• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.5
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• pp.163-169
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• 2019

This study examined whether industry-level competition affects excess stock returns because of changes in cash holdings. Competitive inter-company threats increase the possibility of the manager's replacement, and function to induce management to make their best efforts, resulting in the amount and quality of the information provided by the enterprise increasing. Therefore, as competition intensifies, agency problems are reduced and stock returns increase because the company's cash holdings are expected to increase. However, there is a view that firms in industries with severe competition tend to have high information asymmetry because competitors may compete in more favorable positions by using detailed information disclosed by the competing firms. Accordingly, as market competition intensifies, the excess stock returns resulting from increased cash holdings are expected to decline. These results show that excess stock returns because of increases in cash holdings increase as the degree of competition in the industry intensifies, thus supporting the positive effect of market competition. Overall, the results of this study provide an understanding that market competition plays an effective external governance mechanism and that investors positively evaluate the cash held by companies with severe industry competition.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.11a
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• pp.173-179
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• 2006

In order to explain a U-shape pattern of stock returns, Fama and French(1988) suggested the state-space model consisting of I(1) permanent component and AR(1) stationary component. They concluded the autoregression coefficient induced from the state-space model follow the U-shape pattern and the U-shape pattern of stock returns was due to both negative autocorrelation in returns beyond a year and substantial mean-reversion in stock market prices. However, we found negative autocorrelation is induced under the assumption that permanent and stationary noise component are independent in the state-space model. In this paper, we derive the autoregression coefficient based on ARIMA process equivalent to the state-space model without the assumption of independency. Based on the estimated parameters, we investigate the pattern of the time-varying autoregression coefficient and conclude the autoregression coefficient from the state-space model of ARIMA(1,1,1) process does not follow a U-shape pattern, but has always positive sign. We applied this result on the data of 1 month retums for all NYSE stocks for the 1926-85 period from the Center for Research in Security Prices.

• Asia-Pacific Journal of Business
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• v.12 no.2
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• pp.97-114
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• 2021

Purpose - The purpose of this study was to examine the effects of privatization of Chinese state-owned enterprises (SOEs) on their initial returns and long-term performance after initial public offering(IPO). Design/methodology/approach - This study used 1,599 Chinese IPO firms, some of which were SOEs. The multivariate regression analyses were implemented to analyze their effects. Findings - First, the privatization of SOEs does not have any statistically significant effect on the initial return of IPO firms. Second, the shareholdings of government prior to IPOs for both privatizing of SOEs and non-privatizing firms and for both exchanges of Shanghai and Shenzhen have a statistically significant positive effect on the initial return of IPO firms. Third, the privatization of SOEs has statistically significant negative effect on the long-term returns of IPO firms. Fourth, the state-shareholdings prior to IPOs have statistically significant negative effects on the long-term return of IPO firms. Fifth, the state-shareholdings of the privatizing SOEs prior to IPOs have statistically significant positive effects on the long-term return of IPO firms. Research implications or Originality - The results imply that the higher shareholdings and ownership of the Chinese government on SOEs reduce the information asymmetry for the investors of IPO shares or maybe due to inefficiency of SOEs prior to IPOs lead to lower offer prices or higher opening prices leading to severe underpricing and relatively lower stock market returns in the long-run both for the privatizing firms and for the higher state-shareholding firms, while both factors interactively improve their long-term stock market returns.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.7
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• pp.95-104
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• 2020

This study examines the effect of fintech on retail banks stock return listed in Indonesia Stock Exchange for the period of 2016-2018 as today's new technology lead to the emergence of fintech companies playing the same role as retail banks in the financial industry. This study is conducted quantitatively using monthly data from January 2016 to October 2018 and uses fintech as independent variable, proxied by fintech funding frequency and fintech funding value. Data transformation is conducted due to data volatility. The data of fintech funding, both frequency and value, is transformed into standardized fintech funding and growth of fintech funding. The data is obtained from Crunchbase, while the data of stock returns is obtained from Investing. This study further analyzes the data using Fama French Three-Factor Model and panel data regression. We found that fintech has no significant effect on retail banks' stock returns listed in Indonesia Stock Exchange for the period of 2016-2018. The findings of the study provide some useful insights in understanding fintech companies' current position to retail banks in Indonesia. This study also suggests banking institutions, fintech companies, policy-makers, and others to take advantageous steps in building inclusive financial sectors.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.1
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• pp.15-22
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• 2021

This study aims to obtain a stock investment strategy model based on the industrial sector in Indonesia Stock Exchange (IDX). This study uses IDX data for the period of January 1996 to December 2016. This study uses the Markov Regime Switching Model to identify trends in market conditions that occur in industrial sectors on IDX. Furthermore, by using the Logit Regression Model, we can see the influence of economic factors in determining trends in market conditions sectorally and the probability of trends in market conditions. This probability can be the basis for determining stock investment decisions in certain sectors. The results showed descriptively that the stocks of the consumer goods industry sector had the highest average return and the lowest standard deviation. The trend in sectoral stock market conditions that occur in IDX can be divided into two conditions, namely bullish condition (high returns and low volatility) and bearish condition (low returns and high volatility). Differences in the conditions are mainly due to differences in volatility. The use of a Logit Regression Model to produce probability of market conditions and to estimate the influence of economic factors in determining stock market conditions produces models that have varying predictive abilities.

