• Journal of Convergence for Information Technology
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• v.11 no.2
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• pp.82-89
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• 2021

The objective of this study is to propose a new Glide Path that dynamically adjusts the risky asset inclusion ratio of the Target Date Fund by simultaneously considering the market's forecast volatility as well as the time of investor retirement, and to compare the investment performance with the traditional Target Date Fund. Forecasts of market volatility utilize historical volatility, time series model GARCH volatility, and the volatility index VKOSPI. The investment performance of the new dynamic Glide Path, which considers stock market volatility has been shown to be excellent during the analysis period from 2003 to 2020. In all three volatility prediction models, Sharpe Ratio, an investment performance indicator, is improved with higher returns and lower risks than traditional static Glide Path, which considers only retirement date. The empirical results of this study present the potential for the utilization of the suggested Glide Path in the Target Date Fund management industry as well as retirees.

• Journal of the Korean Solar Energy Society
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• v.36 no.3
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• pp.75-85
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• 2016

This research aims to predict and analyze green building certification market of Korean Peninsula after unification. First, it analyzes prospected unification time period, then it forecasts number of new residential and non-residential buildings to be constructed based on estimated number of residences in short at the time in North Korea. There exists a good chance that North Korea's new building market forms similar to that of South Korea, as unification would thoroughly proceed which would result levels of economic culture social politics in quasi-equal state. Thus, assuming the ratio of residential and non-residential building against population is similar in both Korea's, the number against North Korea's house supplied population can be estimated. Based on the expected numbers in North Korea, number of proceeded Building Energy Conservation Plan, Building Energy Rating Certification, and Green Standard for Energy and Environmental Design (G-SEED) are predicted. The research shows certification market related to green building in united Korean Peninsula to be \660 billion over 10 years. Not only certifications to newly built buildings but also including existing buildings, this market is to grow to a considerable extent. As this would largely influence eco-constructive materials, energy plant/equipment, and other relevant markets as well, it would require to make thorough preparations. In sum, to stabilize green building market even before the unification, the research proposes the necessities of appropriate systems in consideration of North Korea, through in-depth discussions and establishment of technology and policy directions in green building sector, such as building energy management and emission reduction technology.

• The Journal of Natural Sciences
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• v.10 no.1
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• pp.199-208
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• 1998

This study forecasts the trend of ethnic theme through market survey, concentrating on Los Angeles market. First, the background of ethnic theme was examined, and the present situation of shops, department sores, and headquarter was also surveyed. After that, fashion trend suitable for market was suggested by analyzing the life style of consumers through zip code. The results of the study are as follows. The conspicuous trend of '97 F/W retail stores is ethnic. This reaction to complicated modern life, and symbolizes the desirable evaluation on the simpleness of basic life and nature. The model of ethnic design is identified in natural clothing, primitive arts, ethnic culture and African theme. In short, this ethnic fashion is expressed as simpleness, naturalism convenience and freedom. On the other hand, the standard of general department stores such as Broadway and Robinson May which are the headquarter of this trend is to satisfy various consumers with various styles. Ethnic goods from Broadway has not arrived at the top for its introducing step. To elevate sales of these goods, promotion through VMD and suggesting various ethnic goods should be done. Besides, when analyzing the consumers of Beverly center Broadway, the target of these goods are mostly professional young people in their 25-34 and 35-44. The life style of these people emphasizes sophisticated life in aspects such as job-oriented activities, and up-to-date fashion. Especially, image is very important. They want individuality different from others. These images are diversified from simpleness, naiveness to sexy character. Accordingly, suggesting fashion trend satisfying the demand of consumers through market survey will make fashion market create infinite possibilities.

