• Proceedings of the Korea Technology Innovation Society Conference
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• 2017.05a
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• pp.161-174
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• 2017

최근 들어 기술벤처기업에 대한 투자가 증가하고, 이를 위한 기술신용평가의 역할이 증대하였다. 그러나 금융권에서 바라보는 기술신용평가의 경우, 해당 기업의 신용등급이나 기술(력) 등급평가에 초점을 두어, 대상기술의 사업화 및 수익성 관점을 체계적으로 반영하지 못하는 한계를 지닌다. 따라서, 벤처캐피털(VC)이나 엔젤투자자를 비롯한 금융권에서 대상기술의 수익성 정보를 참조하거나 기술벤처기업 설립시 기술지분을 참고하는 등, 기존 기술이전거래 협상참조용이나 담보 보증용에 널리 이용되던 기술가치평가의 활용범위가 급격히 확대되고 있다. 제조 서비스 분야의 일반 기술 뿐만이 아니라, 바이오 제약 의료 분야 기술에서도 미래 투입되어야 하는 사업화 소요기간 및 비용을 고려하여 기술가치를 산정해야 할 때가 있다. 기존의 현금흐름할인법(DCF법)이 연속된 투자에 대한 고려를 못하거나 기술적용 제품의 상용화 투입비용에 대한 확률적인 속성을 반영하지 못하는 등 한계점을 지니고 있다. 그러나 기술과 투자의 가치는 기회가치로 보고 자원배분을 위한 의사결정 정보를 감안해야 하므로, 실물옵션의 개념을 적용하는 것이 바람직하다고 여겨진다. 흔히 기업가치를 평가할 때 주가의 변동성(volatility) 개념을 도입하여 전일종가 대비 익일시가의 분산값을 활용하기도 한다. 이러한 개념을 기술가치평가에 적용하기 위해서는 '주가의 연속성(상대적 미세한 변화)' 및 '양(+)의 조건'을 고려해야 하는데, 실제 기술가치평가 상의 현금흐름은 사업초기년도 음(-)의 값이 나타나거나 2~3년 내외의 짧은 수익예상기간 하에서는 주가와 같은 변동성을 도출하는데 무리가 있다. 따라서 많은 문헌에서 연구된 바와 같이, 실물옵션 기반의 기술가치 산정을 위한 블랙-숄즈 모형에서 변동성과 기초자산가치, 그리고 사업화비용 간의 관계를 살펴볼 필요가 있다. 아울러 옵션가격결정모형(Option Pricing Model)에서 불확실성을 반영한 기초자산의 현재가치와 사업화비용의 현재가치분이 특정 임계조건 하에서 '옵션행사 포기(NAT; no action taken)' 영역으로 구분되는 지를 수학적으로 도출하고 관찰변수(입력값)에 따른 옵션가치 산출표를 개발하여 제시한다.

• The Korean Journal of Applied Statistics
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• v.22 no.5
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• pp.995-1005
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• 2009

Conditional correlation between financial time series plays an important role in risk management, asset allocation and portfolio selection and therefore diverse efforts for modeling conditional correlations in multivariate-GARCH processes have been made in last two decades. In particular, CCC (cf. Bollerslev, 1990) and DCC(dynamic conditional correlation, cf. Engle, 2002) models have been commonly used since they are relatively parsimonious in the number of parameters involved. This article is concerned with DCC modeling for multivariate GARCH processes in comparison with CCC specification. Various multivariate financial time series are analysed to illustrate possible advantages of DCC over CCC modeling.

• KDI Journal of Economic Policy
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• v.14 no.2
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• pp.189-203
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• 1992

Any money model should address the most important phenomenon of a monetary economy, which is the phenomenon of the rate of return dominance. Even if the holding returns on financial or nonfinancial assets are higher than the rate of return on fiat money holding, which is typically zero, people still hold and use money. In a period of accelerating inflation, number of dominating assets increases continuously, yet people continue to hold and use money. Wallace's (1980) overlapping generations model cannot address the rate of return dominance phenomenon. His model does not capture the mediun of exchange role of fiat money. In this paper, an overlapping types model of fiat money is constructed, in which different types of consumers have different preferences on different types of goods, are endowed with different types of goods, are located at seperated regions, and live for only two periods. In this model, people hold and use money despite the dominating assets, even if inflation accelates. Money in this case serves as a pure medium of exchange, whereas in Wallace's model, money serves as a pure store of value, and money disappears if a dominating asset exists. An interesting feature of the overlapping types model presented in this paper is that money does not provide a cheap approximation to an idealized and efficient real allocation. A monetary economy is always superior to a nonmonetary economy, because money helps overcome the incompleteness of the overlapping types friction. In a monetary economy, however, a pareto optimal allocation cannot always be achieved, because money cannot always overcome the overlapping types friction itself. Therefore, with the criterion of optimality of real allocations, the monetary economy is more optimal than a nonmonetary economy but less optimal than a complete Arrow-Debreu economy. This feature has important implications on macro modelling. Because of the difficulty in introducing money into a macro model in an essential and endogenous manner as in the overlapping types model of this paper, a macro model typically ignores money and studies real allocations without the money factor. The possible inefficiencies of a monetary economy, relative to a complete real Arrow-Debreu economy, may indicate differences in real allocations between the two models.

