• Journal of Korean Institute of Industrial Engineers
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• v.33 no.4
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• pp.410-418
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• 2007

This article suggests the methods to investigate adverse movement across global stock markets arising from insolvency of subprime mortgage in U.S. Our application deals with asymptotic tail dependence of daily stock index returns (KOSPI, DJIA, Shanghai Composite) of three countries; Korea, U.S., and China, over specific period via extreme value theory and copula functions. Daily stock index returns among three countries show higher extremal dependence during the period exposed to systematic shock. We confirm that extreme value theory and copula functions have potential to well describe the extreme dependence between three countries' daily stock index returns.

• Journal of Distribution Science
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• v.13 no.9
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• pp.37-45
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• 2015

Purpose - This paper's aim is to investigate whether or not gross profitability explains the cross-sectional variation of the stock returns in the Korean stock market. Gross profitability is an alternative profitability measure proposed by Novy-Marx in 2013 to predict cross-sectional variation of stock returns in the US. He shows that the gross profitability adds explanatory power to the Fama-French 3 factor model. Interestingly, gross profitability is negatively correlated with the book-to-market ratio. By confirming the gross profitability premium in the Korean stock market, we may provide some implications regarding the well-known value premium. In addition, our empirical results may provide opportunities for the fund distribution industry to promote brand new styles of funds. Research design, data, and methodology - For our empirical analysis, we collect monthly market prices of all the companies listed on the Korea Composite Stock Price Index (KOSPI) of the Korea Exchanges (KRX). Our sample period covers July1994 to December2014. The data from the company financial statementsare provided by the financial information company WISEfn. First, using Fama-Macbeth cross-sectional regression, we investigate the relation between gross profitability and stock return performance. For robustness in analyzing the performance of the gross profitability strategy, we consider value weighted portfolio returns as well as equally weighted portfolio returns. Next, using Fama-French 3 factor models, we examine whether or not the gross profitability strategy generates excess returns when firmsize and the book-to-market ratio are controlled. Finally, we analyze the effect of firm size and the book-to-market ratio on the gross profitability strategy. Results - First, through the Fama-MacBeth cross-sectional regression, we show that gross profitability has almost the same explanatory power as the book-to-market ratio in explaining the cross-sectional variation of the Korean stock market. Second, we find evidence that gross profitability is a statistically significant variable for explaining cross-sectional stock returns when the size and the value effect are controlled. Third, we show that gross profitability, which is positively correlated with stock returns and firm size, is negatively correlated with the book-to-market ratio. From the perspective of portfolio management, our results imply that since the gross profitability strategy is a distinctive growth strategy, value strategies can be improved by hedging with the gross profitability strategy. Conclusions - Our empirical results confirm the existence of a gross profitability premium in the Korean stock market. From the perspective of the fund distribution industry, the gross profitability portfolio is worthy of attention. Since the value strategy portfolio returns are negatively correlated with the gross profitability strategy portfolio returns, by mixing both portfolios, investors could be better off without additional risk. However, the profitable firms are dissimilar from the value firms (high book-to-market ratio firms); therefore, an alternative factor model including gross profitability may help us understand the economic implications of the well-known anomalies such as value premium, momentum, and low volatility. We reserve these topics for future research.

• Korean Business Review
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• v.22 no.1
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• pp.27-44
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• 2009

This paper compares the accounting standards for stock option of Japan and Korea. Especially, tire setting process of accounting standards for stock option, accounting methods and disclosures for stock option in two countries are analyzed. The results provide that two countries shaw different characteristics in accounting standards for stock option. First, in Japan, acquired services are reported as compensation costs and capital adjustments. On the other hand, in Korea, in case of cash-settled share- based payment transactions, acquired services are reported as compensation costs and capital adjustments, but in case of equity-settled share- based payment transactions, acquired services are reported as compensation costs and debt. Second, when tire stock option rights are abandoned, they are reported as extraordinary items in Japan and are reported as other surplus in Korea. Third, though both countries do not choose specific stock option pricing model, Japan prefers Black-Sholes Model and Korea regards binomial model as proper model.

• Asia pacific journal of information systems
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• v.30 no.1
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• pp.31-52
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• 2020

Stock markets are popular investment avenues to people who plan to receive premium returns compared to other financial instruments, but they are highly volatile and risky due to the complex financial dynamics and poor understanding of the market forces involved in the price determination. A system that can forecast, predict the stock prices and automatically create a portfolio of top performing stocks is of great value to individual investors who do not have sufficient knowledge to understand the complex dynamics involved in evaluating and predicting stock prices. In this paper the authors propose a Stock prediction, Portfolio Generation and Selection model based on Machine learning algorithms, Artificial neural networks (ANNs) are used for stock price prediction, Mathematical and Statistical techniques are used for Portfolio generation and Un-Supervised Machine learning based on K-Means Clustering algorithms are used for Portfolio Evaluation and Selection which take in to account the Portfolio Return and Risk in to consideration. The model presented here is limited to predicting stock prices on a long term basis as the inputs to the model are based on fundamental attributes and intrinsic value of the stock. The results of this study are quite encouraging as the stock prediction models are able predict stock prices at least a financial quarter in advance with an accuracy of around 90 percent and the portfolio selection classifiers are giving returns in excess of average market returns.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.7
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• pp.365-373
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• 2021

