• 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.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.10a
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• pp.958-961
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• 2002

The optical disk drive is a basic option on the PC now. So the lower price and higher read/write speed goods are now on market. These trends make many difficulties to produce more reliable drives, comparing when they are treated as high price stuff. In mechanical terms, the lower price and higher read/write speed drive make higher vibration and noise, lower stiffness, even severe fracture of cheap and low quality disk, problems. Due to the internal crash of P/U inside of the drive, the failure of drives, inferior drives, increase more and more by the careless transportation and the originated low stiffness parts. This report is the introduction of the FE simple model to decrease the internal P/U crash problems, and the results.

• The Korean Journal of Financial Management
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• v.22 no.1
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• pp.71-91
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• 2005

The object or this paper is to analyze the rollover effect on KOSPI 200 index option prices. Especially we analyze the implied volatilities of the options that became the near maturity options as the old one expired. For this analysis, a panel data of KOSPI 200 Index Option Prices from year 1999 to year 2001 were used, and following results were obtained. First, after controlling for the underlying index returns, strike prices and other pricing factors, the call option prices tend to decrease while the put option prices tend to increase during the week of expiry. Second, if one concentrates on the daily price changes, call option prices tend to go up on Thursday (as the old options expire), and then experience a price decrease on the following day, while the reverse is true for the put options. These results imply that the option prices are affected by some of the market micro-structure effects such as whether the option is the near maturity option. We conjecture that the reason for this is related to the undervaluation of KOSPI 200 futures. The results from this paper have implications on the timing of option trades. If one wants to buy put options, and/or sell call options, he has better off by executing his intended trades before the old options expire. On the other hand, if one wants to buy call options, and/or sell put options, hi has better off by executing his intended trades after the expiry.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.10
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• pp.1423-1431
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• 2022

Volatility is one of the variables that the Black-Scholes model requires for option pricing. It is an unknown variable at the present time, however, since the option price can be observed in the market, implied volatility can be derived from the price of an option at any given point in time and can represent the market's expectation of future volatility. Although volatility in the Black-Scholes model is constant, when calculating implied volatility, it is common to observe a volatility smile which shows that the implied volatility is different depending on the strike prices. We implement supervised learning to target implied volatility by adding V-KOSPI to ease volatility smile. We examine the estimation performance of KOSPI200 index options' implied volatility using various Machine Learning algorithms such as Linear Regression, Tree, Support Vector Machine, KNN and Deep Neural Network. The training accuracy was the highest(99.9%) in Decision Tree model and test accuracy was the highest(96.9%) in Random Forest model.

• Journal of the Korean Data and Information Science Society
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• v.22 no.1
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• pp.37-47
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• 2011

Stock price index option market has various investment strategies that have been developed. Specially, arbitrage strategies are very important to be efficient in option market. The purpose of this study is to improve profit using rough set and Box spread by using past option trading data. Option trading data was based on an actual stock exchange market tick data ranging from 2001 to 2006. Validation process was carried out by transferring the tick data into one-minute intervals. Box spread arbitrage strategies is low risk but low profit. It can be accomplished by back-testing of the existing strategy of the past data and by using rough set, which limit the time line of dealing. This study can make more stable profits with lower risk if control the strategy that can produces a higher profit module compared to that of the same level of risk.

• 한국경영정보학회:학술대회논문집
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• 2008.06a
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• pp.454-471
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• 2008

This study suggests the dynamic pricing model which reveals the organic relationship between ASP (Application Service Provider) price and the related factors, using system dynamics methodology. Basically, we applied the law of supply and demand for analyzing price changes. Then, we deducted ASP price, focusing on fixed cost and variable cost. We also researched the customer's buying behavior according to version differentiation policy. In the version policy, we set up the proposition about customer's satisfaction and willingness-to-pay, using option system. As a result, this research designed the simulation model which analyzes the changes of the sales according to version differentiations and customer's willingness-to-pay. Through this research, we can find effective version differentiation strategies. This paper also found that the larger the number of package, the greater the demand and customer's willingness-to-pay. The increase of the number of package causes the increase of the sales. The increase of the sale is not exactly relative to the number of package. Drawing S-curve, the sales was increased. This dynamic pricing model suggests the ground that the ASP price changes based on the existing version differentiation theory and the demand of customers can affect the changes of the sales. We expect that this model suggests a clear standard of ASP pricing by combining real cases.

• Environmental and Resource Economics Review
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• v.16 no.4
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• pp.763-779
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• 2007

The combined heat-and-power (CHP) plant is recently suggested as an effective resolution in response to recent rising oil prices and the Kyoto Protocol. This research provides a model for economic appraisal to evaluate CHP investment. Real option model is developed to incorporate a case where the investment is irreversible and underlying revenue is stochastic. The analysis shows that power plant capacity more than 40 Gcal makes CHP investment profitable while the results may vary 10 modest level with respect to investment cost, heat sales price and discount rate.

• The Korean Journal of Applied Statistics
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• v.25 no.5
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• pp.757-773
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• 2012

Traditional value at risk(S-VaR) has a difficulity in predicting the future risk of financial asset prices since S-VaR is a backward looking measure based on the historical data of the underlying asset prices. In order to resolve the deficiency of S-VaR, an economic value at risk(E-VaR) using the risk neutral probability distributions is suggested since E-VaR is a forward looking measure based on the option price data. In this study E-VaR is estimated by assuming the generalized gamma distribution(GGD) as risk neutral density function which is implied in the option. The estimated E-VaR with GGD was compared with E-VaR estimates under the Black-Scholes model, two-lognormal mixture distribution, generalized extreme value distribution and S-VaR estimates under the normal distribution and GARCH(1, 1) model, respectively. The option market data of the KOSPI 200 index are used in order to compare the performances of the above VaR estimates. The results of the empirical analysis show that GGD seems to have a tendency to estimate VaR conservatively; however, GGD is superior to other models in the overall sense.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.107-110
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• 2013

Recently, Korea parliament legislated the Low Carbon Green Growth Act (April, 2012) and approved a bill (May, 2012) to start carbon emission trading system in 2015. It means that for the first time, government would regulate the amounts of carbon emission in private entities, and private entities should attain predefined emission reduction goals by implementing clean development mechanism (CDM) project or buy the Certified Emission Reductions (CERs) from the trading market to avoid penalty. Under these circumstances, it is not easy for them to determine when or how to implement the CDM project because the governmental energy policies about the level of governmental subsidies, periods for free emission allocation, etc. are still under discussion and the future price of the CERs is quite uncertain. Thus, this study presents a real-option based model to assess the financial viability of the CDM project which switches bunker-C oil to liquefied natural gas (LNG). The proposed model is expected to assist private entities in establishing the investment strategy for CDM project under uncertain government energy policies.

• Management Science and Financial Engineering
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• v.17 no.2
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• pp.99-129
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• 2011

This paper analytically studies how to choose hedging instrument for firms with steady operating cash flows from value maximization perspective. I derive a formula to determine option's optimal strike that makes hedged cash flow have the best monetary payoff given a hedger's view on the underlying asset. I find that not only the expected mean but also the expected standard deviation of the underlying asset in relation to the forward price and the implied volatility play a crucial role in making optimal hedging decision. Higher moments play a certain part in hedging decision but to a lesser degree.