• Environmental and Resource Economics Review
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• v.30 no.4
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• pp.535-555
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• 2021

This study empirically analyzes the effects of international oil prices on domestic stock market volatility. The data used for the analysis are 10-minute high-frequency data of the KOSPI index and WTI futures price from January 2, 2015, to July 30, 2021. For using the high-frequency data, a heterogeneous autoregression (HAR) model is employed. The analysis model utilizes the advantages of high frequency data to observe the impact of international oil prices through realized volatility, realized skewness, and kurtosis as well as oil price return. In the estimation, the Box-Cox transformation is applied in consideration of the distribution of realized volatility with high skewness. As a result, it finds that the daily return fluctuation of the WTI price has a statistically significant positive (+) effect on the volatility of the KOSPI return. However, the volatility, skewness, and kurtosis of the WTI return do not appear to affect the volatility of the KOSPI return. This result is believed to be because the volatility of the KOSPI return reflects the daily change in the WTI return, but does not reflect the intraday trading behavior of investors.

• Journal of Korean Society of Rural Planning
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• v.19 no.3
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• pp.25-36
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• 2013

This study aims to perform the economic analysis to the use of solar power facilities in rural villages considering the climate change scenario. IPCC climate change scenarios in the recently adopted the RCP scenarios (RCP8.5, RCP6.5, RCP4.5, RCP2.6) was used. By RCP scenarios, solar radiation, depending on the scenario in 2100, respectively, 3.6%, 2.5%, 1.9%, 1.1% was assumed to increase. From the economic analysis(payback period is 25 year) on 8 points of each province, in all cases of normal data and four RCP scenarios, at all points analyzed were NPV indicate a negative, BC ratio less than 1.0, respectively. In the case of Mokpo, Chunnam RCP8.5, BC ratio were found to be up to a 0.92, followed by 0.89 in the case of RCP8.5 in Jinju, Kyungnam shows, while the minimum was in Jeju. BC ratio is 1.0 or bigger, in order for the normal solar radiation data in Mokpo, Chonnam was the minimum that it takes 37 years. Similarly, in the case of RCP scenarios, 30 years in Mokpo, Chonnam RCP8.5 and 31 years in the cases of Jinju, Kyungnam and Jeonju, Cheonbuk RCP8.5 were analyzed. It was analyzed that RCP8.5 has the highest value. BC analysis models for each of the factors, the results of the sensitivity analysis, the initial installation costs, electricity sales price, discount rate in the order of economy showed higher sensitivity, and the rest factors showed lower changes. Although there are some differences of solar radiation by region, but in Korea most facilities in rural areas, the use of solar power was considered to be economical enough, considering change of several factors with high sensitivity, such as increasing of government subsidies for the solar power installation of the facility, rising oil prices due to a rise in electricity sales price, and a change in discount rate. In particular, when considering climate change scenarios, the use of solar energy for rural areas of the judgment that there was more economical.

• Journal of Climate Change Research
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• v.2 no.2
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• pp.115-131
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• 2011

Out of all the possible actions that can be taken to respond to greenhouse gas reduction, including development of greenhouse gas reduction technology, infrastructure, actions to improve energy saving and efficiency, and offset with carbon emission reductions (CERs), this study shall focus on the investment on CERs. This study will take a look at risks involved with investing in CERs such as UN registration refusal risk and CERs price fluctuation, and will design risk management model which shall be verified. The goal of this paper is to provide optimized CERs investment strategies for different types of investors, such as general trading companies seeking for investment opportunities and financial companies with plans for green products development and investment by preparation for carbon market. It is expected that the global competitiveness of domestic financial companies shall be improved by taking actions on carbon market instead of previous passive response to climate change and that Korea, the number two Carbon Emissions supplier and number one derivatives market in terms of volume, shall be able to lead the worldwide carbon market.

• Journal of Korea Port Economic Association
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• v.35 no.2
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• pp.61-76
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• 2019

The purpose of this study is to use the EGARCH model and Granger causality test to analyze how the change in the BDI affects the Korean stock price volatility. The main analysis results are summarized as follows. First, according to the results of the mean equation, the change in the BDI is significant in large-cap stocks, as well as in the manufacturing, service, and chemistry indexes, but not in others. This implies that the Korean stock market does not respond appropriately to the maritime market situation; further, the increase in demand for raw materials has not led to a real economic recovery. Second, in the result of the variance equation, the coefficient on the change in the BDI is negative(-), and the change in the BDI is significant for all size indexes. Particularly, the change in the BDI has a greater impact on the volatility of small-cap stocks than that of large-cap stocks. The results of the analysis of the sector indexes were statistically significant for the service, financial, construction, and electric and electronics industries, but not for the manufacturing and chemical industries. In particular, the changes in the BDI have the greatest impact on the construction industry. Third, according to the Granger causality test results, the change in the BDI leads the financial industry and construction industry. There is, however, no relationship between the BDI and the other indexes. This shows that change in the shipping freight index can be used to predict the volatility in the Korean stock market. This can help investors and policymakers make better decisions.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.103-128
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• 2021

