• Journal of Korea Society of Digital Industry and Information Management
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• v.6 no.3
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• pp.211-219
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• 2010

This paper designs the dynamic symbol automatic trading system in Korean option market. This system is based on Multichart program which is convenient and efficient system trading tool. But the Multichart has an important restriction which has only one constant symbol per chart. This restriction causes very useful strategies impossible. The proposed design uses global variables, signal chart selection and position order exchange. So an automatic trading system with dynamic symbol works on Multichart program. To verify the proposed system, BS(Buythensell)-SB(Sellthenbuy) strategies are tested which uses the change of open-interest of stock index futures within a day. These strategies buy both call and put option in ATM at start candle and liquidate all at 12 o'clock and then sell both call and put option in ATM at 12 o'clock and also liquidate all at 14:40. From 23 March 2009 to 31 May 2010, 301-trading days, is adopted for experiment. As a result, the average daily profit rate of this simple strategies riches 1.09%. This profit rate is up to eight times of commision price which is 0.15 % per option trade. If the method which raises the profitable rate of wining trade or lower commission than 0.15% is found, these strategies make fascinated lossless trading system which is based on the proposed dynamic symbol automatic trading system.

• Journal of the Korean Operations Research and Management Science Society
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• v.34 no.1
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• pp.1-10
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• 2009

Consumers earn a number of points for every purchase and then they can exchange a specified number of points for a desired reward in a typical loyalty program. The immediate payoff of their effort given as points is not the real reward they actually care about. It is merely an instrument (or medium) which has no value in itself. In a real world, consumers frequently choose the option with a bigger medium even though the economic value of the option is not changed by the medium. We call it 'medium effect.' In this study we explored if the size of medium affects consumers' preferences. For this we controlled the reward options with three types of medium (small, medium, big) and measured the magnitude of preference difference among the three types of reward options. In addition, we manipulated comparability of reward options with wine and gas discount coupon. We confirmed that choosing one of two wines was easier than that of the two gas coupons. 123 respondents were allocated into three experimental groups. In three experimental grounds, the ratios of the focused reward option's medium to the compared reward option's medium were different. For example, the focused reward option has 10 million points whereas the compared reward option has 10 million points for 1 million won purchase amount in the first group. Then each respondent was asked to choose one of two loyalty programs (focused program vs. compared program) in two different conditions (comparability between reward options. easiness vs. difficulty). To compare the medium effects among the experiment conditions we used chi-squares tests. The empirical results show consumer preference increases and then decreases as reward mile-ages/points given according to purchase amount increase. Additionally, they let us know that comparability of alter natives affects change of consumer preference by reward mileages/points.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2008.10a
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• pp.179-190
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• 2008

Consumers earn a number of points for every purchase and then they can exchange a specified number of points for a desired reward in a typical loyalty program. The immediate payoff of their effort given as points is not the real reward they actually care about. It is merely an instrument (or medium) which has no value in itself. In a real world, consumers frequently choose the option with a bigger medium even though the economic value of the option is not changed by the medium. We call it 'medium effect'. In this study we explored if the size of medium affects on consumers' preferences. For this we controlled the reward options with three types of medium (small, medium, big) and measured the magnitude of preference difference among the three types of reward options. In addition, we manipulated comparability of reward options with wine and gas discount coupon. We confirmed that choosing one of two wines was easier than that of the two gas coupons. 164 respondents were allocated into three experimental groups and one control group. In three experimental groups, the ratios of the focused reward option's medium to the compared reward option's medium were different. For example, the focused reward option has 10 million points whereas the compared reward option has 10 million points for 1 million won purchase amount in the first group. Then each respondent was asked to choose one of two loyalty programs (focused program vs. compared program) in two different conditions (comparability between reward options: easiness vs. difficulty). To compare the medium effects among the experiment conditions we used chi-squares tests. The empirical results show the medium effect increases and then decreases as the ratio of reward mileages/points to purchase amount increases. Additionally, they let us know that comparability of alternatives affects on the medium effects depending on the ratio of reward mileages/points to purchase amount.

