• Communications for Statistical Applications and Methods
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• v.22 no.1
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• pp.31-40
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• 2015

This study proposes a mathematical model that can forecast national defense expenditures. The ongoing European debt crisis weighs heavily on markets; consequently, government spending in many countries will be constrained. However, a forecasting model to predict military spending is acutely needed for South Korea because security threats still exist and the estimation of military spending at a reasonable level is closely related to economic growth. This study establishes two models: an Auto-Regressive Moving Average model (ARIMA) based on past military expenditures and Transfer Function model with the Gross Domestic Product (GDP), exchange rate and consumer price index as input time series. The proposed models use defense spending data as of 2012 to create defense expenditure forecasts up to 2025.

• Journal of the Korea Society of Computer and Information
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• v.10 no.2 s.34
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• pp.199-204
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• 2005

Despite the growth of research interest into electronic commerce, there is still little information available on the ways in which an electronic commerce can be successfully developed. This study reports a set of success factors for electronic commerce, specifically some important implications for managers of internet shopping mall area in Korea. In this study it is found that trust on shopping mall and delivery are very important to increase purchase intention of customer. In addition, the result of this study shows that price and ease of use and loading time and error tolerance are very important to increase purchase intention.

• Journal of Korea Port Economic Association
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• v.34 no.3
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• pp.183-200
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• 2018

This study empirically tests the presence of rational bubbles in the ship prices using time series data from October 1996 to April 2017. To detect the existence of ship prices' rational bubbles, we use integration and cointegration tests, which were proposed by Campbell and Shiller(1987) and Diba and Grossman(1988), for circumventing misspecification of ship price model and applying the bubble test to nonstationary time series. The result of integration test supports existence of tanker price's rational bubble. The co-integration test also shows that drybulk ship and containership prices have been overvalued relative to the market fundamental, drybulk and container freight rates, due to non-stationary rational bubbles. These results provide Korean shipping industry and authorities implications that anticyclical ship investment and long-term and steady fleet capacity expansion policy are needed.

• The Korean Journal of Applied Statistics
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• v.29 no.3
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• pp.463-470
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• 2016

In analysing a time series on the frequency domain, the spectral estimator (or periodogram) is a very useful statistic to identify the periods of a time series. However, the spectral estimator is very sensitive in nature to outliers, so that the spectral estimator in terms of M-estimation has been studied by some researchers. Pak (2001) proposed an empirical method to choose a tuning parameter for the Huber's M-estimating function. In this article, we try to implement Pak's estimation proposal in the spectral estimator. We use the Korean housing price index as an example data set for comparing various M-estimating results.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.53 no.7
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• pp.414-419
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• 2004

In TWBP new uncertainty will be increased. Risk management is risen to a important problem. Vesting contract makes market Players trade at fixed price in TWBP early stages. In the case of advanced country, market players manage risk with a future contract. When a risk management method moves from vesting contract to future contract, it may have to use together two contracts for schedule period. In this paper, risk management strategy that use vesting contract and forward contract at the same time is proposed.

• Journal of the Korean Data and Information Science Society
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• v.25 no.3
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• pp.513-522
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• 2014

Using the assumption that the price of a stock follows a geometric Brownian motion with constant volatility, Black and Scholes (BS) derived a formula that gives the price of a European call option on the stock as a function of the stock price, the strike price, the time to maturity, the risk-free interest rate, the dividend rate paid by the stock, and the volatility of the stock's return. However, implied volatilities of BS method tend to depend on the stock prices and the time to maturity in practice. To address this shortcoming, we estimate the implied volatility function as a function of the strike priceand the time to maturity for data consisting of the daily prices for KOSPI200 call options from January 2007 to May 2009 using support vector regression (SVR), the multiple additive regression trees (MART) algorithm, and ordinary least squaress (OLS) regression. In conclusion, use of MART or SVR in the BS pricing model reduced both RMSE and MAE, compared to the OLS-based BS pricing model.

