• The Korean Journal of Financial Management
• /
• v.24 no.4
• /
• pp.201-232
• /
• 2007

In this study, we investigated public announcements of stock splits using the Korean Stock Market data from 2000 through 2007. The purposes of this study are to examine whether stock splits have the information contents in the Korean capital markets, and to investigate the possible cause of the market reactions. We measured the market reactions with abnormal returns, cumulative abnormal returns and cumulative average abnormal returns. For the purpose, two specific hypotheses were tested. One is 'Signalling Effects' where stock splits function as a signal through which managers transmit a favorable information for investors. The other is 'Liquidity Effects' where stock splits increase the trading convenience. We have th following results. Firstly, positive market effects were found when stock splits were announced. Secondly, there was difference in trading convenience between the high and the low split ratios. Finally, the long term performance through stock splits in the Korean capital markets was not significant.

• The Journal of the Korea Contents Association
• /
• v.18 no.9
• /
• pp.623-632
• /
• 2018

Both investors and researchers are attentive to the prediction of stock price movement directions since the accurate prediction plays an important role in strategic decision making on stock trading. According to previous studies, taken together, one can see that different factors are considered depending on stock markets and prediction periods. This paper aims to analyze what data mining techniques show better performance with some representative index and stock price datasets in the Korea stock market. In particular, extreme gradient boosting technique, proving itself to be the fore-runner through recent open competitions, is applied to the prediction problem. Its performance has been analyzed in comparison with other data mining techniques reported good in the prediction of stock price movement directions such as random forests, support vector machines, and artificial neural networks. Through experiments with the index/price datasets of 12 years, it is identified that the gradient boosting technique is the best in predicting the movement directions after 1 to 4 days with a few partial equivalence to the other techniques.

• Journal of the Korea Convergence Society
• /
• v.9 no.7
• /
• pp.213-222
• /
• 2018

This study attempts to empirically investigate the excess returns of growth stocks in the Korean stock market comparing with those of value stocks. Recently, a few of IT and bio-pharmaceutical stocks with high growth potentials have accomplished dramatically high returns in the Korean stock market. Whereas, important prior studies in this line have observed negative excess returns from investment of growth stocks on average. And a few studies have reported that the distribution of excess returns from growth stocks is not normal but positively skewed. Empirical results of the present study are consistent with those of prior studies. Interestingly, the present study observed serial inverse correlation between excess returns of growth stocks and value stocks. Also, regardless of growth or value stocks, the stocks with higher PEG(=PER/ROE) showed higher excess returns.

• Asian Journal of Innovation and Policy
• /
• v.3 no.2
• /
• pp.172-192
• /
• 2014

This study aims to analyze the valuation of technology firms in the stock market to answer how before-market entities should be valuated. This study analyzes 230 market reports of 2012 for technology firms in the KOSDAQ under several hypotheses. The results are as follows: 90% used the 3 multiples methods consisting of PER multiples with 80%, PBR multiples 8.7% and EBITDA multiples 1.7%. The average of PER multiples was 15 with the range of 6.9 to 83. That of PBR multiples is 2.27. Forecasting for cash flow is not applied over 4 years, but mainly 2-3 years. The accuracy of forecasting was 18.8%, 34.4% and 8% according to the different definitions. No differences were found in the accuracy of forecasting between valuation methods, between the industries having more intangible assets and the industries having less, and between startups and general companies and between ages and listed ages.

• The Journal of Asian Finance, Economics and Business
• /
• v.8 no.2
• /
• pp.57-64
• /
• 2021

This research attempts to formulate a new mean-risk model to replace the Markowitz mean-variance model by altering the risk measurement using ARCH variance instead of the original variance. In building the portfolio, samples used are closing prices of Indonesia Composite Stock Index and Indonesia Composite Bonds Index from 2013 to 2018. This study is a qualitative study using secondary data from the Indonesia Stock Exchange and Indonesia Bonds Pricing Agency. This research found that Markowitz's model is still superior when utilized in daily data, while the mean-ARCH model is appropriate with wider gap data like monthly observation. The Historical return has also proven to be more appropriate as a benchmark in selecting an optimal portfolio rather than a risk-free rate in an inefficient market. Therefore Mean-ARCH is more appropriate when utilized under data that have a wider gap between the period. The research findings show that the portfolio combination produced is inefficient due to the market inefficiency indicated by the meager return of the stock, while bears notable standard deviation. Therefore, the researcher of this study proposed to replace the risk-free rate as a benchmark with the historical return. The Historical return proved to be more realistic than the risk-free rate in inefficient market conditions.

