• Journal of Korea Port Economic Association
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• v.38 no.1
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• pp.31-47
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• 2022

While the ship finance industry has long been struggling with diminishing involvements from the private sector, government-run banks have consistently increased their presence in maritime finance. To address such concerns, this research conceptually explores the creation of blockchain technology-driven security token offering (STO) platforms. To suggest a sound platform model, this piece first examines key design principles. Based on the integral perspective on the digital platform, this paper exhibits three core design principles to create a virtuous platform ecosystem, then sets out STO platform design guidelines. This paper further explores an STO platform model by considering conventional ship finance systems and practices in Korea. The STO platform has three main effects; 1) the wider availability of STOs can enlarge both the scope and size of ship finance users, 2) the activation of security token transactions leads to an increase in participation, and 3) possibilities to create complementary innovative financial services can further encourage the participation of private investors. The STO ecosystem may contribute to the shipping, shipbuilding, and ship finance industries by enhancing its attractiveness to the general public and by creating positive externalities for Busan as a maritime finance center.

• Journal of the Korea Society of Computer and Information
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• v.27 no.11
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• pp.147-155
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• 2022

In this study, we developed a system to dynamically balance a daily stock portfolio and performed trading simulations using gradient boosting and genetic algorithms. We collected various stock market data from stocks listed on the KOSPI and KOSDAQ markets, including investor-specific transaction data. Subsequently, we indexed the data as a preprocessing step, and used feature engineering to modify and generate variables for training. First, we experimentally compared the performance of three popular gradient boosting algorithms in terms of accuracy, precision, recall, and F1-score, including XGBoost, LightGBM, and CatBoost. Based on the results, in a second experiment, we used a LightGBM model trained on the collected data along with genetic algorithms to predict and select stocks with a high daily probability of profit. We also conducted simulations of trading during the period of the testing data to analyze the performance of the proposed approach compared with the KOSPI and KOSDAQ indices in terms of the CAGR (Compound Annual Growth Rate), MDD (Maximum Draw Down), Sharpe ratio, and volatility. The results showed that the proposed strategies outperformed those employed by the Korean stock market in terms of all performance metrics. Moreover, our proposed LightGBM model with a genetic algorithm exhibited competitive performance in predicting stock price movements.

• Advanced Industrial SCIence
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• v.2 no.3
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• pp.22-28
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• 2023

In this study, we conducted research on the automated trading of U.S. stocks through a volatility strategy using the Fear and Greed index. Volatility in the stock market is a common phenomenon that can lead to fluctuations in stock prices. Investors can capitalize on this volatility by implementing a strategy based on it, involving the buying and selling of stocks based on their expected level of volatility. The goal of this thesis is to investigate the effectiveness of the volatility strategy in generating profits in the stock market.This study employs a quantitative research methodology using secondary data from the stock market. The dataset comprises daily stock prices and daily volatility measures for the S&P 500 index stocks. Over a five-year period spanning from 2016 to 2020, the stocks were listed on the New York Stock Exchange (NYSE). The strategy involves purchasing stocks from the low volatility group and selling stocks from the high volatility group. The results indicate that the volatility strategy yields positive returns, with an average annual return of 9.2%, compared to the benchmark return of 7.5% for the sample period. Furthermore, the findings demonstrate that the strategy outperforms the benchmark return in four out of the five years within the sample period. Particularly noteworthy is the strategy's performance during periods of high market volatility, such as the COVID-19 pandemic in 2020, where it generated a return of 14.6%, as opposed to the benchmark return of 5.5%.

• Asia Marketing Journal
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• v.11 no.3
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• pp.57-89
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• 2009

This study aims to shed light on the new insights on the cross-buying intentions in the banking industry and suggests an integrated model of the cross-buying intentions. Recently with globalization in the financial sector, financial companies are trying to retain current customers and attract new one by developing various financial products. In South Korea, this trend is especially apparent in the banking sector. Cross-selling of various financial products such as beneficiary certificates, bankasurance and etc. is becoming more important in retaining competitive advantage in Korean banking industry. However, there are few studies which are trying to find out the factors affecting cross-buying intentions and explain their interrelationships comprehensively. Based upon the previous studies, this study finds out the factors affecting cross-buying intentions and classifies them into two dimensions: affective and instrumental. Affective dimension includes trust, satisfaction and commitment. Instrumental dimension includes the factors such as geological convenience, one-stop convenience, professionality, and direct mail. The results from this study are as follow. All the factors in the affective dimension(trust, satisfaction and commitment) have significant impacts on cross-buying intentions. Also all the factors in the instrumental dimension(geological convenience, one-stop convenience, professionality, and DM) significantly affect cross-buying intentions. Some implications of this dissertation are as follow; First, this study identifies the antecedents of cross-buying intentions comprehensively. Second, this paper provides practical guidelines for the banks attempting to intensify cross-selling activities. Third, banks need to develop sophisticated plans which can consolidate the emotional ties with customers through positive service experiences as the affective dimension is important in influencing cross-buying intentions. Finally, regarding the instrumental dimesnion, the implications are: 1) Developing various new financial products in addition to traditional product such as deposits and installment savings for improving customer convenience, 2) Enhancing the professionality of employees by strengthening education programs on numbers of financial products, 3) Increasing cross-buying intentions through the DM.