Recently, investors' interest and the influence of stock-related information dissemination are being considered as significant factors that explain stock returns and volume. Besides, companies that develop, distribute, or utilize innovative new technologies such as artificial intelligence have a problem that it is difficult to accurately predict a company's future stock returns and volatility due to macro-environment and market uncertainty. Market uncertainty is recognized as an obstacle to the activation and spread of artificial intelligence technology, so research is needed to mitigate this. Hence, the purpose of this study is to propose a machine learning model that predicts the volatility of a company's stock price by using the internet search volume of artificial intelligence-related technology keywords as a measure of the interest of investors. To this end, for predicting the stock market, we using the VAR(Vector Auto Regression) and deep neural network LSTM (Long Short-Term Memory). And the stock price prediction performance using keyword search volume is compared according to the technology's social acceptance stage. In addition, we also conduct the analysis of sub-technology of artificial intelligence technology to examine the change in the search volume of detailed technology keywords according to the technology acceptance stage and the effect of interest in specific technology on the stock market forecast. To this end, in this study, the words artificial intelligence, deep learning, machine learning were selected as keywords. Next, we investigated how many keywords each week appeared in online documents for five years from January 1, 2015, to December 31, 2019. The stock price and transaction volume data of KOSDAQ listed companies were also collected and used for analysis. As a result, we found that the keyword search volume for artificial intelligence technology increased as the social acceptance of artificial intelligence technology increased. In particular, starting from AlphaGo Shock, the keyword search volume for artificial intelligence itself and detailed technologies such as machine learning and deep learning appeared to increase. Also, the keyword search volume for artificial intelligence technology increases as the social acceptance stage progresses. It showed high accuracy, and it was confirmed that the acceptance stages showing the best prediction performance were different for each keyword. As a result of stock price prediction based on keyword search volume for each social acceptance stage of artificial intelligence technologies classified in this study, the awareness stage's prediction accuracy was found to be the highest. The prediction accuracy was different according to the keywords used in the stock price prediction model for each social acceptance stage. Therefore, when constructing a stock price prediction model using technology keywords, it is necessary to consider social acceptance of the technology and sub-technology classification. The results of this study provide the following implications. First, to predict the return on investment for companies based on innovative technology, it is most important to capture the recognition stage in which public interest rapidly increases in social acceptance of the technology. Second, the change in keyword search volume and the accuracy of the prediction model varies according to the social acceptance of technology should be considered in developing a Decision Support System for investment such as the big data-based Robo-advisor recently introduced by the financial sector.

• Land and Housing Review
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• v.12 no.3
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• pp.11-26
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• 2021

With the increasing demand for office space, there have been questions on how office rent distribution produces a change in the urban spatial structure in Seoul. The purpose of this paper is to investigate a relative price gradient and to present a time-series model that can quantitatively explain the dynamic changes in the urban spatial structure. The analysis was dealt with office rent above 3,306 m² for the past 10 years from 1Q 2010 to 4Q 2019 within Seoul. A modified repeat sales model was employed. The main findings are briefly summarized as follows. First, according to the estimates of the office price gradient in the three major urban centers of Seoul, the CBD remained at a certain level with little change, while those in the GBD and the YBD continued to increase. This result reveals that the urban form of Seoul has shifted from monocentric to polycentric. This shows that the spatial distribution of companies has gradually accelerated decentralized concentration implying that the business networks have become significant. Second, contrary to small and medium-sized office buildings that have undertaken no change in the gradient, large office buildings have seen an increase in the gradient. The relative price gradients in small and medium-sized buildings were inversely proportional among the CBD, the GBD, and the YBD, implying their heterogeneous submarkets by office rent movements. Presumably, those differences in the submarkets were attributed to investment attraction, industrial competition, and the credit and preference of tenants. The findings are consistent with the hierarchical system identified in the Seoul 2030 Plan as well as the literature about Seoul's urban form. This research claims that the proposed method, based on the modified repeat sales model, is useful in understanding temporal dynamic changes. Moreover, the findings can provide implications for urban growth strategies under rapidly changing market conditions.