• Child Health Nursing Research
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• v.8 no.3
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• pp.313-321
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• 2002

We would like to suggest the guideline of use of materials of sexual education for adolescent in school by examining the status of use of materials and by evaluating the video materials frequently used. Survey was done by enquetes on status of use of materials of sexual education from school nurses in 190 primary, 44 middle and 50 high schools in Seoul, Kyonggi-do and Kangwon-do from August 1999 to February 2000. The frequently used 84 videotapes were evaluated on their contents. As for the status of use, 99.3% of subjected schools possessed the materials for sexual education. Decision of purchase was determined according to the review of contents (92.6%). Information about materials was received by the advertisement in newspapers or broadcasting (46.1%) or recommendation of peer teacher (32.4%). Videotape was most frequently used (64.1%) rather than books or CD. Teachers concerns on the materials were the educational content according to developmental stage of students (41.9%), content provoking interest (33.5%) and concrete guide for teacher (10.6%). As for the evaluation of the contents of videotapes, a subject of education was not described out of 46.6%. Videotape producer were mostly the Government-affiliated institutes or non-profit organizations (86.8%). The year of production was indicated from 41.7%. Running time range of 21-30 minutes was highest (55.9%). The price was marked in only one videotape. Subjects of contents were general sexual education (34.5%), sexual violence or sexual harassment (21.4%), pregnancy and contraception (14.2%) and AIDS and sexually transmitted diseases (8.3%) and dating and adolescent change (4. 8%), and etc (11.9 %). According to above results, we suggested that materials for sexual education should be completed with a description on the subjected group, summary of content, information on the tape producer, year of production, running time and sale price.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.4
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• pp.515-526
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• 2014

In this study, the 'preservation of Jeonju Hanok Village Improvement Project' in earnest in promoting itself as the official land price changes in Jeonju Hanok Village and surrounding area thereby affect land prices to some extent in order to identify the time series analysis, t-black dispersion analysis showed the following results were obtained. First, time series analysis, and the Hanok Village, but the average official land price rises, and the area has been stead ilyrising. Second, the time series of the Official price year-over-year change in the average rate of the Hanok Village(+)rising, and the area is a gentle rise sooner or later (+)is expected to be an increase in conversion. Third, the number of tourists visiting Jeonju Hanok Village and sharply increased since 2008, was. Fourth, in order to use local official land price rises in the commercial area of highest priority that requires strategy was analyzed.

• Journal of Korea Entertainment Industry Association
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• v.15 no.5
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• pp.99-113
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• 2021

This study to verify the influence of the macroeconomic factors to sportainment industry and also to find the value of use. For this, 'Dow Jones Industrial Average (DJIA)', 'West Texas intermediate (WTI)', and 'Gold Price (GP)' were selected from macroeconomic factors, and the 'Stock Price' of NIKE and Adidas for sportainment industry factor. The transaction data for 20 years (5,285 trade days) were analyzed through a two-step extraction process. Durbin-Watson regression analysis was performed to prove the influence and predict. From these analyses, the first, the Macroeconomics factors were found to have a significant effect on the sportainment industry. The second, each different levels of regression equations were found by the time setting, the environmental characteristics of each time period, and mutual relation between factors. Finally, it was found that the regression equation between specific period can be used for the future prediction in sportainment industry.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.2
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• pp.204-208
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• 2018

In this paper, we proposed and evaluated the time series deep learning prediction model for learning fluctuation pattern of stock price. Recurrent neural networks, which can store previous information in the hidden layer, are suitable for the stock price prediction model, which is time series data. In order to maintain the long - term dependency by solving the gradient vanish problem in the recurrent neural network, we use LSTM with small memory inside the recurrent neural network. Furthermore, we proposed the stock price prediction model using bidirectional LSTM recurrent neural network in which the hidden layer is added in the reverse direction of the data flow for solving the limitation of the tendency of learning only based on the immediately preceding pattern of the recurrent neural network. In this experiment, we used the Tensorflow to learn the proposed stock price prediction model with stock price and trading volume input. In order to evaluate the performance of the stock price prediction, the mean square root error between the real stock price and the predicted stock price was obtained. As a result, the stock price prediction model using bidirectional LSTM recurrent neural network has improved prediction accuracy compared with unidirectional LSTM recurrent neural network.