• Journal of The Korean Digital Architecture Interior Association
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• v.10 no.2
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• pp.5-12
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• 2010

Unlike housing development project that can ensure profit by selling built units, a hotel development depends on long-term business operation to be profitable due to characteristics of service industry. The expected cash flow has substantial uncertainty depending on room occupancy rate and room charge. Thus, even after construction is complete, business risk tends to rise. It is necessary to ensure strategic response to uncertainty in future value of a hotel. The objective of the study is to explore strategic measures to deal with risk and uncertain future value in hotel development project by adopting abandonment option, which is a type of real options. The case in analysis had sevenyears of project period: Two years for construction, and five years for operation; a plan was made to sell the hotel after five years' of operation. For the research purpose, option value ofrecoverable investment amount was estimated, and value of abandonment option was KRW 124.921 billion. When abandonment option is applied, the project value was deemed to be KRW 120.592 billion. Generally, the amount of loss is enormous when a real estate project like a hotel development fails, and therefore, application of option is expected to be an effective measure to leverage uncertainty of a project.

• International conference on construction engineering and project management
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• 2007.03a
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• pp.729-738
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• 2007

The Public Private Partnership/Private Finance Initiative (PPP/PFI) schemes have made the private sector become a major participant involved in the development of infrastructure systems along with the government. Due to more integrated efforts among project participants and longer concession period, PPP/PFI projects are inherently more complex and risky. It is therefore very important to proactively manage the risks involved throughout the project life cycle. Conventional risk management strategies sometimes ignore managerial flexibility in the planning and execution process. This paper starts with a revised risk management framework which incorporates the real option concept. Following the presentation of the framework, a new risk classification is proposed which leads to different ways of structuring options in a project according to the stage of the project life cycle. Finally, the paper closes by discussing other issues concerning option modeling and negotiation.

• Journal of Korea Technology Innovation Society
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• v.3 no.1
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• pp.37-54
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• 2000

본 글에서는 최근 기술가치평가에 적용되고 있는 조건부가치평가법(Contingent Valuation Method) 다속성효용평가법(Multi-attribute Utility Assessment) 그리고 조건부청구권가치평가법(Real Option Pricing Method)의 세가지 가치측정기법들의 특징과 조요 관련 문헌들을 간략하게 정리하여 소개함으로서 관심있는 연구자들에게 유용한 정보를 제공하고자 한다. 소개하는 방법론들은 환경재화의 가치측정기법과 위험도가 높은 에너지프로젝트의 가치평가기법으로 개발된 기법들로서 신기술이 가지는 특징인 외부성 등의 비시장재적 특성과 높은 위험도에따른 투자가치를 반영할 수있어 기술 및 기업의 가치평가 사례연구에 응용할 수있다.

• Journal of Information Technology Applications and Management
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• v.26 no.6
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• pp.119-138
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• 2019

This work examines whether IT managers adopt of real options such as defer, expand, contract, and abandon in order to cope with ERP risks, which include technological risk, relationship risk with SW vendors, economic risk, and security risk. We collect data of logistics firms in Seoul and its suburbs in 2018 to empirically validate the effect of risks upon the adoption of real options. The results suggest that IT managers adopt all 4 options when facing economic risk and adopt contract and abandon options only when facing security risk. Additionally, we find that IT managers prefers expand option and avoid abandon option when they think ERP compatibility is high.

• Proceedings of the Safety Management and Science Conference
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• 2003.11a
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• pp.329-333
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• 2003

This paper reviews differences between the traditional investment evaluation methods and real option approaches. This study considers management flexibility, contingency and volatility from a strategic management perspective. The roles of various real option approaches are discussed.

• Economic and Environmental Geology
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• v.41 no.5
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• pp.551-562
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• 2008

Option pricing model in finance has been applied to price non-financial options, called real options. The real option valuation method is ideally suited to irreversible decision making under uncertainty, including the need to determine the optimal time to act and even change between alternative courses of action as information is collected. Therefore, the real option valuation method is expected to provide a superior and less subjective approach to determining optimal strategies for water resources supply projects, which have been reported to have huge risks due to uncertainties, and investors and policy makers need to build an optimal strategy - when and if to invest - with uncertainties and managerial flexibilities considered.