• Journal of Korea Technology Innovation Society
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• v.20 no.3
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• pp.732-753
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• 2017

Recently, when evaluating the technology values in the fields of biotechnology, pharmaceuticals and medicine, we have needed more to estimate those values in consideration of the period and cost for the commercialization to be put into in future. The existing discounted cash flow (DCF) method has limitations in that it can not consider consecutive investment or does not reflect the probabilistic property of commercialized input cost of technology-applied products. However, since the value of technology and investment should be considered as opportunity value and the information of decision-making for resource allocation should be taken into account, it is regarded desirable to apply the concept of real options, and in order to reflect the characteristics of business model for the target technology into the concept of volatility in terms of stock price which we usually apply to in evaluation of a firm's value, we need to consider 'the continuity of stock price (relatively minor change)' and 'positive condition'. Thus, as discussed in a lot of literature, it is necessary to investigate the relationship among volatility, underlying asset values, and cost of commercialization in the Black-Scholes model for estimating the technology value based on real options. This study is expected to provide more elaborated real options model, by mathematically deriving whether the ratio of the present value of the underlying asset to the present value of the commercialization cost, which reflects the uncertainty in the option pricing model (OPM), is divided into the "no action taken" (NAT) area under certain threshold conditions or not, and also presenting the estimation logic for option values according to the observation variables (or input values).

• The Optical Journal
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• s.143
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• pp.78-85
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• 2013

올해 중소기업 정책자금 지원규모는 3조 8500억 원으로 지난해 3조 3330억 원에서 15.5% 증가한다. 중소기업청과 중소기업진흥공단은 정책자금의 우선순위를 일자리 창출에 두고 민간금융기관을 통해 자금 조달이 어려운 창업자와 기술개발기업에 전체 정책자금의 40.3%인 1조 5500억 원을 배분한다. 이에 창업기업지원자금이 지난해보다 200억 원, 개발기술사업화자금이 420억 원 늘어나며, 정책자금을 지원받은 기업이 일자리를 1명씩 늘릴 때마다 0.1%포인트씩 최대 1%포인트까지 금리를 인하해 일자리 창출 효과를 극대화 한다는 계획이다. 또한 중진공을 통한 직접 대출 비중이 기존 55%에서 70%로 확대되며, 개발기술사업화자금, 수출금융, 소공인 특화자금은 전액 직접대출로 운영되고 운전자금에 대한 보증서부 대출은 폐지된다. 반면 신용대출 규모는 20% 늘어나 중소기업의 담보 부담이 줄어들 전망이다. 변화하는 산업 구조에 맞춰 정책자금 구조도 바뀐다. 담보력이 부족한 창업 및 소기업의 자금 지원을 위해 기계기구, 재고자산, 매출채권의 담보 인정비율을 높인다. 하반기 중에는 지식재산권 담보대출이 새로 도입된다. 별도의 기술가치 평가 모형을 통해 특허기술의 경제적 가치를 평가하고 특허권을 담보로 대출을 시행한다. 자세한 사항 및 정책자금 신청 희망기업은 중소기업진흥공단 홈페이지(www.sbc.or.kr) '정책자금 융자도우미'를 통해 신청요건 및 추천자금 등을 자가진단 후 신청하면 된다.

• Environmental and Resource Economics Review
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• v.18 no.3
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• pp.431-455
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• 2009

This study estimates the WTP for the plan of solving deforestation due to limestone mining and calculates that damage cost using contingent valuation method. As the results of analysing a dichotomous choice CV data, the yearly mean WTP per household for the plan is 5,045 won(95% confidence interval : 3,729~6,360 won) in single bounded CV model and is 4,361 won(95% confidence interval : 3,710~5,012 won) in double bounded CV model. The damage cost of deforestation due to limestone mining can be estimated as 55.3% of WTP for the plan which is assigned to restoring the deforestation area to the original or similar alternative state. The average yearly deforestation cost of 1 ha due to limestone mining is reached 20.90 million won(95% confidence interval : 16.53~25.27 million won). And the asset value of that 1 ha damage is 160.02 million won(95% confidence interval : 126.56~193.49 million won). The fact is found that the damage cost of deforestation using replacement cost method is likely to be underestimated. The total damage cost of deforestation because of limestone mining in 3 cities (Donghae, Samcheok, Yeongwol) is 204.0 billion won(95% confidence interval : 161.4~246.7 billion won) which is composed of 26.5% for Donghae, 28.9% for Samcheok, and 44.6% for Yeongwol according to the damage size of deforestation due to limestone mining in 3 cities.

