• Asia pacific journal of information systems
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• v.26 no.4
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• pp.526-541
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• 2016

This research aims to examine the predictive power of multiple online stock message boards, namely, NAVER Finance and PAXNET, which are the most popular stock message boards in South Korea, in stock market activities. If predictive power exists, we then compare the predictive power of multiple online stock message boards. To accomplish the research purpose, we constructed a panel data set with close price, volatility, Spell out acronyms at first mention.PER, and number of posts in 40 companies in three months, and conducted a panel vector auto-regression analysis. The analysis results showed that the number of posts could predict stock market activities. In NAVER Finance, previous number of posts positively influenced volatility on the day. In PAXNET, previous number of posts positively influenced close price, volatility, and PER on the day. Second, we confirmed a difference in the prediction power for stock market activities between multiple online stock message boards. This research is limited by the fact that it only considered 40 companies and three stock market activities. Nevertheless, we found correlation between online stock message board and stock market activities and provided practical implications. We suggest that investors need to focus on specific online message boards to find interesting stock market activities.

• Journal of the Korea Furniture Society
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• v.14 no.1
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• pp.35-45
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• 2003

It has shown that the investment on the new products have a direct influence on the price of manufactured goods. This brings about a point, which has been a common problem for many Korean enterprises. That is Korean products can only its international competitiveness from the price, not quality. Our industry has shown its movement from producing cheap, low quality products to creating somewhat more advanced and higher qualify products. However the industry cannot avoid the financial burden from the investment. Just like the title of this article, for existing the 3D-MODELING, the 3D-CAD is existed first has immediate effect on the many developing processes, such as planning a product, designing, and producing. The development of the furniture design in the future will be done in the same way as this article presents. This will have a great effect on the overall productivity. (Time, cost, efficiency and etc). The simulation experiment on this article is based on the idea of development of industry, forms the immediate constituent for the prediction related to the production development, marketing and the trend. Which means, this will play an important part where companies achieve satisfaction from the marketing part and the economy.

• The International Journal of Costume Culture
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• v.4 no.1
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• pp.44-60
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• 2001

The purpose of this study is to present suggestions to improve the problems the domestic department stores face by analyzing and comparing the status of the development of PB which is absolutely critical for the specialized domestic department stores to survive, and to search for the future course which may lead to boosting sales and profit by developing the strategic PB products. Selected for this study were atotal of 20 PB's out of domestic as well s foreign PB's in the 4 big department stores. The data were analyzed with SAS package employed as per the by items frequency, percent, mean and standard deviation. From the above study, following viewpoints can be taken into account for the future development of PB ; First, the active will of the excutive is basically necessary for successful development of PB, by relying on long-term investment. Second, the existing mid or low-price goods should be in line with the mid or high price one's development for domestic merchandising with focus on middle or high class society. Third, the stock burden, biggest problem of PB, can be solved by discount policy at optimum prices and success rate of merchandising prediction.

• Korean Management Science Review
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• v.31 no.1
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• pp.17-26
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• 2014

This study presents a new real estate value analysis model considering the changes in the population structure. We propose a new model that takes advantage of the binomial option model one of the techniques of real options and considers the changes in the population structure. The real estate market price data of Seoul city from year 2001 to 2012 were extracted and the correlation analysis between real estate prices and changes in the population structure was performed. The result shows that they have positive correlation with one year time lag. The coefficient between the real estate prices and demographic changes was estimated using the OLS analysis and included in the traditional binomial option model to calculate the value of the property. It is assumed for the future price prediction that real estate invested in Seoul in January, 2013 will be sold within five years. Analysis result shows that the values of real estate in September of 2013 were predicted as 583.5 million won in the new model and as 582.4 million won in the traditional model. This reflects that the new model considering the change of population change gives better realistic performance than the traditional one.

• Geotechnical Engineering
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• v.11 no.2
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• pp.79-98
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• 1995

In the present study an analytical modeling was carried out to predict mobilized shear strength at the interface between the nail and surrounding soils by carefully examining the behavior characteristics of nailed boil excavated walls. Based on the developed model of mobilized shear strength, the method of overall stability analysis of nailed -soil walls was also developed using the Morgentern -Price limit -equilibrium slice method. The developed analytical procedure could predict the behaviors of nailed -soil excavated walls during the successive excavation stages, at the final stage of construction and post -construction stages. To verify the validity of the developed model and method of stability analysis, mobilized tensile forces of nails and overal stability estimated by the developed procedure were compared with test measurements from three nailed -soil experimental walls having different soil conditions. The effect of seepage pressures inside the soil mass was considered in the developed procedure.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.3
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• pp.1474-1480
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• 2013