• Health Policy and Management
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• v.23 no.2
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• pp.103-111
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• 2013

Seven diagnosis-related groups (DRGs) prospective payment system is going to expand to all hospitals including university hospitals this year. However there are few studies on the change of practice pattern under prospective payment system in the university hospital setting. So This study was intended to predict the practice pattern change after the introduction of 7 DRGs prospective payment system in a university hospital setting. To predict the change of practice pattern, this study used simulation technique. Five hundred and nineteen patients classified as 5 DRGs in a university hospital were selected for simulation. The change of practice pattern were predicted based on clinicians' opinion. We also predicted payment change by service items. Major findings of this study are as follows. First, the total medical payment was reduced by 14.4%. The drug payment change (8.8%) took most of total payment reduction. The followings are the change of treatment material cost (3.2%), the change of laboratory tests cost (1.8%), the change of room charge (0.5%), and other payment change (0.1%), respectively. Second, most of the reduction in total medical payment resulted from the decreased amount of medical services themselves. The transfer of medical services to outpatient setting took up only 4.9% of the total payment reduction. The change of unit price or composition took up 5.5% of the total payment reduction. In this study we found that it is possible to reduce the inpatient services through practice pattern change in university hospital setting. However, it needs to be careful to adjust DRG payment after the reduction of provided services, because most of reduction was not due to service transfer but to service volume reduction. It is desirable to utilize the saving from practice pattern change as incentive to improve quality of care.

• Journal of Fashion Business
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• v.12 no.4
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• pp.28-45
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• 2008

The purpose of this study is to diagnose actual condition of preference of hair-styling, hair-styling techniques, management, grasping a consumer's consciousness, etc with women living in a city. The survey was gotten to a feminine customer who visited the ten of beauty-shops in shopping center. And statistical data about the actual condition of hair-styling preference realities, hair-styling method and style management was entered into the SPSS statistics analysis system. In brief, be as follows by the results of study. There showed significant difference that noted in hair-style information and basis alternative a beauty salon, there were able to know people whose age is from 20's to 40's got mainly an influence of public media very much and from 40's to 50's got mainly an influence of people around them. Basis alternative of a beauty salon showed significant difference to follow age categories. It appeared that introducing from people around them have a effect on the 20's and 30's, and 40's got an influence of convenience of traffic, and 50's got mainly the shortest distance. In an attitude toward a hair style, especially toward hair cut, a case to do hair cut was most a lot of in own selections, and its result was independent of age categories. The reason that wants to give a chance was most a lot of thinking without an age. Preference length of hair cut showed a significant difference according to age. In permanent section, own selections appeared most regardless of age. And in the permanent motive, also, to have a change appeared most regardless of age. And people had a preference natural to role up to setting regardless of age in permanent wave. In hair color section, women whose age is 20's, 30's, 40's had a motive for a change, on the other hand, 50's and their senior had a motive for a gray hair. Women of all over the age almost knew a fashion color, and they had a preference brown color. In a preference way along a hair color kind, there was a significant difference according to age, also. 20's and 30's did mainly 'semi-permanent coating' and 40's and 50's did mainly 'permanent hair color'. In a attitude about a hair-style management, the more age is young, the more a period is long term. And the more age is old, the more the outlay for price of cut is expensive. But, on the contrary, permanent price showed that the more age is young, the more the outlay for price of permanent is expensive. In hair color, the more age is old, the more a period is short and the more price is low.

• Journal of Energy Engineering
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• v.25 no.4
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• pp.37-52
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• 2016

This study attempts to compare the role of the oil refinery industry in the Korean and Japanese national economy using an inter-industry analysis. First of all, the study conducts a comparative analysis on production-inducing effects and value-added creation effects of the oil refinery industry based on demand-driven model. Moreover, we investigate the supply shortage effects and sectoral pervasive effects of price change by using supply-driven model and Leontief price model, respectively. These analyses have been done by specifying the oil refinery industry as not endogenous but exogenous. The results show that1 won of production or investment in the oil refinery industry induces 0.2620 won and 0.6537 won of production in other industries of Korea and Japan, respectively. The former is less than the latter. It also creates 0.0946 won and 0.0536 won of value-added in other industries of Korea and Japan, respectively. The first is larger than the second. The effects of 1 won of supply shortage in oil refinery industry on other industries are computed to be 0.9657 won and 1.4476 won for Korea and Japan, respectively, and thus the former is smaller than the latter. Finally, the pervasive effects of 10% price change in oil refinery industry are estimated to be 0.3819% and 0.3409% in Korea and Japan, respectively, and thus the first is larger than the second.

• Environmental and Resource Economics Review
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• v.21 no.1
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• pp.69-92
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• 2012

This paper analyzed price asymmetry of domestic petroleum products by distribution stage. Analyzing the asymmetry by distribution stage, we can investigate the gap between analysis results and consumers' perception. For the first stage, we analyzed asymmetries between retail prices including tax and the spot prices of crude oil. The results show that retail price increases more quickly in response to the crude oil prices rise than to the crude oil prices fall as consumers' perception. For the second stage, we analyzed asymmetry of international petroleum product prices in Korean Won with the change in the crude oil spot prices. The results show that international petroleum product prices increase higher in response to the crude oil prices increase than to the crude oil prices decrease. For the final stage, we examined the asymmetry of wholesale price and retail price with the change in the international petroleum product prices in Korean Won. The results show that wholesale prices increase more quickly in response to the crude oil prices rise than to the international petroleum product prices fall. The retail prices, however, decrease more quickly in response to the crude oil prices fall than to the international petroleum product prices rise.