• The Journal of Asian Finance, Economics and Business
• /
• v.1 no.1
• /
• pp.5-14
• /
• 2014

This paper empirically examines the short-run and long-run causal relationship between stock market prices and exchange rates in Chinese stock markets using monthly data from January 2002 to December 2012 retrieved from the National Bureau of Statistics of the People's Republic of China. Unit root, cointegration tests, vector error correction estimates, block exogeneity Wald tests, impulse responses, variance decomposition techniques and structural break tests are employed. This study found 1) long-run causality from exchange rates to stock prices in Chinese stock markets and 2) short-run causality from Japanese yen and Korean won exchange rates to stock prices in the Shanghai Stock Exchange strongly prevails while in the Shenzhen Stock Exchange weakly prevails. The impact of the global financial crisis from 2007 to 2009 on Chinese stock markets was insignificant.

• The Korean Journal of Financial Management
• /
• v.26 no.4
• /
• pp.103-140
• /
• 2009

This paper investigates various channels through which liquidity can affect stock returns and examines whether behavioral explanation for liquidity risk is reasonable. First, we examine whether liquidity level (average liquidity) plays a significant role in determining asset returns. The result is consistent with the hypothesis that a stock with higher average illiquidity will have a higher expected return. Second, we focus on the argument that liquidity has a non-diversifiable systematic component. If systemic liquidity has a different impact across individual securities, a stock that is more sensitive to systematic liquidity will have a higher expected return. The results of various tests are inconsistent with each other, not completely supporting the argument. Finally, the intra-market tests in Korea support the behavioral explanation for the liquidity premium, and the effect is stronger in the liquidity level than in the liquidity beta related to systematic liquidity.

• Journal of the Korea Society of Computer and Information
• /
• v.21 no.1
• /
• pp.139-146
• /
• 2016

In this paper, we analyze the information asymmetry among investors in online trading environment using rumors which are collected in the Korean stock market for the eleven-year period between January 2004 and December 2014. We find that cumulative abnormal return of sample firms is negative and statistically significant, indicating that a significant fall of the stock price starts before the online disclosure, suggesting that the rumors were reflected in the stock price to a significant extent. Furthermore, individual investors show net purchases on firms prior to disclosure while institutional investors show net sales, showing that individual investors trade unfavorably vis-$\grave{a}$-vis institutional investors. This phenomenon is more evident for the KOSDAQ. This result confirms that the information asymmetry exists between individual and institutional investors in online trading environment.

• Journal of Korea Trade
• /
• v.27 no.5
• /
• pp.167-198
• /
• 2023

Purpose - This paper aims to compare and analyze the co-movements and information spillover effects between the international commodity futures markets and the South Korean stock markets during the COVID-19 and the 2008 financial crises. Design/methodology - The DCC-GARCH model is used in the co-movements analysis. In contrast, the BEKK-GARCH model is used to evaluate information spillover effects. The statistical data used is from January 1, 2005, to December 31, 2022. It comprises the Korea Composite Stock Price Index data and daily international commodity futures prices of natural gas, West Texas Intermediate crude oil, gold, silver, copper, nickel, soybean, and wheat. Findings - The results of the co-movement analysis were as follows: First, it was shown that the co-movements between the international commodity futures markets and the South Korean stock markets were temporarily strengthened when the COVID-19 and 2008 financial crises occurred. Second, the South Korean stock markets were shown to have high correlations with the copper, nickel, and crude oil futures markets. The results of the information spillover effects analysis are as follows: First, before the 2008 financial crisis, four commodity futures markets (natural gas, gold, copper, and wheat) were shown to be in two-way leading relationships with the South Korean stock markets. In contrast, seven commodity futures markets, except for the natural gas futures market, were shown to be in two-way leading relationships with the South Korean stock markets after the financial crisis. Second, before the COVID-19 crisis, most international commodity futures markets, excluding natural gas and crude oil future markets, were shown to have led the South Korean stock markets in one direction. Third, it was revealed that after the COVID-19 crisis, the connections between the South Korean stock markets and the international commodity futures markets, except for natural gas, crude oil, and gold, were completely severed. Originality/value - Useful information for portfolio strategy establishment can be provided to investors through the results of this study. In addition, it is judged that financial policy authorities can utilize the results as data for efficient regulation of the financial market and policy establishment.

• International Area Studies Review
• /
• v.13 no.3
• /
• pp.287-308
• /
• 2009

This article examines the distributional characteristics of the return of Chinese stock market indices. The majority of previous empirical researches have tended to focus upon the simple stock market index. However, this study focuses on the four indices which represent the characteristics of each stock market index. The empirical findings indicate that the returns of the four chinese indices are not normally distributed at conventional levels. The Ljimg-Box -statistics indicate the returns of the index of A shares are not serially autocorrelated. However, the returns of the index of B shares are serially autocorrelated. The empirical findings also indicate returns of the four chinese indices are not serially autocorrelated. The statistics of Regression Specification Error Test and ARCH indicate the returns of all four indices are not serially linear. The findings also indicate that E- GARCH model is the most fittest model for the returns of the four chinese indices and the forecast error can be reduced by using student t distribution rather normal distribution.