• Journal of Service Research and Studies
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• v.14 no.2
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• pp.18-36
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• 2024

As interest in ESG has been increased, it is easy to find papers that empirically study that a company's ESG activities have a positive impact on the company's performance. However, research on what ESG activities companies should actually engage in is relatively lacking. Accordingly, this study systematically classifies ESG activities of companies and seeks to provide insight to companies seeking to plan new ESG activities. This study analyzes how Chinese manufacturing companies perform ESG activities based on their dynamic capabilities in the global economy and how they differ in their activities. This study used the ESG annual reports of 151 Chinese manufacturing listed companies on the Shanghai & Shenzhen Stock Exchange and ESG indicators of China Securities Index Company (CSI) as data. This study focused on the following three research questions. The first is to determine whether there are any differences in ESG activities between companies with high ESG scores (TOP-25) and companies with low ESG scores (BOT-25), and the second is to determine whether there are any changes in ESG activities over a 10-year period (2010-2019), focusing only on companies with high ESG scores. The results showed that there was a significant difference in ESG activities between high and low ESG scorers, while tracking the year-to-year change in activities of the top-25 companies did not show any difference in ESG activities. In the third study, social network analysis was conducted on the keywords of E/S/G. Through the co-concurrence matrix technique, we visualized the ESG activities of companies in a four-quadrant graph and set the direction for ESG activities based on this.

• The Korean Journal of Financial Management
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• v.25 no.1
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• pp.1-22
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• 2008

This study is to evaluate, to the extent to, which advanced currency futures and emerging currency futures markets can predict accurately the future spot rate. To this end, Johansen's the maximum-likelihood cointegration method(1988, 1991) is adopted to test the unbiasedness and efficiency hypothesis. Also, this study is to estimate and compare a quantitative measure of relative efficiency as a ratio of the forecast error variance from the best-fitting quasi-error correction model to the forecast error variance of the futures price as predictor of the spot price in advanced currency futures with in emerging currency futures market. Advanced currency futures is British pound and Japan yen. Emerging currency futures includes Korea won, Mexico peso, and Brazil real. The empirical results are summarized as follows : First, the unbiasedness hypothesis is not rejected for Korea won and Japan yen futures exchange rates. This indicates that the emerging currency Korea won and the advanced currency Japan yen futures exchange rates are likely to predict accurately realized spot exchange rate at a maturity date without the trader having to pay a risk premium for the privilege of trading the contract. Second, in emerging currency futures markets, the unbiasedness hypothesis is not rejected for Korea won futures market apart from Mexico peso and Brazil real futures markets. This indicates that in emerging currency futures markets, Korea won futures market is more efficient than Mexico peso and Brazil real futures markets and is likely to predict accurately realized spot exchange rate at a maturity date without risk premium. Third, this findings show that the results of unbiasedness hypothesis tests can provide conflicting finding. according to currency futures class and forecasts horizon period, Fourth, from the best-fitting quasi-error correction model with forecast horizons of 14 days, the findings suggest the Japan yen futures market is 27.06% efficient, the British pound futures market is 26.87% efficient, the Korea won futures market is 20.77% efficient, the Mexico peso futures market is 11.55%, and the Brazil real futures market is 4.45% efficient in the usual order. This indicates that the Korea won-dollar futures market is more efficient than Mexico peso, and Brazil real futures market. It is therefore possible to concludes that the Korea won-dollar currency futures market has relatively high efficiency comparing with Mexico peso and Brazil real futures markets of emerging currency futures markets.

• The Korean Journal of Financial Management
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• v.21 no.2
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• pp.27-63
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• 2004

Since the 1980s, many multinational corporations have been issuing stocks on foreign stock exchanges, not only to enhance their investor base and liquidity, but also to diversify risks. The phenomenon has also been intensified by the rapid financial globalization and securitization trends. The main purpose of this study is to look into the long-run performance of MNCs' cross-listings of stocks on foreign stock exchanges. We use the event study and cross-sectional regression methods. We obtained some interesting empirical results about the long-run effect of cross-listings. First before the listing data the effect of cross-listing is to increase the underlying stock Vice in the local market. It may be caused by expectation of lower risk and cost of capital. However, after the listing data the stock price has been declining, even if it is not significant. Second, we examine the difference in the long-run cross-listing effect, which may be caused by the listing direction. When listing is made from a less developed market to a more developed market, the effect is better than that in the reverse direction. Furthermore, the effect is worse, when the listing company's home country is the U.S. Third, there is a negative relation between CARs and underlying stock liquidity in the local market, So it implies that a firm, whose underlying stocks are very liquid in the local market should carefully value cross-listing based upon the cost and benefit analysis. Last, but not the least we find that the long-un cross-listing effect is better, when a listing firm's ROE is higher.

