• 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.

• East Asian Economic Review
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• v.21 no.2
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• pp.147-165
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• 2017

This study quantifies the dynamic interrelationship between the KOSPI index return and search query data derived from the Naver DataLab. The empirical estimation using a bivariate GARCH model reveals that negative contemporaneous correlations between the stock return and the search frequency prevail during the sample period. Meanwhile, the search frequency has a negative association with the one-week- ahead stock return but not vice versa. In addition to identifying dynamic correlations, the paper also aims to serve as a test bed in which the existence of profitable trading strategies based on big data is explored. Specifically, the strategy interpreting the heightened investor attention as a negative signal for future returns appears to have been superior to the benchmark strategy in terms of the expected utility over wealth. This paper also demonstrates that the big data-based option trading strategy might be able to beat the market under certain conditions. These results highlight the possibility of big data as a potential source-which has been left largely untapped-for establishing profitable trading strategies as well as developing insights on stock market dynamics.

• The Korean Journal of Financial Management
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• v.24 no.1
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• pp.149-182
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• 2007

This study examines the determinants of the long-run stock price performance of the firms that granted stock options between 1997 and 2002. We divide the sample into the firms run by the owner and those run by the professional manager. If the primary reason for granting stock options is reduction of the agency costs between the manager and shareholders, the effect of stock options is likely to be more pronounced in the firms run by the professional manager. We find that the long-run abnormal returns of the firms run by the professional manager are negatively associated with the shareholdings by the manager and the book-to-market value and are positively associated with the earnings growth and the size of the outstanding stock options. In contrast, the long-run abnormal returns of the firms run by the owner are negatively associated with the cash flows rate and the sales growth rate and are positively associated with the firm size. This is consistent with the argument that the agency costs arising from the conflicts between the manager and shareholders are an important determinant of the post-stock option granting long-run stock price performance only in the firms run by the professional manager. The results also suggest that stock options in the firms run by the owner are likely to be used for the purposes such as additional compensation, a signaling device, a means that reduce the agency costs within firms.

• Management & Information Systems Review
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• v.29 no.1
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• pp.1-23
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• 2010

This study examines the impacts of outside directors' characteristics and compensation on stock performances of KOSDAQ and NASDAQ IPO firms. The results of this study indicated the following interesting results. First, there is no significant relation between outside directors' age and CARs on KOSDAQ firms. while significant positive relation between outside directors' age and CARs on NASDAQ firms. And the elder age group shows a more positive impact on performances compared with the younger age group. Second, there is no relation between outside directors' academic background and CARs for KOSDAQ firms. But We find a significantly positive one for NASDAQ firms. Third, In Relation to outside directors' careers, their professional or CEO careers group have more positive impact on stock performances than gray directors' careers group. Lastly, there is an insignificant negative relation between the outside directors' compensation and CARs for KOSDAQ firms. while there is a positive relative for NASDAQ firms. In particular, there is a significant positive relative between value of stock options and CARs for NASDAQ firms. from the result, I could find out the stock option for outside' directors have a positive influence on firm value.

• Journal of the Korean Operations Research and Management Science Society
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• v.29 no.2
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• pp.45-57
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• 2004

The purpose of this paper is studying the valuation of option prices in Incomplete markets. A market is said to be incomplete if the given traded assets are insufficient to hedge a contingent claim. This situation occurs, for example, when the underlying stock process follows jump-diffusion processes. Due to the jump part, it is impossible to construct a hedging portfolio with stocks and riskless assets. Contrary to the case of a complete market in which only one equivalent martingale measure exists, there are infinite numbers of equivalent martingale measures in an incomplete market. Our research here is focusing on risk minimizing hedging strategy and its associated minimal martingale measure under the jump-diffusion processes. Based on this risk minimizing hedging strategy, we characterize the dynamics of a risky asset and derive the valuation formula for an option price. The main contribution of this paper is to obtain an analytical formula for a European option price under the jump-diffusion processes using the minimal martingale measure.

• Journal of the Korea Society of Computer and Information
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• v.16 no.2
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• pp.267-278
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• 2011

This study examines the relationship among stock options, pay equity, organizational commitment. Employees who received stock options tend to perceive their pay more equitable and the tendency shows a positive relationship among the amount of stock options and the equity perception. Also employees who received stock options perceive greater procedural equity, as they recognize stock options are awarded to many employees. However, the perception of stock options was not significantly associated with organizational commitment, turnover intention, and pay satisfaction. In 2003, the study surveyed 115 employees who received stock options in 10 publicly owned Korean firms that introduced stock option plans. The statistical analysis leads to the conclusions as follows. First, as the number of stock options increases, the receiver tends to perceive that pay system is more distributively equitable. Second, as the number of stock option receivers increases, the employees perceive the pay system more procedurally equitable. Third, stock option payments don't ensure that it improves pay satisfaction, turnover intention, and organizational commitment. This study shows a positive relationship that stock options work favorably in terms of pay equity, but the effect doesn't seem to be widely positive. The reason is that the introduction of stock options in domestic firms has been made only recently after the foreign exchange crisis in the late 1990s. More experiments and design issues should be discussed for the future.

• Asia-Pacific Journal of Business
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• v.12 no.3
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• pp.343-359
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• 2021

Purpose - The purpose of this paper is to investigate the relationship between earnings management and the disclosure effect of share repurchase. In addition, we analyze whether the relationship between earnings management and share repurchase is affected by executive stock options. Design/methodology/approach - We calculate the discretionary accrual amount for the year immediately preceding the share repurchase and the cumulative excess return around the announcement of the share repurchase, and examine the relationship between the two by regression analysis. Findings - We confirmed a negative relationship between discretionary accrual in the year immediately preceding the share repurchase and the market response to the share repurchase disclosure. In particular, it was found that the negative relationship between discretionary accrual and stock price return on share repurchase announcement was found to decrease in companies to which executive stock options were granted. Research implications or Originality - When uncertainties exist in the motives for share repurchase, we find that earnings management and executive stock options can be useful tools for reducing the adverse selection risk inherent in share repurchase announcements.

• Management & Information Systems Review
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• v.30 no.4
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• pp.339-358
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• 2011

This study analyzes whether there are differences in the level of compensation and pay-performance sensitivity between venture firms and non-venture firms listed on KOSDAQ. To test the above mentioned purpose, this study uses 726 firm-year data listed on KOSDAQ from 2006 to 2009. The results are as follow: First, we find that managers' compensation level of venture firms are higher than non-venture firms. Second, pay-stock performance sensitivity is higher than pay-accounting performance sensitivity in venture firms. Overall, because venture firms give a lot of stock-option to managers, compensation level of venture firms is higher than other firms. Also, venture firms set higher pay-stock performance sensitivity than pay-accounting performance sensitivity to mitigate short-sighted decision.

• 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 applied mathematics & informatics
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• v.29 no.5_6
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• pp.1501-1509
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• 2011

In this study, assume that the stock price obeys the stochastic differential equation driven by mixed fractional Brownian motion, and the short rate follows the Vasicek model. Then, the Black-Scholes partial differential equation is held by using fractional Ito formula. Finally, the pricing formulae of the barrier option are obtained by partial differential equation theory. The results of Black-Scholes model are generalized.