• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.4
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• pp.63-73
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• 2023

This study explores modern portfolio theory by integrating the Black-Litterman portfolio with time-series clustering, specificially emphasizing K-shape clustering methodology. K-shape clustering enables grouping time-series data effectively, enhancing the ability to plan and manage investments in stock markets when combined with the Black-Litterman portfolio. Based on the patterns of stock markets, the objective is to understand the relationship between past market data and planning future investment strategies through backtesting. Additionally, by examining diverse learning and investment periods, it is identified optimal strategies to boost portfolio returns while efficiently managing associated risks. For comparative analysis, traditional Markowitz portfolio is also assessed in conjunction with clustering techniques utilizing K-Means and K-Means with Dynamic Time Warping. It is suggested that the combination of K-shape and the Black-Litterman model significantly enhances portfolio optimization in the stock market, providing valuable insights for making stable portfolio investment decisions. The achieved sharpe ratio of 0.722 indicates a significantly higher performance when compared to other benchmarks, underlining the effectiveness of the K-shape and Black-Litterman integration in portfolio optimization.

• The Journal of Industrial Distribution & Business
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• v.10 no.6
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• pp.51-58
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• 2019

Purpose - Prior studies reported that the opacity of information caused stock price crash. If managers fail to disclose unfavorable information about the firm over a long period of time, the stock price is overvalued compared to its original value. If the accumulated information reaches a critical point and spreads quickly to the market, the stock price plunges. Information management by management's disclosure policy can cause information uncertainty, which will lead to a plunge in stock prices in the future. Thus, this study aims at examining the impact of disclosure quality on crash risk by focusing on the unfaithful disclosure firms. Research design, data, and methodology - This study covers firms listed on KOSPI and KOSDAQ from 2004 to 2013. Firms excluded from the sample are non-December firms, capital-eroding firms, and financial firms. The financial data used in the research was extracted from the KIS-Value and TS2000 database. Unfaithful disclosure firm designation data was collected from the Korea Exchange's electronic disclosure system (kind.krx.co.kr). Stock crash is measured as a dummy variable that equals one if a firm experiences at least one crash week over the fiscal year, and zero otherwise. Results - Empirical results as to the relation between unfaithful disclosure corporation designation and stock price crashes are as follows: There was a significant positive association between unfaithful disclosure corporation designation and stock price crash. This result supports the hypothesis that firms that have previously exhibited unfaithful disclosure behavior are more likely to suffer stock price plunges due to information asymmetry. Second, stock price crashes due to unfaithful disclosures are more likely to occur in Chaebol firms. Conclusions - While previous studies used estimates as a proxy for information opacity, this study used an objective measure such as unfaithful disclosure corporation designation. The designation by Korea Exchange is an objective evidence that the firm attempted to conceal and distort information in the previous year. The results of this study suggest that capital market investors need to investigate firms' disclosure behaviors.

• 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%.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.469-477
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• 2021

In this paper, the relationship between the profitability level of an enterprise and the credit policy adopted by an enterprise was measured. A sample of industrial firms listed on the stock exchanges of Iraq, Jordan, and Kuwait was analyzed. Five industrial firms were randomly selected from each exchange with a condition of having at least 5 year-activity. The total sample size was 15 industrial firms. The study financial data was imported from the sample firms' websites. The financial data was for the financial year 2017. The Regression Analysis was adopted to measure the impact of trade credit on the profitability of an enterprise using the SPSS software. It was found that the receivable accounts have a proportional relationship with the turnover property rights rate. Similarly, the statistical results showed that the turnover property rights rate increased with an increase in the turnover receivable accounts rate and the percentage of investment in receivable accounts. The influence of trade credit on the enterprise profitability percentage in the Iraq stock exchange, Amman stock exchange, and Boursa Kuwait were 0.938, 0.200, and 0.089, respectively. The results showed that the three secondary assumptions were incorrect, while the zeroth assumption, i.e., trade credit has no influence on profitability, was correct.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.3
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• pp.79-85
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• 2016

In today's fast-paced capitalistic society, a primary concern is whether to invest capital in any way to increase profits. In recent years, many companies have emphasized ethics and practiced corporate social responsibility activities. These activities are not only required to have at the end of the company. Bringing the ultimate goal of profit maximization is one way to contribute to the development of society and the economy. Investors are aware of corporate social responsibility activities and have begun to reflect this in their investments. We studied the behavior of a newly incorporated company's stock price on the KRX SRI Index using a scale that indicates the level of social responsibility for companies in the domestic stock market. Socially responsible investment involves an excellent company that looks out and looks for additional effects on the stock price of imports and improves the reliability of investors through an event study. The results show that the company we examined has a positive impact on the market. This study confirms the hypothesis that additional stock market reaction will occur when superior companies are newly incorporated in the KRX SRI Index and gain investors' trust. The results demonstrate that becoming a newly incorporated corporation in the KRX SRI Index is positive information to investors.

