Empirical investigation of herding behavior in Chinese stock markets: Evidence from quantile regression analysis

Analysis of Herd Behavior Using Quantile Regression: Evidence from Karachi Stock Exchange (KSE)

“…As Karachi Stock Exchange is an emerging stock market therefore, to that extent, these results are consistent with their results. These results are consistent with those reported by Chiang, Li and Tan, (2010) ;Tan, Chiang, Mason and Nelling, (2008) that herd behavior exist in the Chinese market. Chiang, Li and Tan, (2010) found herding behavior in A-share markets.…”

“…These results are consistent with those reported by Chiang, Li and Tan, (2010) ;Tan, Chiang, Mason and Nelling, (2008) that herd behavior exist in the Chinese market. Chiang, Li and Tan, (2010) found herding behavior in A-share markets. Tan, Chiang, Mason, and Nelling, (2008) found herding behavior in dual-listed B-shares in the Chinese equity market.…”

“…Therefore, during market stress, herding occur in lower quantiles. These results are consistent with Chiang, Li and Tan, (2010) results indicate that herding exists in the median and lower quantiles of the stock return dispersions in Chinese aggregate stock market while in sub groups they found mixed results. The detailed results are reported in table 5.…”

“…Results in Table 5 show that the estimated coefficients and significance levels differ with According to Chiang, Li and Tan, (2010), this difference in results in two methodologies is due to the difference in approaches of these methodologies. The OLS method considers the mean as a measure of location while the quantile regression method considers different regression curves against each quantile dependent variable i.e.…”

“…They also reported that results may be distorted due to excessive outliers created by news in financial markets (Chiang, Li, & Tan, 2010). Due to its coverage of different quantiles, Barnes and Hughes (2002) reported that this method is the best to detect extreme values that have a skewed distribution or fat tails.…”