• Korean Management Science Review
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• v.31 no.3
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• pp.95-111
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• 2014

It is essential to carry out an economic analysis on public water supply projects so that policy makers and water enterprises are aware of the actual value of the project. However, many popular approaches based on discounted cash flow analysis do not capture the uncertainties inherent in cash flow. In order to analyze the economic values of the water supply project of local governments, we utilize real option model, which considers uncertainty in future water price behavior and captures the value of real life flexibility. The real option model is designed to incorporate the option to expand and abandon, and it is applied to a local government case. Furthermore, we assess the project by exploring Luehrman's option space to accommodate the more efficient decision making. The results show that substantial amount of potential value is included in the public water supply service, and the overall value is greater than the value obtained from the discounted cash flow model.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.177-192
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• 2016

Machine learning is a field of artificial intelligence. It refers to an area of computer science related to providing machines the ability to perform their own data analysis, decision making and forecasting. For example, one of the representative machine learning models is artificial neural network, which is a statistical learning algorithm inspired by the neural network structure of biology. In addition, there are other machine learning models such as decision tree model, naive bayes model and SVM(support vector machine) model. Among the machine learning models, we use SVM model in this study because it is mainly used for classification and regression analysis that fits well to our study. The core principle of SVM is to find a reasonable hyperplane that distinguishes different group in the data space. Given information about the data in any two groups, the SVM model judges to which group the new data belongs based on the hyperplane obtained from the given data set. Thus, the more the amount of meaningful data, the better the machine learning ability. In recent years, many financial experts have focused on machine learning, seeing the possibility of combining with machine learning and the financial field where vast amounts of financial data exist. Machine learning techniques have been proved to be powerful in describing the non-stationary and chaotic stock price dynamics. A lot of researches have been successfully conducted on forecasting of stock prices using machine learning algorithms. Recently, financial companies have begun to provide Robo-Advisor service, a compound word of Robot and Advisor, which can perform various financial tasks through advanced algorithms using rapidly changing huge amount of data. Robo-Adviser's main task is to advise the investors about the investor's personal investment propensity and to provide the service to manage the portfolio automatically. In this study, we propose a method of forecasting the Korean volatility index, VKOSPI, using the SVM model, which is one of the machine learning methods, and applying it to real option trading to increase the trading performance. VKOSPI is a measure of the future volatility of the KOSPI 200 index based on KOSPI 200 index option prices. VKOSPI is similar to the VIX index, which is based on S&P 500 option price in the United States. The Korea Exchange(KRX) calculates and announce the real-time VKOSPI index. VKOSPI is the same as the usual volatility and affects the option prices. The direction of VKOSPI and option prices show positive relation regardless of the option type (call and put options with various striking prices). If the volatility increases, all of the call and put option premium increases because the probability of the option's exercise possibility increases. The investor can know the rising value of the option price with respect to the volatility rising value in real time through Vega, a Black-Scholes's measurement index of an option's sensitivity to changes in the volatility. Therefore, accurate forecasting of VKOSPI movements is one of the important factors that can generate profit in option trading. In this study, we verified through real option data that the accurate forecast of VKOSPI is able to make a big profit in real option trading. To the best of our knowledge, there have been no studies on the idea of predicting the direction of VKOSPI based on machine learning and introducing the idea of applying it to actual option trading. In this study predicted daily VKOSPI changes through SVM model and then made intraday option strangle position, which gives profit as option prices reduce, only when VKOSPI is expected to decline during daytime. We analyzed the results and tested whether it is applicable to real option trading based on SVM's prediction. The results showed the prediction accuracy of VKOSPI was 57.83% on average, and the number of position entry times was 43.2 times, which is less than half of the benchmark (100 times). A small number of trading is an indicator of trading efficiency. In addition, the experiment proved that the trading performance was significantly higher than the benchmark.

• Journal of the Korean Operations Research and Management Science Society
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• v.40 no.2
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• pp.43-61
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• 2015

The valuation of patents is very important, since technology competitiveness is crucial for firms to maintain global competitiveness. But, the patent valuation is difficult and challenging because of the uncertainty affecting their returns. Hence, we propose a patent valuation method by incorporating game theory into the real option model, which can not only potentially recognizes the effect of uncertainty on patent value, but also consider investment decision in a competitive market, as a game between firms. With the model, we can consider dynamic strategy involving an option of patent leveraging strategies enabling the firm to switch among compete, cooperate, or wait modes under different demand or competitive advantage condition.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.11
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• pp.5465-5475
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• 2013

In this study, when to invest in real estate abroad, to present a real option in the way of decision-making. Thus, by using the binomial option model of one of the real thing and DCF, we compared the choice of real estate investment in China and South Korea. Research concerns the real estate market of Shanghai and Seoul, Analyzed the data between 2001-2009. Results were calculated NPV investment period (Net Present Value), Seoul appears in 435.44, Shanghai was 398.26. Investment decision by NPV method will select Seoul. However, as a result of calculating the value using the real option, it was found that for Seoul appear in 615.4, Shanghai has been shown to 626.1, and is suitable for investment in Shanghai. Assuming on the basis of this, that it has invested in practice, and compare the results, Seoul is intended for since 2010, real estate prices fell to 2013 currently, damage has occurred, profit's occurred Shanghai. This ensures that when making decisions in real estate investment and to use the real option than the existing DCF is appropriate.