• Management & Information Systems Review
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• v.32 no.1
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• pp.63-85
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• 2013

This study tries to investigate the fundamental implications inherent in inventory asset information(specifically, unexpected inventory investment) by analyzing how the relationship between unexpected inventory investment and future operating performance. And we study how is the response of the stock market participants to the fundamental implications inherent in inventory asset information. Prior papers often assume the efficient market and they view the significant relation between stock prices and financial indicators as evidence of the contribution of such indicators to future earnings. Leading indicators are attracting the market's attention for equity valuation. We study whether one leading indicator (unexpected Inventories) forecasts future earnings, and whether market participants fully reflect the predictive ability when they sets share prices(Mishkin test, 1983). Our empirical results of the study are summarized as follows. Current unexpected inventory investment is negatively associated with future operating performance. Also, our evidence is that the stock market participants overprice the contribution of unexpected inventory investment when predicting future earnings. Furthermore, a hedge strategy that uses the overpricing gives significant future abnormal returns. The overall results help the users of financial reports, researchers of accounting, and the accounting principle setting body.

• International Commerce and Information Review
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• v.16 no.5
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• pp.27-47
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• 2014

Gartner mentioned IoT (Internet of Things) as one of the ten growth engines in the world in 2014. In addition, IoT has been frequently invited as a theme by participants at CES held in the early this year. Gartner predicts that the number of devices connected will reach to 26 billion and a total of economic value added will grow to 1.9 trillion dollars until 2020. The definition of IoT has been arranged in a different way by each institution. Therefore, this study arranged the concept of IoT which has been variously defined and used together with M2M and IoE. Further, forecasts presented by research institutions which stated domestic and foreign market outlook were collected and arranged. As IoT is on the uptrend and is selected as one of the ten growth engines in the world, it was found out how policies on IoT in the US, China, Japan and Korea were established and promoted as well as how recent strategies on IoT of major large companies have been carried out. Lastly, the following countermeasures of our government and companies were discussed.

• STI Policy Review
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• v.1 no.1
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• pp.1-21
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• 2010

To achieve the "low carbon green growth" vision, the first step is securing core technologies. Therefore, S&T policy direction for green technology development is urgently needed. As of 2008, investment in green technology (GT) development hovered around 10% of the government's total R&D budget. Thus, the Korean government developed a plan to increase that percentage to 15%, by 2013. To develop reasonable investment strategies for green technology development, targeted strategies that reflect technology and market changes by green technology area are needed. However, the overall planning and coordination of national GT development is currently split among, approximately, 10 government ministries. To establish an efficient green technology development system, the so-called "Green Technology R&D Council" should be launched in collaboration with the Presidential Committee on Green Growth and the National Science and Technology Council. Furthermore, to build a solid foundation for commercializing the outcomes of GT development projects and promote GT transfer, the government should undertake two initiatives. First, the government should reinforce GT R&D performance management, by establishing a GT R&D performance management and evaluation system. Second, the government should implement the "customized packaged support for promoting green technology business rights and commercialization" and present "e-marketplace for market-oriented green technologies". Creating a pan-ministerial policy for GT development policy would necessitate restructuring the HR(Human Resources) development system, which is currently separated by technology area. Based upon mid/long-term HR supply and demand forecasts, the government should design differentiated HR development projects, continuously evaluate those projects, and reflect the evaluation results in future policy development. Finally, to create new GT-related industries, the "Green TCS (Testing, Certification, and Standards) System" needs to be implemented. For objective evaluation and diffusion of R&D results by green technology area, a common standardization plan for testing, analysis, and measurement, like the "Green TCS", should be developed and integrated.

• Journal of Korea Port Economic Association
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• v.27 no.4
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• pp.1-11
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• 2011

In much the same way as the US Lehman crisis of 2008-2009 severely impacted the European economy through financial market dislocation, a European banking crisis would materially impact the US economy through a generalized increase in global risk aversion. A deepening of the European crisis could very well derail the US economic recovery and have a harmful impact on the Asian economies. This kind of vicious circle could be a bad news to the shipping companies. The purpose of the study is to predict the Baltic Dry Index representing the shipping business during the period of 2012 using the ARIMA-type models. This include the ARIMA and Intervention-ARIMA models. This article introduces the four ARIMA models and six Intervention-ARIMA models. The monthly data cover the period January 2000 through October 2011. The out-of-sample forecasting performance is also calculated. Forecasting performance is measured by three summary statistics: root mean squared percent error, mean absolute percent error and mean percent error. The root mean squared percent errors, however, are somewhat higher than normally expected. This reveals that it is very difficult to predict the BDI The ARIMA-type models show that the shipping market will be bearish in 2012. These pessimistic ex-ante forecasts are supported by the Hodrick-Prescott filtering technique.