This study attempted to estimate construction costs in accordance with the resource-based cost estimation (unit cost price) system by diameter for TBM method, and analyzed the direct cost and the total cost. Based on such figures, this study performed a regression analysis and proposed a model for an equation for estimating construction costs. model for the resource-based cost estimation (unit cost price) system classified by diameter for TBM method proposed by this study can be effectively applied to business planning, preliminary investigation, feasibility study, construction cost estimations in the early design stages.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.4
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• pp.103-108
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• 2021

It is difficult to predict an increase or decrease of stock price because of uncertainty. Researches for prediction of stock price using AI technology have been done for a long time. Recently stock buy/sell recommend programs called by Robot Advisor using AI machine learning technology are used. In this paper, to develop a stock buy/sell recommend system using AI technology, an core engine of this system is designed. An analysis and design method of a stock buy/sell recommend system software using AI machine learning technology will be presented by showing user requirement analysis using object-oriented analysis method, flowchart and screen design.

• Journal of Information Technology Services
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• v.21 no.5
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• pp.95-106
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• 2022

Recently, physical examinations have become an important strategy to reduce costs for individuals and society. Pre-physical counseling is important for an effective physical examination. However, incomplete counseling is being conducted because the demand for physical examinations is not predicted. Therefore, in this study, the demand for physical examination was predicted using text mining and stepwise regression. As a result of the analysis, the most recent text data showed a high explanatory power of the demand for physical examination. Also, large amounts of data have high explanatory power. In addition, it was found that the high frequency of the text "health food" reduces the number of health examination customers. And the higher the frequency of the text of the word "food", the lower the number of physical examination customers. However, when the word "wild ginseng" was exposed a lot on Twitter, the number of physical examination customers visiting hospitals increased. In other words, customers consume efficiently by comparing the health examination price with the price of consumer goods. The proposed research framework can help predict demand in other industries.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.01a
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• pp.31-34
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• 2023

주택 매매에 있어서 가격에 대한 예측은 매우 중요하지만, 실거래 발생 전까지는 정확한 가격을 알 수 없다. 그렇기에 주택가격을 예측하는 많은 연구가 진행되어왔다. 주택가격을 결정하는 영향요인은 크게 주택의 내부요인과 주택의 외부 요인으로 구분되는데, 내부적인 요인 (공급면적, 전용면적, 층, 방 개수 등)에 대한 연구가 많이 진행되었다. 하지만 외부적인 요인 (위치 요인, 금융요인 등)에 대한 연구는 미비하였다. 본 연구는 주택 매수자 관점에서 가격 예측 시 외부적인 요인 역시 중요하다고 판단하여 외부요인을 적용하고자 한다. 본 논문에서 제안하는 방법은 다양한 외부요인 중 주택의 위치 정보를 활용하여, 해당 정보 기반으로 도출 가능한 데이터를 추가한다. 또한 이용량에 따른 지하철역 데이터를 추가하여 관련된 여러 영향요인들을 분석 및 적용 후 머신러닝 기반 예측 모델을 생성한다. 생성된 모델들에 주택매매 실거래 데이터를 적용하여 예측 정확도를 비교 후 높은 정확성을 보이는 모델 결과에 주요하게 영향을 끼치는 요인에 관하여 기술한다.

• East Asian Economic Review
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• v.27 no.3
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• pp.213-242
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• 2023

This paper investigates whether the price of cryptocurrency is determined by the US dollar index, the price of investment assets such gold and oil, and the implied volatility of the KOSPI. Overall, the returns on cryptocurrencies are best predicted by the trading volume of the cryptocurrency both in-sample and out-of-sample. The estimates of gold and the dollar index are negative in the return prediction, though they are not significant. The dollar index, gold, and the cryptocurrencies seem to share characteristics which hedging instruments have in common. When investors take notice of the imminent market risks, they increase the demand for one of these assets and thereby increase the returns on the asset. The most notable result in the out-of-sample predictability is the predictability of the returns on value-weighted portfolio by gold. The empirical results show that the restricted model fails to encompass the unrestricted model. Therefore, the unrestricted model is significant in improving out-of-sample predictability of the portfolio returns using gold. From the empirical analyses, we can conclude that in-sample predictability cannot guarantee out-of-sample predictability and vice versa. This may shed light on the disparate results between in-sample and out-of-sample predictability in a large body of previous literature.