• Nuclear Engineering and Technology
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• v.55 no.2
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• pp.640-647
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• 2023

Material corrosion in nuclear power plant (NPP) is not controlled only by amine injection but also by ion exchange (IX) which is the best option to remove trace Na⁺. This study was conducted to understand the Na⁺ leakage characteristics of IX beds packed with ethanolamine-form (ETAH-form) and hydrogen-form (H-form) resins in the simulated water-steam cycle in terms of intrinsic behaviors of four kinds of cation-exchange resins through ASTM test and Vanselow mass action modeling. Na⁺ was inappreciably escaped throughout the channel created in resin layer. Na⁺ leakage from IX bed was non-linearly raised because of its decreasing selectivity with increasing Na⁺ capture and with increasing the fraction of ETAH-form resin. Na⁺ did not reach the breakthrough earlier than ETAH⁺ and NH₄⁺ due to the increased selectivity of Na⁺ to the cation-exchange resin (H⁺ < ETAH⁺ < NH₄⁺ ≪ Na⁺) at the feed composition. Na⁺ leakage from the resin bed filled with small particles was decreased due to the enhanced dynamic IX processes, regardless of its low selectivity. Thus, the particle size is a predominant factor among intrinsic properties of IX resin to reduce Na⁺ leakage from the condensate polishing plant (CPP) in NPPs.

• 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.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.25 no.3
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• pp.93-106
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• 2021

In this paper, an efficient hybrid numerical method for solving two-asset option pricing problem is presented based on the Crank-Nicolson and the radial basis function methods. For this purpose, the two-asset Black-Scholes partial differential equation is considered. Also, the convergence of the proposed method are proved and implementation of the proposed hybrid method is specifically studied on Exchange and Call on maximum Rainbow options. In addition, this method is compared to the explicit finite difference method as the benchmark and the results show that the proposed method can achieve a noticeably higher accuracy than the benchmark method at a similar computational time. Furthermore, the stability of the proposed hybrid method is numerically proved by considering the effect of the time step size to the computational accuracy in solving these problems.

• 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 Trauma and Injury
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• v.24 no.2
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• pp.155-158
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• 2011

Mechanical ventilation is usually the treatment of choice for severe respiratory failure associated with trauma. However, in case of severe hypoxia, mechanical ventilation may not be sufficient for gas exchange in lungs. Patients with Acute Respiratory Distress Syndrome (ARDS) undergo difficulties in oxygen and carbon dioxide exchange. Extracorporeal Membrane Oxygenation (ECMO) is the ideal therapeutic option for those patients with severe traumatic injuries. ECMO allows lungs to reserve their functions and decreases further lung injuries while increasing survival rate at the same time. We report two cases of patients with traumatic ARDS and Multiple Organ Failure including compromised heart function. The preservation of lung function was successful using ECMO therapy.

• East Asian Economic Review
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• v.18 no.3
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• pp.301-335
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• 2014

In this paper, we consider a small open economy under the New Keynesian model with unemployment of Gal$\acute{i}$ (2011a, b) to discuss the design of the monetary policy. Our findings can be summarized in three parts. First, even with the existence of unemployment, the optimal policy is to minimize variance of domestic price inflation, wage inflation, and the output gap when both domestic price and wage are sticky. Second, stabilizing unemployment rate is important in reducing the welfare loss incurred by both technology and labor supply shocks. Therefore, introducing the unemployment rate as an another argument into the Taylor-rule type interest rate rule will be welfare-enhancing. Lastly, controlling CPI inflation is the best option when the policy is not allowed to respond to unemployment rate. Once the unemployment rate is controlled, however, stabilizing power of CPI inflation-based Taylor rule is diminished.

• The KSFM Journal of Fluid Machinery
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• v.19 no.6
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• pp.19-25
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• 2016

Anti-icing is important in gas turbines because ice formation on compressor inlet components, especially inlet guide vane, can cause performance degradation and mechanical damages. In general, the compressor bleeding anti-icing system that supplies hot air extracted from the compressor discharge to the engine intake has been used. However, this scheme causes considerable performance drop of gas turbines. A new method is proposed in this study for the anti-icing in combined cycle power plants(CCPP). It is a heat exchange heating method, which utilizes heat sources from the heat recovery steam generator(HRSG). We selected several options for the heat sources such as steam, hot water and exhaust gas. Performance reductions of the CCPP by the various options as well as the usual compressor bleeding method were comparatively analyzed. The results show that the heat exchange heating system would cause a lower performance decrease than the compressor bleeding anti-icing system. Especially, the option of using low pressure hot water is expected to provide the lowest performance reduction.