• Journal of the Korean Solar Energy Society
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• v.39 no.6
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• pp.113-125
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• 2019

With the opening of the small power brokerage business market in December 2018, the small power trading market has started in Korea. Operators must submit the day-ahead estimates of power output and receive incentives based on its accuracy. Therefore, the accuracy of power generation forecasts is directly affects profits of the operators. The forecasting process for power generation can be divided into two procedure. The first is to forecast solar irradiation and the second is to transform forecasted solar irradiation into power generation. There are two methods for transformation. One is to simulate with physical model, and another is to use regression model. In this study, we found the best-fit regression model by analyzing hourly data of PV output and solar irradiation data during three years for 242 PV plants in Korea. The best model was not a linear model, but a sigmoidal model and specifically a Gompertz model. The combined linear regression and Gompertz curve was proposed because a the curve has non-zero y-intercept. As the result, R² and RMSE between observed data and the curve was significantly reduced.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.55 no.4
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• pp.172-178
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• 2006

In this paper, an advanced demand clustering algorithm which can explore the planned maintenance outage of generators in changed electricity industry is proposed. The major contribution of this paper can be captured in the development of the long-term estimates for the generation availability considering planned maintenance outage. Two conflicting viewpoints, one of which is reliability-focused and the other is economy-focused, are incorporated in the development of estimates of maintenance outage based on the advanced demand clustering algorithm. Based on the advanced clustering algorithm, in each demand cluster, conventional effective outage of generators which conceptually capture maintenance and forced outage of generators, are newly defined in order to properly address the characteristic of the planned maintenance outage in changed electricity markets. First, initial market demand is classified into multiple demand clusters, which are defined by the effective outage rates of generators and by the inherent characteristic of the initial demand. Then, based on the advanced demand clustering algorithm, the planned maintenance outages and corresponding effective outages of generators are reevaluated. Finally, the conventional demand clusters are newly classified in order to reflect the improved effective outages of generation markets. We have found that the revision of the demand clusters can change the number of the initial demand clusters, which cannot be captured in the conventional demand clustering process. Therefore, it can be seen that electricity market situations, which can also be classified into several groups which show similar patterns, can be more accurately clustered. From this the fundamental characteristics of power systems can be more efficiently analyzed, for this advanced classification can be widely applicable to other technical problems in power systems such as generation scheduling, power flow analysis, price forecasts, and so on.

• Journal of Electrical Engineering and Technology
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• v.12 no.6
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• pp.2177-2186
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• 2017

The goal of this paper is to provide the specific forecasting steps and to explain how to design the forecasting architecture and training data sets to forecast very short-term wind power when the numerical weather prediction (NWP) is unavailable, and when the sampling periods of the wind power and training data are different. We forecast the very short-term wind power every 15 minutes starting two hours after receiving the most recent measurements up to 40 hours for a total of 38 hours, without using the NWP data but using the historical weather data. Generally, the NWP works as a predictor and can be converted to wind power forecasts through machine learning-based forecasting algorithms. Without the NWP, we can still build the predictor by shifting the historical weather data and apply the machine learning-based algorithms to the shifted weather data. In this process, the sampling intervals of the weather and wind power data are unified. To verify our approaches, we participated in the 2017 wind power forecasting competition held by the European Energy Market conference and ranked sixth. We have shown that the wind power can be accurately forecasted through the data shifting although the NWP is unavailable.