• Asia-Pacific Journal of Business
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• v.14 no.3
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• pp.45-66
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• 2023

Purpose - This paper examines whether overnight returns and idiosyncratic volatility (IVOL) jointly affects the cross-section of expected stock returns in the Korean stock market. Design/methodology/approach - Constructing 5×5 bivariate monthly portfolios independently sorted on overnight returns and IVOL, this paper tests whether overpricing of stocks with high overnight returns is more pronounced for the stocks that also have high IVOL. In addition, we also investigate whether time-variation in the degree of overpricing for those stocks can be explained by market volatility. Findings - Our results show that stocks having both high overnight returns and high IVOL exhibit strong negative returns in the future. In contrast, we are unable to observe such negative returns for the stocks that have high overnight returns and low IVOL. This suggests that overpricing of stocks with high overnight returns is concentrated for the stocks having high IVOL. Moreover, we also find that the degree to which such stocks are overpriced is negatively related to market volatility. Research implications or Originality - his paper is the first attempt to explore whether degree of overpricing of stocks having high overnight returns is related to IVOL. We also discover time-varying property of overpricing is jointly driven by overnight returns and IVOL. Our results indicate that IVOL might help explain other previously documented stock return anomalies, suggesting interesting topics for future research.

• Asia-Pacific Journal of Business
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• v.11 no.4
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• pp.243-254
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• 2020

Purpose - This paper explores whether overnight returns measured from the last closing price to today's opening price explain the cross-section of stock returns. Design/methodology/approach - This study is conducted using the Korean stock market data from 1998 to 2018, obtained from DataGuide database. The analysis begins with portfolio-level tests, followed by firm-level cross-sectional regressions. Findings - First, when decile portfolios sorted on the daily average of overnight returns in the previous months, the highest decile portfolio exhibits a significant negative risk-adjusted return. This suggests that stocks with higher average overnight returns are temporarily overvalued due to buying pressure from investors. Second, at least 6 months of persistence exists in average overnight returns, which is in line with the results reported by Barber, Odean and Zhu (2009) that investor sentiment persists over several weeks. Finally, Fama-MacBeth cross-sectional regression of expected returns after controlling for a variety of firm characteristic variables such as firm size, book-to-market ratio, market beta, momentum, liquidity, short-term reversal, the slope coefficient for overnight returns remains negative and statistically significant. Research implications or Originality - Overall, the evidence consistently suggests that overnight return is considered as a new priced factor in the cross-section of expected returns. The findings of this paper not only adds to finance literature, but also could be useful to practitioners in making stock investment decision.

• Management & Information Systems Review
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• v.25
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• pp.83-114
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• 2008

We examine whether spinoffs improve long-run stock returns and analyze the factors of long run stock returns. The measures of long run stock returns are CAR(Cumulative Abnormal Returns) and BHAR(Buy and Hold Abnormal Returns). The expected factors of abnormal returns are methods of spinoffs, size, BV/MV, administrative costs, cashflow and Herfindahl index. We find that long-run returns of the case such as carve-out methods, small size, high BV/MV, low administrative costs, low cashflow and low Herfindahl index are larger than those of other cases. We show positive relationship between spinoffs and long-run stock returns(CAR and BHAR). The results supports spinoffs, as the methods of focusing on core business, are very usefulness of corporate restructuring.

• Management & Information Systems Review
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• v.26
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• pp.1-26
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• 2008

Since Capital Asset Pricing Model(CAPM) was proposed in the early 1960s by William Sharpe(1964) and John Lintner(1965) researchers have investigated the validity of the model. The results of empirical researches do not show that expected returns of stocks seem to be determined solely by systematic risk of the stocks as precicted by CAPM. In this paper the relationship between transaction volume and expected returns of stocks was investigated. Empirical cross-sectional analysis about the data collected from Stock Market of Korea Exchange shows transaction volume and variability of stock returns play an important role in pricing assets. The well-known variables which were used traditionally to explain the differences of expected returns among stocks such as the size and beta of a stock seems to be unimportant in pricing assets.

