• Proceedings of the Korea Technology Innovation Society Conference
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• 2001.11a
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• pp.307-337
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• 2001

In this paper, we propose the valuation frame of the IT(Information Technology) ventures using ROV(Real Options Valuation) model. Generally, ROV can comprises the traditional valuation method such as DCF(Discounted Cash Flow), which can measure only the tangible value of a firm from the expected future earnings, in that ROV can additionally measure the intangible value such as the strategic value of a firm in the uncertain environment. We set up the hypothetic IT venture future investment plan and assume that there are a growth option and a switching option consequently along the investment time horizon, which are caused by each characteristics of ventures and IT technologies, especially modularity. In the case that there are several embedded real options in the firm's investment plan in a row, we should apply the compound option pricing model as a real option valuation model in order to consider the value interaction between real options. In an addition, we present the results of optimal investment timing analysis using real options approach and compare them. with those of the original assumed investment timing.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.7
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• pp.1205-1210
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• 2007

Several mechanisms are introduced for the procurement of capacity adequacy. In the competitive electricity market, however, it is a GENCO that makes generation investment decision. A GENCO will invest a new generator when it can get more profit than cost. There requires a model to evaluate profit with respect to a new generation investment. In the view of long-term investment, evaluation of a profit of a generator in the electricity market is quite different from that of short-term operation. In this paper, a new profit-evaluation model is proposed for the long-term generation investment. It can treat the probabilistic characteristics of generators, ie, forced-outage-rates, which affect profit of generators.

• Asian Journal of Business Environment
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• v.6 no.1
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• pp.19-24
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• 2016

Purpose - This paper aims to find and analyze factors that determine the flows of bilateral foreign direct investment in intra-ASEAN. It specifically focuses on the dimension of macro-economic, natural resources, human resources, and the quality of governance. Research design, data, and methodology - Data were collected from 64 bilateral relations between ASEAN nations from 2002 to 2013. Panel gravity model was utilized to find factors that determine the flows of bilateral foreign direct investment. Results - Significant factors were identified that determine the flows of bilateral foreign direct investment: GDP home country, GDP host country, real interest rate, distance, and total natural resources rent. Unexpectedly, natural resources have a negative effect. Conclusions - In a situation of increasing the flow of FDI among the countries of ASEAN, the government should control the interest rates and maintain good relations with nearby countries. The negative effect of total natural resource rents implies that ASEAN countries should not depend on their natural resources to attract foreign investments.

• Convergence Security Journal
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• v.9 no.1
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• pp.39-44
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• 2009

To get legitimacy of a security investment, the analysis of ROI about the security investment is required. In this paper, we suggest a practical quantitative model with considering factors that do decision-making of optimized security investment difficult. This model makes use of the value of a residual risk to decide the best information security solution and considers a corelation of response techniques of the information security solution against each threat to do exact decision-making.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.4
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• pp.855-861
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• 2017

Gordon & Loeb[1] suggested that the optimal level of investment decision of an enterprise is the point that the marginal benefit(MB) of information security investment is equal to the marginal cost(MC). However, many companies suffering from information security incidents are not aware of the fact that they are experiencing information security accidents and can not measure how much they are affected. In this paper, I propose a model of information security investment decision making under the incomplete information situation by modifying the Gordon & Loeb[1] model and compare the differences in investment level. Under the incomplete information situation the expected return from the information security investment tends to be lower than that of actual information security investment, and the level of investment is also less. This shows that if a third party such as the government gives accurate information such as the rate of incidents of information security accidents and the amount of damages, companies can expand their investment in information security.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1997.10a
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• pp.138-141
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• 1997

In this study, a simulation model is developed to analyze the effects of routing and scale-economy of transmission facilities on the traffic network topology and investment cost changes in a metropolitan telephone network. Computational experiments showed that the wide deployment of bifurcated routing in a dual-homing configuration reduces significantly the traffic network connectivity and the investment cost. Its enhanced version, when combined with the subscriber network cost model, can be used as a prototype cost proxy model for figuring out the access charges in a multi-operator environment.

• Journal of Technology Innovation
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• v.11 no.2
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• pp.175-193
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• 2003

The purpose of this study is to examine relationship between public R&D investment and private R&D investment in Korea, and to obtain policy implications of the results. To this end, the author attempts to provide more careful consideration of the causality issues by applying rigorous techniques of Granger causality. Tests for unit roots, co-integration, and Granger causality based on an error-correction model are presented. The existence of bi-directional causality between public R&D investment and private R&D investment is detected. This finding has various implications for policy analysts and forecasters. Increasing private R&D investment requires enormous public R&D investment, though there are many other factors contributing to private R&D investment, and public R&D investment is but one part of it. Thus, this study generates confidence in decisions to invest in public R&D. Moreover, this study lends support to the argument that increase in private R&D investment, ceteris paribus, gives rise to public R&D investment. Increase in private R&D investment results in greater national income to be spent on R&D investment and stimulates further public R&D investment.

• 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 Applied Statistics
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• v.27 no.1
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• pp.123-132
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• 2014

Inflation uncertainty is known to have deleterious effects on facilities investment by disturbing the corporate decision on the opportunity cost of investment. In this paper, we test the validity of this hypothesis in Korea by estimating the inflation uncertainty with both a time-varing parameter model with GARCH disturbances and the relative price volatility and then, estimate the facilities investment equation which includes those uncertainty indicators. The uncertainty indexes estimated by the above-mentioned methods continue to fluctuate even after the inflation rate has dropped dramatically reflecting the structural changes of Korea's economy since the financial crisis in 1997. As a result of estimation of the investment equation by both OLS and GMM, we find the inflation uncertainty has a negative effect on facilities investment with a statistical significance. Moreover, by means of Markov-switching regression model utilized to verify the non-linearity of this relationship, we draw a conclusion that this negative effect of inflation uncertainty heightens asymmetrically during the downturn periods of business cycle.

• The Journal of Information Systems
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• v.32 no.1
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• pp.179-199
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• 2023

Purpose This study builds a prediction model to find stocks that can reach intrinsic value among KOSPI and KOSDAQ-listed companies to improve the stability and profitability of the stock investment. And investment simulations are conducted to verify whether stock investment performance is improved by comparing the prediction model, random stock selection, and the market indexes. Design/methodology/approach Value investment theory and machine learning techniques are applied to build the model. Various experiments find conditions such as the algorithm with the best predictive performance, learning period, and intrinsic value-reaching period. This study selects stocks through the prediction model learned with inventive variables, does not limit the holding period after buying to reach the intrinsic value of the stocks, and targets all KOSPI and KOSDAQ companies. The stock and financial data are collected for 21 years (2001-2021). Findings As a result of the experiment, using the random forest technique, the prediction model's performance was the best with one year of learning period and within one year of the intrinsic value reaching period. As a result of the investment simulation, the cumulative return of the prediction model was up to 1.68 times higher than the random stock selection and 17 times higher than the KOSPI index. The usefulness of the prediction model was confirmed in that the number of intrinsic values reaching the predicted stock was up to 70% higher than the random selection.