• Journal of Technology Innovation
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• v.19 no.1
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• pp.1-27
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• 2011

This paper aims to measure and analyze R&D productivities and efficiencies of 17 major OECD countries including Korea over the 1984-2008 period by using the Malmquist Productivity Index and Data Envelopment Analysis, classifying R&D performance into an output and outcome aspects. It also searches the Korea's current status and characteristics in each R&D stage to enhance Total Factor Productivity (TFP) compared with other developed countries. Our major findings are the followings: (i) Korea's productivity index of R&D input vis-a-vis R&D output is very high (13.39% annual growth rate) compared with those of major advanced countries, whereas the annual average of efficiency index is very low (0.33), i.e. Korea's technical efficiency index has risen to 0.83 at the last time series started at 0.10 point and come up to the level of major advanced countries. (ii) the Korea's productivity index of R&D output vis-a-vis R&D outcome is very low (14.02% annual reduction rate) compared with those of major advanced countries, whereas the annual average of efficiency index is very high (0.22), i.e. Korea's integrated frontier technical efficiency index has dropped to 0.057 at the last time series started at 1.00 point and coming up to the level of major advanced countries. (iii) The productivity of R&D input vis-a-vis R&D outcome is positively correlated with that of R&D output vis-a-vis R&D outcome and the growth of R&D input factors. In a nutshell, it implicates that the effort to take advantage of R&D outputs, namely establishing the diffusion and commercialization system of technical knowledge to the level of developed countries, should be strengthened over that on the growth of R&D investment and output for enhancing R&D productivity and efficiency in Korea.

• Journal of the Korean Society of Marine Environment & Safety
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• v.19 no.6
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• pp.612-620
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• 2013

In this study, time series analysis was tried, which is widely applied to demand forecast of diverse fields such as finance, economy, trade, and so on, different from previous regression analysis. Future marine traffic volume was forecasted on the basis of data of the number of ships entering Incheon port from January 1996 to June 2013, through courses of stationarity verification, model identification, coefficient estimation, and diagnostic checking. As a result of prediction January 2014 to December 2015, February has less traffic volume than other months, but January has more traffic volume than other months. Also, it was found out that Incheon port was more proper to ARIMA model than exponential smoothing method and there was a difference of monthly traffic volume according to seasons. The study has a meaning in that future traffic volume was forecasted per month with time series model. Also, it is judged that forecast of future marine traffic volume through time series model will be the more suitable model than prediction of marine traffic volume with previous regression analysis.

• The Korean Journal of Financial Management
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• v.26 no.3
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• pp.139-169
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• 2009

This paper introduces the modified VaR which takes into account the asymmetry and fat-tails of financial asset distribution, and then compares its out-of-sample forecast performance with traditional VaR model such as historical simulation model and Riskmetrics. The empirical tests using stock indices of 6 countries showed that the modified VaR has the best forecast accuracy. At the test of independence, Riskmetrics and GARCH model showed best performances, but the independence was not rejected for the modified VaR. The Monte Carlo simulation using skew t distribution again proved the best forecast performance of the modified VaR. One of many advantages of the modified VaR is that it is appropriate for measuring VaR of the portfolio, because it can reflect not only the linear relationship but also the nonlinear relationship between individual assets of the portfolio through coskewness and cokurtosis. The empirical analysis about decomposing VaR of the portfolio of 6 stock indices confirmed that the component VaR is very useful for the re-allocation of component assets to achieve higher Sharpe ratio and the active risk management.

• Journal of Service Research and Studies
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• v.5 no.2
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• pp.15-24
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• 2015

The trade balance for the information and communications technology (ICT) industries in 2014 have reached 863 hundred million dollars as the main export products such as smart phone and semi-conductor increase, since the ICT industries have played an important role in economic growth in Korea. Until now, the consistent supporting of government and investment of company have been doing with the growth of ICT industries, as a result, Korea marked as the first in the UN electronic government preparing index, and rank 12 in the network preparing index through the policy of national information and basic plan of inter-industry convergence. However, as the unstable international economic circumstances, ICT industries is faced with the stagnation, and then preemptive development of products and services for ICT convergence industries is needed to continually get definite ICT Korea image. In this paper, the ICT convergence industry is analyzed and forecasted. In specific, the international and domestic market for cloud, 3D convergence, and internet of things is diagnosed. The market for ICT convergence industries is predicted to be 3.6 trillion dollar in the world, and 110 trillion won in domestic. From the analytical results for technology and services development, the preemptive supporting of the technology development and policy for the internet of things and 3D convergence industries is required. In addition to, through the future forecasting by socio-tech matrix method, the policy supporting for the ICT convergence area of healthcare, fintech, artificial intelligence, body platform, and human security is needed.

