• Journal of the Korean Society for Railway
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• v.10 no.2 s.39
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• pp.137-145
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• 2007

In traditional financial theory, the discount cash flow model(DCF or NPV) operates as the basic framework for most analyses. In doing valuation analysis, the conventional view is that the net present value(NPV) of a project is the measure of the present value of expected net cash flows. Thus, investing in a positive(negative) NPV project will increase(decrease) firm value. Recently, this framework has come under some fire for failing to consider the options of the managerial flexibilities. Real option valuation(ROV) considers the managerial flexibility to make ongoing decisions regarding the implementation of investment projects and the deployment of real assets. The appeal of the framework is natural given the high degree of uncertainty that firms face in their technology investment decisions. This paper suggests an algorithm for estimating volatility of logarithmic cash flow returns of real assets based on the Black-Sholes option pricing model, the binomial option pricing model, and the Monte Carlo simulation. This paper uses those models to obtain point estimates of real option value with the G7- HSR350X(high-speed train).

• Bulletin of the Korean Mathematical Society
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• v.55 no.4
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• pp.1241-1261
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• 2018

We derive discrete time model of the geometric fractional Brownian motion. It provides numerical pricing scheme of financial derivatives when the market is driven by geometric fractional Brownian motion. With the convergence analysis, we guarantee the convergence of Monte Carlo simulations. The strong convergence rate of our scheme has order H which is Hurst parameter. To obtain our model we need to convert Wick product term of stochastic differential equation into Wick free discrete equation through Malliavin calculus but ours does not include Malliavin derivative term. Finally, we include several numerical experiments for the option pricing.

• Bulletin of the Korean Mathematical Society
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• v.46 no.2
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• pp.209-227
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• 2009

We examine a unified approach of calculating the closed form solutions of option price under stochastic volatility models using stochastic calculus and the Fourier inversion formula. In particular, we review and derive the option pricing formulas under Heston and correlated Stein-Stein models using a systematic and comprehensive approach which were derived individually earlier. We compare the empirical performances of the two stochastic volatility models and the Black-Scholes model in pricing KOSPI 200 index options.

• Asian Journal of Innovation and Policy
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• v.6 no.2
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• pp.225-244
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• 2017

When evaluating the economic value of technology or business project, we need to consider the period and cost for commercialization. Since the discounted cash flow (DCF) method has limitations in that it can not consider consecutive investment or does not reflect the probabilistic property of commercialization cost, we often take it desirable to apply the concept of real options with key metrics of underlying asset value, commercialization cost, and volatility, while regarding the value of technology and investment as the opportunity value. We at this moment provide more elaborated real options model with the effective region of volatility, which reflects the uncertainty in the option pricing model (OPM).

• The Journal of Society for e-Business Studies
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• v.13 no.4
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• pp.49-69
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• 2008

Recently, ubiquitous computing technology becomes available to develop advanced electronic commerce：u-commerce. Hence, it is the very time to perform feasibility analysis in applying ubiquitous computing technology, especially estimating economical value of the on-going technology. Hence, the purpose of this paper is to propose a financial value estimating methodology in performing feasibility test on ubiquitous computing technology. To do so, Black and Scholes model is basically adopted. To show the feasibility if the idea proposed in this paper, actual case study through focused group interview with those who are actually performing on-going ubiquitous computing projects. As the result, we validated the possibility of applying Black-Sholes model to assessing feasibility analysis for ubiquitous technology development with the price of call option, volatility, and the comparison with other similar technologies.

• Bulletin of the Korean Mathematical Society
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• v.33 no.2
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• pp.259-265
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• 1996

The history of option valuation problem goes back to the year 1900 when Louis Bachelier deduced on option valuation formula under the assumption that the price process follows standard Brownian motion. More than 50 years later, the research for a mathematical theory of option valuation was taken up by Samuelson ([6]) and others. This work was brought into focus in the major paper by Black and Scholes ([1]) in which a complete option valuation model was derived on the assumption that the underlying price model is a geometric Brownian motion. THis paper starts with subjects developed mainly in Harrison and Kreps ([4]) and in Harrison and Pliska ([5]). The ideas established in these papers are essential for option valuation problem, and in particularfor the point of view that we take in this paper.

• Journal of Korean Society of Transportation
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• v.35 no.4
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• pp.360-373
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• 2017

The BTO-a projects is the types, which has a demand risk among the type of PPP projects in Korea. When demand risk is realized, private investor encounters financial difficulties due to lower revenue than its expectation and the government may also have a problem in stable infrastructure operation. In this regards, the government has applied various risk sharing policies in response to demand risk. However, the amount of government's risk sharing is the government's contingent liabilities as a result of demand uncertainty, and it fails to be quantified by the conventional NPV method of expressing in the text of the concession agreement. The purpose of this study is to estimate the value of investment risk sharing by the government considering the demand risk in the profit sharing system (BTO-a) introduced in 2015 as one of the demand risk sharing policy. The investment risk sharing will take the form of options in finance. Private investors have the right to claim subsidies from the government when their revenue declines, while the government has the obligation to pay subsidies under certain conditions. In this study, we have established a methodology for estimating the value of investment risk sharing by using the Black - Scholes option pricing model and examined the appropriateness of the results through case studies. As a result of the analysis, the value of investment risk sharing is estimated to be 12 billion won, which is about 4% of the investment cost of the private investment. In other words, it can be seen that the government will invest 12 billion won in financial support by sharing the investment risk. The option value when assuming the traffic volume risk as a random variable from the case studies is derived as an average of 12.2 billion won and a standard deviation of 3.67 billion won. As a result of the cumulative distribution, the option value of the 90% probability interval will be determined within the range of 6.9 to 18.8 billion won. The method proposed in this study is expected to help government and private investors understand the better risk analysis and economic value of better for investment risk sharing under the uncertainty of future demand.

• 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).

• Journal of Korean Institute of Industrial Engineers
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• v.29 no.2
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• pp.126-134
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• 2003

Among a variety of models proposed by so far to calculate the real options value when the investment decision about the underlying project may be delayed, the Black-Scholes and the binomial lattice models have been widely used and discussed by academics and practitioners. However these two models do not provide us with intuition into how it is constructed and what it does really mean. In this paper, we will therefore explore its components and practically more intuitive meaning. With the components explored, we developed the mathematical model to calculate the real options value and thus strategic net present value, based on the opportunity cost concept, for which the investment decision about the underlying project is postponed by one year. We will finally present a short illustrative example for readers better understanding on the model proposed in the paper.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.05a
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• pp.742-745
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• 2004

Most of options pricing theory including Black and Scholes continuous model and Cox, Ross, and Rubinstein(CRR)'s binomial lattice model were developed based on the notion that continually revised risk-free hedges involving options and stock should earn the risk-free interest rate. This notion is valid with the assumption that the investor's attitude toward risk is neutral. In reality, this assumption may be frequently violated. Therefore, Hodder, Mello, and Sick proposed the way to value real options using the risk-adjusted interest rate. However, they did not show how to derive the mathematical expression for it. In this paper, we will clearly present how to obtain the mathematical expression for the risk-adjusted interest rate for real options and demonstrate two numerical examples to show its applicability.