• International Commerce and Information Review
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• v.3 no.2
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• pp.1-16
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• 2001

This study discusses some theoretical implications for efficient utilization of the global E-commerce in a world of uncertainty by beginning with measures of risk and return for the global E-commerce, and by moving to risk and return for a efficient transaction portfolio of many risky methods of transaction. Decision rules are developed to show how individuals choose optimal transaction portfolios that maximize their expected utility of wealth. First, the individuals will generally want to allocate positive amount to the global E-commerce, which requires that the expected marginal utility of wealth equals zero. Secondly, the optimal transaction portfolio will be determined by finding the point of tangency between the efficient trading line and the hightest indifference curve in the mean-variance plane. Thirdly, if the global E-commerce is positively correlated with wealth, it must have an expected return that is higher than the risk-free transaction methods in order to compensate for its risk. Fourthly, on the other hand, if the global E-commerce is negatively correlated with wealth, it will have an expected return that is less than the risk-free transaction methods. Finally, the valuation of global E-commerce depends on the degree of individual's risk aversion and the covariance between the expected return of total wealth and the return of global E-commerce.

• Korea Real Estate Review
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• v.28 no.2
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• pp.7-20
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• 2018

This paper has statistically analyzed the determining factors that affect office building sale prices by focusing on strata property sales through the hedonic price function. In this study, 1,171 office building transaction cases were analyzed in Seoul from 2000 to 2017. To determine the influence of various factors on office building sale prices, independent variables included factors that represented macroeconomic characteristics, locational characteristics, physical characteristics, and deal characteristics. The analysis of the strata property sales, which is a major concern in this study, showed that strata property sales enjoyed a discount of about 1.56 million won per pyeong out of the entire sales. In terms of the discount rate, strata property sales were at a 12.6% discount compared to entire property sales, so it was found that strata property sales significantly influenced office building selling price. This is due to the fact that the owner of the strata property encounters more difficulties in distributing cost than the sole proprietor in terms of property rights and the exercise of management rights. The results of this study are expected to contribute in securing transparency in transactions and risk management strategies in the future.

• The Journal of Bigdata
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• v.4 no.2
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• pp.159-173
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• 2019

Last-Mile delivery optimization plays a key role in the urban supply chain operation, which is the most expensive and time-consuming and most complicated part of the whole delivery process. The urban consolidation center (UCC) is regarded as a significant asset for supporting customer demand in the last-mile delivery service. It is the key benefit of UCC to improve the load balance of vehicles and to reduce the total traveling distance by finding the better route with the well-organized multi-leg vehicle journey in the urban area. This paper presents the model using multiple scenario analysis integrated with mathematical optimization techniques using Geographic Information System (GIS). The model aims to find the best solution for the distribution network consisted of DC and UCC, which is applied to the case of Ulaanbaatar Mongolia. The proposed methodology integrates two sub-models, location-allocation model and vehicle routing problem. The multiple scenarios devised by selecting locations of UCC are compared considering the general performance and delivery patterns together. It has been adopted to make better decisions the quantitative metrics such as the economic value of capital cost, operating cost, and balance of using available resources. The result of this research may help the manager or public authorities who should design the distribution network for the last mile delivery service optimization using UCC within the urban area.

• Journal of Service Research and Studies
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• v.5 no.1
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• pp.91-103
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• 2015

We examine the information transmission between the KT Spot and the KT Futures Index, the SK Telecom Spot and the SK Telecom Futures Index, based on the returns data offered by the Korea Exchange. The data includes daily return data from 1 January 2012 to 31 December 2014. Utilizing a dynamic analytical tool-the VAR model, Granger Causality test, Impulse Response Function and Variance Decomposition have been implemented. The results of the analysis are as follows. Firstly, results of Granger Causality test suggests the existence of mutual causality the KT Futures Index and the SK Telecom Futures Index precede and have explanatory power the KT Spot and the SK Telecom Spot However the results also identified a greater causality and explanatory power of the KT Spot and the SK Telecom Spot over the KT Futures Index and the SK Telecom Futures Index. Secondly, the results of impulse response function suggest that the KT Futures Index show immediate response to the KT Spot and are influenced by till time 4. From time 2, the impact gradually disappears. Also the SKT Futures Index show immediate response to the SKT Spot and are influenced by till time 4. From time 2, the impact gradually disappears. Lastly, the variance decomposition analysis shows that the changes of return of the KT Spot and SKT Spot are dependent on those of the KT Futures Index and the SK Telecom Futures Index. This implies that returns on the KT Spot and SKT Spot have a significant influence over returns on the KT Futures Index and the SK Telecom Futures Index. It contributes to the understanding of market price formation function through analysis of detached the KT Spot and the KT Futures Index, the SK Telecom Spot and the SK Telecom Futures Index.