This paper investigates the presence of momentum profits in the Saudi stock market. The study applied a quantitative method by utilizing monthly closing prices of 194 listed firms on Tadawal (Saudi Stock Market). The data from January 2010 to February 2019 is taken from the Tadawal market database for analysis. The sample is further divided into two equal sub-samples based on the structural changes that occurred in the Saudi stock market. Moreover, the high- and low-value traded portfolios are also constructed to examine the presence of momentum profits. Sixteen investment strategies are formed for each sample. The results show a very strong presence of momentum profits in the Saudi stock market for the full sample as well as for the sub-samples. The momentum profits are observed for a longer investment horizon. The results confirm that the short or medium-term formation of portfolios produces negative momentum returns for high-value traded stocks. The low-value traded stocks portfolios give similar results to the full sample results in terms of momentum profits. The results suggest that an investor should keep an eye on the past performance of desired stocks for at least three-nine months in which they are willing to invest.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.7
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• pp.383-391
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• 2021

This study examines the connectedness between the number of COVID-19 cases in Thailand and trading value among investors in the Stock Exchange of Thailand. Daily data of COVID-19 cases and trading value were sourced from the Thailand ministry of public health and the Stock Exchange of Thailand, from January 12, 2020 to May 11, 2021. This study applies a multiple linear regression analysis to explain the relationship between variables. Empirical evidence clearly shows that the volatility of trading value was affected by COVID-19's new, confirmed, and deaths cases within the first pandemic period more than during the second pandemic period. Nevertheless, during the third pandemic period there is no evidence that the new, confirmed, and deaths cases significantly influenced trading value. Furthermore, the results show that COVID-19's new and deaths cases have a negative coefficient that indicated the trading value-buy/sell decreased in response to COVID-19's new and deaths cases, whereas the confirmed COVID-19 cases have a positive coefficient that indicated the trading value-buy/sell increased in response to COVID's confirmed cases. In summary, this study suggests that the number of COVID-19 cases have a significant impact on the trading value in the short term more than in the intermediate and long term.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10b
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• pp.1858-1863
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• 1991

The theory of stock option pricing has, recently, attracted attention of many researchers interested not only in finance but also in statistics and control theory. In this field, the problem of estimating stock return volatility is, above all, of great importance in calculating actual stock option value. In this paper, we assume that the stock market is represented by the stochastic volatility model which is the same as that of Hull and White. Then, we propose an approximation function of option value. It is a type of Black-Sholes option formula in which the first and the second order moments of logarithmic stock value are modified in a special form from the original model. Finally, an algorithm of estimating the parameters of the stochastic volatility model is given, and parameters are estimated by using Nikkei 225 index option data.

• Korean Business Review
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• v.20 no.2
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• pp.1-13
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• 2007

The purpose of this study is to investigate a simple present value model Involving earnings (i.e., the earnings discount model) that presumes a relationship between stock prices and earnings. The model suggests a simple linear equilibrium relationship between stock prices and earnings. The tests for cointegration render strong support for the cointegration hypothesis between stock prices (Pt) and earnings (Xt) even at the one-percent significance level. The tests are based on residuals from a cointegrating regression of Pt on Pt+l + Xt. This suggests that there is a stable long-nu equilibrium relationship between stock prices and earnings. The results of the tests lead to the acceptance of the present value model of stock prices involving earnings.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.39-47
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• 2021

This research aims to confirm if the COVID-19 pandemic has had an impact on existing sectors, and how that affects the Indonesian Stock Exchange (IDX) market returns. The research method used is an event study employing market models in nine sectors of the Exchange with purposive sampling technique, and supported by Ordinary Least Square (OLS) regression. Based on the calculation of abnormal returns in the period of 30 days before up to 30 days after, the financial property, real estate, and construction sector results show a decreased abnormal return value. The infrastructure, utilities, and transportation sectors also show an abnormal return value that tends to be constant, while the abnormal return value increases in other sectors. Judging from the cumulative value of abnormal returns, the most affected sector is financials, followed by the trade, service, and investment sectors. The consumer goods and mining industry sectors are still optimistic, while other sectors show temporary negative sentiment. Overall, the stocks on the Indonesia Stock Exchange (IDX) were affected by the COVID-19 pandemic with a cumulative negative value of the average abnormal return sample. The results using OLS regression also strengthen the relationships between the COVID-19 pandemic, and negative and significant market returns.

• Journal of the Korean Data Analysis Society
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• v.20 no.6
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• pp.2759-2769
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• 2018

The behavioral finance view on the existence of asset pricing anomalies is based on two factors: investors' sentiment and limits to arbitrage. This paper tries to examine the effect of investors' sentiment on the stock price in the Korean stock market. In order to measure investors' sentiment, we constructed the sentiment index using principal component of five sentiment variables. By using sentiment index as an additional independent variable to three risk factors, impacts of the sentiment index on individual stocks and 25 portfolios sorted by BM-size are examined. Main results found are as follows: 1) not only all three risk factors show positive impacts on the return of individual stock, but also the sentiment index has a positive impact. SI alone explains 15% of individual return variation. 2) among four independent variables, the most important factor turned out to be the market risk factor and investors' sentiment has better explanatory power on stock price than the size effect. 3) after controlling the market risk factor, the coefficient of the sentiment index for the smallest size and highest book/market value portfolios is significantly positive. 4) all the coefficients of the sentiment index for 25 portfolios sorted by BM-size have significant positive value after controlling size or (and) value.