• Journal of Korea Society of Industrial Information Systems
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• v.21 no.5
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• pp.73-83
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• 2016

NAVER provides search frequency data of search terms via its DataLab service (http://datalab.naver.com/). Using this data, this paper examines the relation between the search frequency of firm's name and its future stock returns. Our results show that the search frequency of firm's name is a new investor attention measure, which is different from previously explored attention measures such as extreme returns, turnover, etc. Firms that go through higher search frequency this week tend to have higher returns in the next week. We do not find return reversal in the long run for the firms with higher search frequency. Furthermore, the extent to which search frequency affects stock returns becomes more pronounced following market-wide attention grabbing events. Our results indicate that search frequency incorporates information for future stock returns.

• IE interfaces
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• v.16 no.1
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• pp.111-116
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• 2003

Business integration has been considered as one of the most critical success factors that enable the firms to gain competitive edges. Despite this trend, it has also been found among not a few companies that the activities that should be functionally tied with are performed even independently. In this study, an integrated model of production planning and inventory has been developed. Computerization of the production planning activities is proposed and implemented. We also proposed the reasonable inventory levels of each item using historic data of the items, which are composed of safety stock from the given fill-rate, operating stock from the production patterns, and reserved stock from the production planning. This study has helped the firm to have clearer job definition of the related processes, to tightly control the inventory by setting and tracing the reasonable fill rates for every product, and to quickly respond to the market changes through the computerized production planning process.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.34 no.2
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• pp.35-48
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• 2011

In this paper, we have studied the impact of adopting XBRL (eXtensible Business Reporting Language) on information asymmetry in capital markets with the additional research on the usefulness of XBRL data how to improve the quality of accounting information. From the Kosdaq XBRL service, the samples are selected including 38 adopted companies and the 30 non-adopted companies for the paired analysis. The daily stock return volatility (VOLA) as independent variable and other several controlling variables have been added for the regression analysis to measure the impact on information asymmetry in capital markets. he analytical result indicated that the asymmetry hypotheses that XBRL data will give a significant impact on the capital market and will reduce the volatility, which are expected in the hypotheses. This is the first analytical research on the capital market and its impacts to the capital market from adopting XBRL based accounting information. Additionally, the analysis showed the impacts on the reporting cycle of accounting information and its usefulness of accounting data itself.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.303-304
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• 2021

In the 21st century, as we enter the Fourth Industrial Revolution, research in various fields utilizing big data is being conducted, and innovative and useful technologies are constantly emerging in the world. Among several technologies recently in the big data era, among various fields utilizing some algorithms of artificial intelligence, it shines in the field of finance and is used for pin tech, financial fraud detection and risk management, etc., and recently Even in the booming stock market, it is used for investment prediction and investment factor analysis using artificial intelligence algorithm models. In this paper, we plan to investigate various research cases and investigate trends in how they are used in the stock market through artificial intelligence that utilizes big data.

• Journal of Industrial Convergence
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• v.20 no.11
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• pp.75-83
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• 2022

This study analyzes whether investor sentiment and liquidity explain the momentum phenomenon in the Korean stock market and whether it is a risk factor for the asset pricing model. The empirical analysis used the monthly returns of non-financial companies listed on the stock market during the period 2000-2021. As a result of the analysis, first, it was found that there is a momentum effect in Korea. This is the same result as the previous study, and since 2000, the momentum effect has been accepted as a general phenomenon in the Korean stock market. Second, if we look at the portfolio based on investor sentiment, investor sentiment is influencing momentum. In particular, when investor sentiment is negative, the return on the winner portfolio is high. Third, as a result of the analysis based on liquidity, the momentum effect disappears and a reversal effect appears. Fourth, it was found that investor sentiment and liquidity influence the momentum effect. This is a result of the strong momentum effect in the illiquid stock group with negative investor sentiment. Fifth, as a result of analyzing the effect of each factor on stock returns, it was found that both investor psychology and liquidity factors have a significant impact on returns. The estimated results provide evidence that the inclusion of these two factors in the Carhart four-factor model significantly increases the predictive power of the model. Therefore, it can be said that investor sentiment factors and liquidity factors are important factors in determining stock returns.