly selected stocks to make the size of the feature set same as that of the proposed model.

• The Journal of the Korea Contents Association
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• v.15 no.7
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• pp.436-448
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• 2015

This study examined one of the contemporary financial aspects, the level of corporate cash holdings for the firms belonging to the chaebols in the Korean capital markets. Being accompanied by various alternative econometric methodologies such as static and dynamic panel data model, stepwise OLS, and Fama-Macbeth modelm this research extended the preceding Kim's study (2015) in anticipation of validating the results to identify any financial factors which may significantly affect the chaebol firms' cash reserves. Several financial characteristics such as CASHFLOW, MVBV, REINVEST, and AGENCY, were found to be statistically significant factors on the level corporate liquidity, along with CCC as cash conversion cycle in the models. It may be plausible that any outcomes of this study may be applied to enhance the efficiency of financial strategies of the chaebol firms on cash holdings, thereby expediting the development of the domestic capital markets status quo toward the advanced one in the market classification.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.11
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• pp.2238-2249
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• 2015

The purpose of this study is to analyze the relations of innovation and productivity following the introduction of ICT and the effects in the process of innovative investments activity-innovation-productivity, not only by finding causes and effects. For this purpose we conducted surveys of SMEs classified into 7 categories by type of business. To put it concretely, this study was performed to find out the foactors which allow companies to secure competitiveness by enhancing of innovative measures through ICT, and to further analyze the political implications for the development of small and medium-size business by conducting an empirical analysis of the process, from the determination of innovative investments all the way through to production. Analysis model used CDM model using econometric methods such as multiple regression analysis and multinominal logit analysis to produce results. Also we established and analyzed models of innovation investment determinants, innovation determinants and productivity determinants to analyze specifically the relations between ICT and productivity.

• Environmental and Resource Economics Review
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• v.21 no.4
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• pp.947-980
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• 2012

This study analyzes the long-run impacts of climate change on Korean agriculture and economy. We estimate the impacts of climate change on the productivities of major agricultural products including rice, dairy and livestock using both a simulation approach and a semiparametric econometric model. The former predicts a decline in productivity while the latter predicts an increase in productivity due to climate change, especially for rice. A recursive dynamic CGE model is used to analyze the general equilibrium impacts of productivity change under the two different scenarios, derived from the two productivity analysis approaches. The loss of GDP in 2050 is 0.2% or 0.02% of total GDP depending on the scenario. It is shown that the losses in dairy and livestock sectors are larger than that in rice sector, although the losses in those two non-rice sectors have been ignored by most existing works.

• The Journal of Industrial Distribution & Business
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• v.10 no.9
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• pp.53-60
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• 2019

Purpose - The objective of this paper is to discover if there exists a relationship between the economic index and distribution industry index in Korean. Because of the distribution industry boom in the recent years, a lot of interest in the relationship between the economic index and distribution industry index in Korean and the economy has been generated. This article examine on the mutual influence between economic index and distribution industry index in Korean. Research design, data, and methodology - For this purpose, we use the vector-auto regression model, impulse response function and variance decomposition of the economic index and distribution industry index, Granger causality test using weekly data on the economic index and distribution industry price index in korea. The sample period is covering from January 2, 2010 to August 31, 2019. The VAR model can also be linked to cointegration analysis. Cointegration Analysis makes possible to find a mechanism causing x and y to move around a long-run equilibrium (Engle and Granger, 1987). This equilibrium means that external shocks may separate the series temporarily at any particular time, but there will be an overall tendency towards some type of long-run equilibrium. If variables are found to have this tendency they are said to be cointegrated and a long-run relationship between these series is established. These econometric tools have been applied widely into economics and business areas to analyze intertemporal linkages between different time series. Results - This research showed following main results. First, from the basic statistic analysis of the economic index and distribution industry index in Korean, the economic index and the distribution industry index in korea have unit roots. Second, there is at least one cointegration between the economic index and distribution industry index in Korean. Finally, the correlation between of the economic index and the distribution industry index in korea is (+) 0.528876. Conclusions - We find that the distribution industry price index Granger cause the economic index in korea. As a consequence, the distribution industry index affect the economic index in Korean. The distribution industry index to the economic index is stronger than that from the economic index to the distribution industry index.

• Environmental and Resource Economics Review
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• v.24 no.4
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• pp.679-708
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• 2015

Almost all of natural gas demand in Korea is currently met by overseas LNG imports. More than 80% of LNG is imported through the mid to long-term contracts with oil-linked pricing. Despite LNG price estimation provides valuable information with various interested parties, an empirical study as well as an econometric model on LNG price hasn't yet been available in Korea. This paper therefore, aims at analyzing not only whether the long-run equilibrium relationship between oil prices and Korean LNG prices exists but also whether structural change occurred in such relationship. Further, it aims at building a conditional VECM taking account of a structural change. According to the final model, an oil price shock is passed through to the LNG prices in nonlinear and different manner from the past.

• Journal of Energy Engineering
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• v.10 no.3
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• pp.233-242
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• 2001

This paper attempts to analyze the effects of promotion of natural gas vehicles (NGVs) on LNG storage facilities and load patterns, and to verify economic feasibilities of NGVs as a DSM (Demand-Side Management) strategy. For these purpose, we have established an econometric mode. Results from the model indicate that natural gas demand in transportation sector will increase continuously, having a 7.84% share in total natural gas demand in 2014. By this analysis, the increased use of NGVs can result in a decreased requirement on the volume of around 1.3 LNG tanks lower in 2014. Also, it shows that TDRs can be reduced by 0.4 for the city gas and by 0.15 for the total LNG in 2014. As a conclusion, we suggest that the promotion of NGVs may play an efficient role as a DSM strategy, and should be considered as a promising strategy to optimize the investment needs in LNG sector as well as an environmental protection measures. Lastly, we acknowledge that a transportation module in our model is based on a Korean government's NGVs promotion plan, not on a market function.