• Management & Information Systems Review
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• v.37 no.2
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• pp.187-207
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• 2018

This study examines the negative relationship between accounting conservatism and excess executive compensation and examines whether their relationship increases as managerial incentive compensation intensity increases. For this purpose, a total of 2,755 company-years were selected for the analysis of the companies listed on the Korea Stock Exchange from December 2012 to 2016 as the final sample. The results of this study are as follows. First, there is a statistically significant negative relationship between accounting conservatism and manager overpayment. This implies that managers' incentives to distort future cash flow estimates by over booking assets or accounting profits in order to maximize their compensation when manager compensation is linked to firm performance. In this sense, accounting conservatism can reduce opportunistic behavior by restricting managerial accounting choices, which can be interpreted as a reduction in overpayment to managers. Second, we found that the relationship between accounting conservatism and excess executive compensation increases with the incentive compensation for accounting performance. The higher the managerial incentive compensation intensity of accounting performance is, the more likely it is that the manager has the incentive to make earnings adjustments. Therefore, the high level of incentive compensation for accounting performance means that the ex post settling up problem due to over-compensation can become serious. In this case, the higher the managerial incentive compensation intensity for accounting performance, the greater the role and utility of conservatism in manager compensation contracts. This study is based on the fact that it presents empirical evidence on the usefulness of accounting conservatism in managerial compensation contracts theoretically presented by Watts (2003) and the additional basis that conservatism can be used as a useful tool for investment decision.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.4
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• pp.163-174
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• 2017

This study analyzed how Korean firms' recapitalization affects their capital structure decision and firm value. Recapitalization was categorized into three groups according to the influence of the debt to equity ratio: debt ratio-increasing-recapitalization(capital reduction with refund, cash dividend), debt ratio-unchanging-recapitalization (capital reduction without refund, retirement of repurchased stocks), and debt ratio-decreasing-recapitalization(exercise the rights for convertible bonds, bond with stock warrants, exchangeable bonds and stock options). This article highlights how the relationship between the firms' recapitalization and the capital structure decision driven by the change in debt to equity ratio through the recapitalization should affect the firm value. The whole recapitalization sample used for this analysis comprised 22,814 enterprises listed on the Korea Exchange that were analyzed over the 16-year period from 2000 to 2015. To summarize the results of this Panel Data Analysis, firstly, when a firm executes debt ratio-increasing-recapitalization and debt ratio-decreasing-recapitalization at the period of t-1, the debt to equity ratio, which is increased or decreased, should affect the firm's debt capacity in the same period, then, at the period of t, the firm establishes a leverage policy to readjust the debt to equity ratio the other way around. These adjustments of debt-paying-ability from the leverage policy, including the capital structure decision, finally affect the firm value. Secondly, when a firm implements the debt ratio-unchanging-recapitalization in the period of t-1, the debt to equity ratio, which is neutral, should not affect the firm's capital structure decision. But, the firm value is positively affected by the influence of that recapitalization. Conclusively, we acknowledge a firm which carries out the recapitalization balances its capital structure to the optimal level of leverage and that the capital structure decision positively affects the corporate value.

• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.157-177
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• 2022

Investors are trading stocks by keeping a close watch on the order information submitted by domestic and foreign investors in real time through Limit Order Book information, so-called price current provided by securities firms. Will order information released in the Limit Order Book be useful in stock price prediction? This study analyzes whether it is significant as a predictor of future stock price up or down when order imbalances appear as investors' buying and selling orders are concentrated to one side during intra-day trading time. Using classification algorithms, this study improved the prediction accuracy of the order imbalance information on the short-term price up and down trend, that is the closing price up and down of the day. Day trading strategies are proposed using the predicted price trends of the classification algorithms and the trading performances are analyzed through empirical analysis. The 5-minute KOSPI200 Index Futures data were analyzed for 4,564 days from January 19, 2004 to June 30, 2022. The results of the empirical analysis are as follows. First, order imbalance information has a significant impact on the current stock prices. Second, the order imbalance information observed in the early morning has a significant forecasting power on the price trends from the early morning to the market closing time. Third, the Support Vector Machines algorithm showed the highest prediction accuracy on the day's closing price trends using the order imbalance information at 54.1%. Fourth, the order imbalance information measured at an early time of day had higher prediction accuracy than the order imbalance information measured at a later time of day. Fifth, the trading performances of the day trading strategies using the prediction results of the classification algorithms on the price up and down trends were higher than that of the benchmark trading strategy. Sixth, except for the K-Nearest Neighbor algorithm, all investment performances using the classification algorithms showed average higher total profits than that of the benchmark strategy. Seventh, the trading performances using the predictive results of the Logical Regression, Random Forest, Support Vector Machines, and XGBoost algorithms showed higher results than the benchmark strategy in the Sharpe Ratio, which evaluates both profitability and risk. This study has an academic difference from existing studies in that it documented the economic value of the total buy & sell order volume information among the Limit Order Book information. The empirical results of this study are also valuable to the market participants from a trading perspective. In future studies, it is necessary to improve the performance of the trading strategy using more accurate price prediction results by expanding to deep learning models which are actively being studied for predicting stock prices recently.