• Journal of the Korea Convergence Society
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• v.12 no.6
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• pp.9-16
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• 2021

In the past, there have been various studies on predicting the stock market by machine learning techniques using stock price data and financial big data. As stock index ETFs that can be traded through HTS and MTS are created, research on predicting stock indices has recently attracted attention. In this paper, machine learning models for KOSPI's up and down predictions are implemented separately. These models are optimized through a grid search of their control parameters. In addition, a hybrid machine learning model that combines individual models is proposed to improve the precision and increase the ETF trading return. The performance of the predictiion models is evaluated by the accuracy and the precision that determines the ETF trading return. The accuracy and precision of the hybrid up prediction model are 72.1 % and 63.8 %, and those of the down prediction model are 79.8% and 64.3%. The precision of the hybrid down prediction model is improved by at least 14.3 % and at most 20.5 %. The hybrid up and down prediction models show an ETF trading return of 10.49%, and 25.91%, respectively. Trading inverse×2 and leverage ETF can increase the return by 1.5 to 2 times. Further research on a down prediction machine learning model is expected to increase the rate of return.

• Journal of the Korean Operations Research and Management Science Society
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• v.38 no.2
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• pp.75-93
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• 2013

In applying Markowitz's portfolio selection model to the stock market, we developed a comprehensive investment decision-making framework including key inputs for portfolio theory (i.e., individual stocks' expected rate of return and covariance) and minimum required expected return. For estimating the key inputs of our decision-making framework, we utilized an exponentially weighted moving average (EWMA) which places more emphasis on recent data than the conventional simple moving average (SMA). We empirically analyzed the investment results of the decision-making framework with the same 15 stocks in Samsung Group Funds found in the Korean stock market between 2007 and 2011. This five-year investment horizon is marked by global financial crises including the U.S. subprime mortgage crisis, the collapse of Lehman Brothers, and the European sovereign-debt crisis. We measure portfolio performance in terms of rate of return, standard deviation of returns, and Sharpe ratio. Results are compared with the following benchmarks : 1) KOSPI, 2) Samsung Group Funds, 3) Talmudic portfolio based on the na$\ddot{i}$ve 1/N rule, and 4) Markowitz's model with SMA. We performed sensitivity analyses on all the input parameters that are necessary for designing an investment decision-making framework : smoothing constant for EWMA, minimum required expected return for the portfolio, and portfolio rebalancing period. In conclusion, appropriate use of the comprehensive investment decision-making framework based on the Markowitz's model integrated with EWMA proves to achieve outstanding performance compared to the benchmarks.

• The Korean Journal of Financial Studies
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• v.8 no.1
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• pp.157-188
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• 2002