• Journal of Distribution Science
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• v.21 no.5
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• pp.101-111
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• 2023

Purpose: The purpose of this paper is to examine the effect of the VKOSPI index on short-term stock returns after a large-scale stock price shock of individual stocks of firms in the distribution industry in Korea. Research design, data, and methodology: This study investigates the effect of the change of the VKOSPI index or investor mood on abnormal returns after the event date from January 2004 to July 2022. The significance of the abnormal return, which is obtained by subtracting the rate of return estimated by the market model from the rate of actual return on each trading day after the event date, is determined based on T-test and multifactor regression analysis. Results: In Korea's distribution industry, the simultaneous occurrence of a bad investor mood and a large stock price decline, leads to stock price reversals. Conversely, the simultaneous occurrence of a good investor mood and a large-scale stock price rise leads to stock price drifts. We found that the VKOSPI index has strong explanatory power for these reversals and drifts even after considering both company-specific and event-specific factors. Conclusions: In Korea's distribution industry-related stock market, investors show an asymmetrical behavioral characteristic of overreacting to negative moods and underreacting to positive moods.

• Communications for Statistical Applications and Methods
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• v.31 no.5
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• pp.535-556
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• 2024

Measuring stock market volatility and its determinants is critical for stock market participants, as volatility spillover effects affect corporate performance. This study adopted a novel approach to analysing and implementing GARCH-MIDAS modelling methods. The classical GARCH as a benchmark and the univariate GARCH-MIDAS framework are the GARCH family models whose forecasting outcomes are examined. The outcome of GARCH-MIDAS analyses suggests that inflation, interest rate, exchange rate, and oil price are significant determinants of the volatility of the Johannesburg Stock Market All Share Index. While for Nigeria, the volatility reacts significantly to the exchange rate and oil price. Furthermore, inflation, exchange rate, interest rate, and oil price significantly influence Ghanaian equity volatility, especially for the long-term volatility component. The significant shock of the oil price and exchange rate to volatility is present in all three markets using the generalized autoregressive conditional heteroscedastic-mixed data sampling (GARCH-MIDAS) framework. The GARCH-MIDAS, with a powerful fusion of the GARCH model's volatility-capturing capabilities and the MIDAS approach's ability to handle mixed-frequency data, predicts the volatility for all variables better than the traditional GARCH framework. Incorporating these two techniques provides an innovative and comprehensive approach to modelling stock returns, making it an extremely useful tool for researchers, financial analysts, and investors.

• The Journal of the Korea Contents Association
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• v.21 no.11
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• pp.320-332
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• 2021

This paper investigates the influence of stock-level left-tail risk, which is defined using Value-at-Risk(VaR) estimates of past one-year daily stock returns, in the expected stock returns in the Korean stock market. Our results are summarized as follows: First, monthly-constructed zero-cost portfolios that buy (shortsell) the highest (lowest) left-tail risk decile in the previous month exhibit an average monthly return (called left-tail risk premium) of -2.29%. Second, Fama-MacBeth cross-sectional regressions suggest that left-tail risk in the previous month shows significant and negative explanatory power over return in this month, after controlling for various firm characteristics such as firm size, B/M, market beta, liquidity, maximum daily return, idiosyncratic volatility, and skewness. Third, the stocks with larger recent month loss have lower returns in the next month. Fourth, the magnitude of left-tail risk premium is negatively related with lagged market-level volatility. These results support the hypothesis from a perspective of behavioral finance that the overpricing of stocks with left-tail risk is attributed to the investors' underreaction to it.

• 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.

• Management & Information Systems Review
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• v.38 no.3
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• pp.1-19
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• 2019

This paper investigates the asymmetric effects of crude oil price uncertainty on industrial stock returns under different market conditions (bearish and bullish stock markets). We consider a quantile regression method using monthly oil volatility index, KOSPI and 22 industrial stock indices from May 2007 to February 2019. Especially, we take care of the positive and negative changes of the oil volatility index to analyze asymmetric effects of the oil price uncertainty for the bearish and bullish stock market conditions. During the bearish markets, the oil volatility index has relatively strong statistically significant negative effects on the industrial stock returns. These effects gradually decrease when the market conditions became more bullish markets. In particular, positive changes in the oil volatility index yields a further significant decrease in 12 industrial stock returns during the extreme bearish markets. Moreover, during the bullish markets, negative changes in the oil volatility index have statistically significant negative effects on the 12 industrial stock returns. From the empirical results, we see that participants of the Korean stock market are sensitive to bad news in a recession.