• Management Science and Financial Engineering
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• v.18 no.2
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• pp.1-4
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• 2012

We study optimal trading strategy of a market maker with stock inventory. Following Avellaneda and Stoikov (2008), we assume the stock price follows a normal distribution. However, we take a constant expected rate of the stock return and assume that the stock volatility is an inverse function of the stock price level. We show that the optimal bid-ask spread of the market maker is wider for a higher expected rate of stock returns.

• The Korean Journal of Financial Management
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• v.26 no.4
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• pp.103-140
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• 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 Distribution Science
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• v.12 no.5
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• pp.61-69
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• 2014

Purpose - Many studies report that returns on hedge portfolios that eliminate particular risk types are abnormal from traditional asset pricing models' perspectives. This study examines the pervasiveness of anomalous returns conditioned on business cycle and group size. Research design, data, and methodology - Using KOSPI and KOSDAQ market data from July 1991 to December 2013, we categorize stocks into appropriately sized groups, and dichotomize our sample periods into expansion and recession periods then, we construct hedge portfolios by sorting stocks by anomaly variables and calculate their returns. Results - Four anomalies, including earnings yield, net stock issue, total asset growth, and liquidity appear pervasive across all groups for the entire sample period. However, only the hedge returns of net stock issues are significant across all group sizes during both expansion and recession. Conclusions - A net stock issue can be an appropriate proxy for expected growth of book equity for all group sizes in recessions. This finding could provide insights to investment industry participants and to researchers interested in the relationship between expected growth of book equity and business cycle risk.

• Journal of the Korean Operations Research and Management Science Society
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• v.22 no.2
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• pp.153-167
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• 1997

There have been many studies concerning the relationships between stock returns and volatilities. Their positive relationship is well known from the theoretical point of view, but not empirically shown. Franch, Schwert and Stambaugh [11] has empirically provided the indirect evidence of the positive relationship betwen expected stock return and expected volatility. However, their study lacks some statistical validity. This study reexamines the relationship using regression diagnostics and GARCH model from an international point of view. The empirical results fall to show the positive relationship between expected stock return and expected volaiility, which contradicts those of France, Schwert and Stambangh [1].

• The Journal of Asian Finance, Economics and Business
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• v.9 no.9
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• pp.1-8
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• 2022

This paper studies market efficiency from a weak form aspect using opening and closing prices of the Shanghai stock exchange composite index (SSEC) and Shenzhen stock exchange composite index (SZSEC) under the expected return theory. Classical methods (autocorrelation and runs test) are used to examine the features of stock returns, and little evidence against mutual independence of returns is found. We predict daily returns of SSEC and SZSEC with AR(p) and VAR(p) models (in this paper, p = 5 is taken as a one-week lag) and perform a virtual experiment on two indexes based on the predicted value of daily returns from AR(p) or VAR(p) model. From the results of AR(p) and VAR(p) for two indexes, we attempt to find out how the market efficiency level changes when the information from the other market is under consideration as we check the market efficiency level in one market. We find that SSEC in 2014-2016 and SZSEC in 2015-2016 are inefficient from the result of autocorrelation, that SSEC in 2016 and SZSEC in 2013 are not efficient from the result of runs test, that the stock market is efficient except 2005, 2009, 2010 and 2017 in SSEC and 2005, 2016 and 2017 in SZSEC and that SSEC is more influenced by SZSEC but SSEC influences SZSEC less from the result of the virtual experiment.

• Journal of Industrial Convergence
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• v.2 no.2
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• pp.127-147
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• 2004

This paper examines the time-series relations among expected return, risk, and book-to-market(B/M) at the portfolio level. The time-series analysis is a natural alternative to cross-sectional regressions. An alternative feature of the time-series regressions is that they focus on changes in expected returns, not on average returns. Using the time-series analysis, we can directly test whether the three-factor model explains time-varying expected returns better than the characteristic-based model. These results should help distinguish between the risk and mispricing stories. We find that B/M is strongly associated with changes in risk, as measured by the Fama and French(1993) three-factor model. After controlling for changes in risk, B/M contains little additional information about expected returns. The evidence suggests that the three-factor model explains time-varying expected returns better than the characteristic-based model.