본 연구는 우리나라 IPO시장에서 나타나고 있는 초과수익률의 원인을 밝히고자 최근 벤처금융의 중심으로 급부상하고 있는 KOSDAQ시장의 공모 IPO를 대상으로 실증분석을 시도하였다. 연구결과 상장일 표본전체 IPO의 초과수익률(AR1)이 9.91%로 나타났으며, 벤처캐피탈투자 IPO는 5.13%, 비투자 IPO는 13.29%로 나타났다. 상한가의 행진이 종료된 날을 기준으로 한 표본전체 IPO의 초과수익률(AR2)은 30.97%, 벤처캐피탈 투자기업 IPO는 24.34%, 비투자기업 IPO는 34.67%로 나타났다. 초과수익률의 원인을 분석하기 위한 8개의 변수 중 IPO의 수요증감 척도인 KOSDAQ 지수는 초과수익률(AR)과는 양(+)의 관계로, 벤처캐피탈리스트들의 능력 및 가치책정의 행태를 엿볼 수 있는 변수인 본질가치와 공모가액의 차이는 음(-)의 관계로, 사업규모나 자본조달의 크기를 엿볼 수 있는 공모금액의 크기는 양(+)의 관계로 1% 유의수준에서 유의한 것으로 나타났다. 그러나 여타 변수들은 통계적으로 유의성을 확보하지는 못하였으나 초과수익률의 원인이론으로 '신호이론'과 '투기적 거품가설'에 의한 설명이 가능하였으며 분석결과를 다음과 같이 정리할 수 있었다. 첫째, IPO 본질가치에 대한 신뢰와 IPO의 발행규모에 대한 신뢰수준이 통계적으로 유의한 결과로 나타났는바 이러한 결과는 기업가치와 벤처 또는 사업의 계속적 수행 등에 대한 신호역할을 수행하고 있다고 할 수 있으며 상장초기 초과수익률은 주로 이러한 신호역할에 의한 수요집중으로 발생된 결과인 것으로 사료되었다. 둘째, 노련한 벤처캐피탈회사로 선정된 KTB의 투자기업들은 상장 후 4주간의 거래에 있어 AR 평균이 음(-)으로 여타 벤처캐피탈이 투자된 기업보다 손실 폭이 더욱 켰음에도 불구하고 상장일 초과수익률 AR2가 매우 높게 나타나 우리나라 IPO시장에 있어 과민반응(fads) 현상이 존재하고 있는 것으로 분석되었다. 셋째, 벤처캐피탈 투자 IPO의 초과수익률이 상대적으로 낮아 벤처캐피탈 투자여부가 IPO의 저가발행 수준을 축소하고 있어 벤처캐피탈리스트의 제 3자 보증역할이 어느 정도는 수행되고 있는 것으로 분석되었다.

• The Journal of the Korea Contents Association
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• v.11 no.12
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• pp.403-412
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• 2011

The execution of capital market law causes severe competition by promoting restructuring of financial industry. This study analyze efficiency and productivity change of the Korean Non-Life Insurance industry between pre-execution and pre-execution of capital market law using DEA model and Malmquist Index. Additionally, this study finds determinants of efficiency using tobit regression. The main results of this study can by summarized as follows. First, the efficiency with post-execution was increased comparing with pre-execution of capital market law significantly. Second, the productivity with post-execution was increased comparing with pre-execution of capital market law significantly. Third, significant determinants of technical efficiency and pure technical efficiency are weight of life planner. operation rate of assets respectively. And significant determinant of scale efficiency are firm size, operation rate of assets, weight of life planner.

• The Journal of Society for e-Business Studies
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• v.13 no.4
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• pp.125-144
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• 2008

Recently, the main concerns of enterprise management activities is how to strengthen the competitiveness to quickly respond to changes and sustain the growth in business environment. As IT(Information Technology) has become to be viewed as a key driver for the business competitiveness, new paradigms, such as business and IT alignment, IT-driven product/service innovation and so on, are regarded as the hot topic in many industries. However, previous studies related to IT evaluation, which is more critical than any other IT activities, have focused on quantitative IT deployment, utilization and its economical effects. Therefore, this study presents the newly-developed evaluation domains and items based on four pairs of relative concepts in industrial informatization, and their multi-dimensional analysis methodology which explains various types of IT characteristics of enterprises. And finally, pilot tests at 2 companies in financial service sector will be performed in order to verify the practicality of the evaluation system.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.9 no.2
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• pp.15-21
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• 2014

The long memory properties of the hedge ratio for stock and futures have not been systematically investigated by the extant literature. To investigate hedge ratio' long memory, this paper employs a data set including KOSPI200 and S&P500. Coakley, Dollery, and Kellard(2008) employ a data set including a stock index and commodities foreign exchange, and suggested the S&P500 to be a fractionally integrated process. This paper firstly estimates hedge ratios with two dynamic models, BEKK(Bollerslev, Engle, Kroner, and Kraft) and diagonal-BEKK, and tests the long memory of hedge ratios with Geweke and Porter-Hudak(1983)(henceforth GPH) and Lo's modified rescaled adjusted range test by Lo(1991). In empirical results, two hedge ratios based on KOSPI200 and S&P500 show considerably significant long memory behaviours. Thus, such results show the hedge ratios to be stationary and strongly reject the random walk hypothesis on hedge ratios, which violates the efficient market hypothesis.