scholarly journals Relationship between Trading Volume and Asymmetric Volatility in the Korean Stock Market

2012 ◽  
Vol 03 (05) ◽  
pp. 584-589 ◽  
Author(s):  
Ki-Hong Choi ◽  
Zhu-Hua Jiang ◽  
Sang Hoon Kang ◽  
Seong-Min Yoon
Keyword(s):  
Stock Market ◽  
Trading Volume ◽  
Asymmetric Volatility ◽  
Korean Stock Market

scholarly journals Investor Sentiment and Herding Behavior in the Korean Stock Market

2020 ◽  
Vol 8 (2) ◽  
pp. 34
Author(s):  
Ki-Hong Choi ◽  
Seong-Min Yoon
Keyword(s):  
Stock Market ◽  
Quantile Regression ◽  
Stock Markets ◽  
Trading Volume ◽  
Investor Sentiment ◽  
Herding Behavior ◽  
Absolute Deviation ◽  
Cross Sectional ◽  
Korean Stock Market ◽  
Quantile Regression Method

This paper investigates herding behavior and the connection between herding behavior and investor sentiment. We apply a Cross-Sectional Absolute Deviation (CSAD) approach and the quantile regression method to capture herding behavior in the KOSPI and KOSDAQ stock markets. The analysis results are outlined as follows. First, we find that herding behavior is exhibited during down-market periods in the KOSPI and KOSDAQ stock markets. However, we show that adverse herding behavior occurs in low-trading volume and low-volatility periods. Second, according to the results of the quantile regression, herding behavior is found in the low and high quantiles of the KOSPI and KOSDAQ stock markets. However, adverse herding behavior is also found, which means that investors herd in extreme market conditions. Third, the relationship between investor sentiment and herding behavior is analyzed through regression and quantile regression, and investor sentiment is confirmed to be one of the important factors that can cause herding behavior in the Korean stock market.

Self-attribution, Overconfidence and Dynamic Market Volatility in Indian Stock Market

2018 ◽  
Vol 21 (4) ◽  
pp. 970-989
Author(s):  
Venkata Narasimha Chary Mushinada ◽  
Venkata Subrahmanya Sarma Veluri
Keyword(s):  
Stock Market ◽  
Trading Volume ◽  
Stock Exchange ◽  
Empirical Evaluation ◽  
Market Volatility ◽  
Crisis Period ◽  
Asymmetric Volatility ◽  
Attribution Bias ◽  
Indian Stock Market ◽  
Overconfidence Bias

The article provides an empirical evaluation of self-attribution, overconfidence bias and dynamic market volatility at Bombay Stock Exchange (BSE) across various market capitalizations. First, the investors’ reaction to market gain when they make right and wrong forecasts is studied to understand whether self-attribution bias causes investors’ overconfidence. It is found that when investors make right forecasts of future returns, they become overconfident and trade more in subsequent time periods. Next, the relation between excessive trading volume of overconfident investors and excessive prices volatility is studied. The trading volume is decomposed into a first variable related to overconfidence and a second variable unrelated to investors’ overconfidence. During pre-crisis period, the analysis of small stocks shows that conditional volatility is positively related to trading volume caused by overconfidence. During post-crisis period, the analysis shows that the under-confident investors became very pessimistic in small stocks and tend to overweight the future volatility. Whereas, the analysis of large stocks indicates that the overconfidence component of trading volume is positively correlated with the market volatility. Collectively, the empirical results provide strong statistical support to the presence of self-attribution and overconfidence bias explaining a large part of excessive and asymmetric volatility in Indian stock market.

scholarly journals Contemporaneous Correlation between the Return and the Change of Trading Volume

2019 ◽  
Vol 27 (4) ◽  
pp. 425-473
Author(s):  
Mhin Kang ◽  
Joon Chae
Keyword(s):  
Stock Market ◽  
Portfolio Management ◽  
Stock Price ◽  
Trading Volume ◽  
Return Volatility ◽  
Daily Return ◽  
Stock Price Prediction ◽  
Contemporaneous Correlation ◽  
Korean Stock Market ◽  
The Individual

This study demonstrates the contemporaneous correlation between return and the change of trading volume (CCRV) in the Korean stock market and analyzes the effect of trading volume change on the return and its volatility of individual stocks. Also, we examine the underlying reasons for CCRV in the Korean stock market. The empirical analysis covers individual stocks listed in KOSPI and KOSDAQ and their portfolios from 1989 to 2015. The main results are as follows. First, the CCRV in the Korean stock market dominantly appears positive. Second, at the individual stock level, the daily return volatility induced by CCRV accounts for 4.22% of the total daily return volatility. Third, the return volatility induced by CCRV is largely offset by well-diversified portfolios. Lastly, the ratio of positive CCRV decreases in stocks with very high or very low liquidity. The above result suggests that the illiquidity premium hypothesis is appropriate in explaining CCRV in the Korean stock market. In addition, the above results also indicate that the changes of trading volume can act as an idiosyncratic risk factor that can additionally intensify or weaken the response of the return toward the news. Furthermore, these results suggest that a strategy with sufficient consideration for CCRV is essential for the stock price prediction, the valuation of derivatives, and portfolio management.

Spot Trading Volume Volatility, Futures Trading Volume Volatility, and the Volatility of Korean Stock Market

2011 ◽  
Vol 19 (2) ◽  
pp. 149-173
Author(s):  
Kook Hyun Chang ◽  
Byung Jo Yoon
Keyword(s):  
Stock Market ◽  
Stock Markets ◽  
Trading Volume ◽  
Relative Importance ◽  
Futures Trading ◽  
Jump Model ◽  
Korean Stock Market ◽  
Transitory Component

This paper tries to investigate whether the information contained in trading volume volatilities of spot and futures may be statistically useful in explaining the volatility of korean stock market. This paper uses both the component-jump model and the bivariate GJR-GARCH type BEKK model to estimate the trading volume volatilities of spot and futures from 1/2/2001 to 9/30/2010. By using the component-jump model, the volume volatility is decomposed into a permanent component and a transitory component. According to this study, the relative importance of permanent component to the transitory component contained in both trading volume volatilities of spot and futures has been more significant in explaining the volatility of the korean stock markets.

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