群聚行為是否為理性或非理性，一直是在文獻中被探討的問題，但始終未能找到有效的方法分辨理性與非理性的群聚行為並且更深入研究兩者行為的不同。本研究嘗試利用Bernhardt, et al. (2006) 所提出衡量分析師群聚行為的S統計量應用於股票市場中，以及利用未來報酬率條件判斷委託簿失衡，提出三個理性群聚行為衡量指標，再利用迴歸式拆解總群聚無法被理性群聚解釋的殘差部分視為非理性的群聚。最後以向量自我迴歸模型探討理性與非理性群聚與市場波動度、效率性及雜訊的相互關係。
本研究結果發現：(1)理性群聚在高市值中可以減少市場波動及雜訊，但對效率性沒有顯著的影響。(2)理性群聚在低市值中也可以降低雜訊但反而增加了市場波動，對市場效率性仍然沒有顯著影響。(3)非理性群聚不論在高市值或低市值皆增加市場波動及雜訊，但對市場效率性仍然沒有顯著影響。(4)市場波動及雜訊，在高市值中確實會降低理性的群聚行為，但在低市值中市場波動反而增加了理性群聚行為，雜訊仍然會降低理性的群聚行為。(5)不論在高市值或低市值，市場波動及雜訊皆會造成非理性群聚行為的增加。(6)市場效率性對於理性與非理性群聚行為並沒有顯著影響，不論在高市值或是低市值。

A comment investment question is: Is herding behavior rational or irrational? Previous studies don’t propose effective methodologies to identify this behavior, or deeply investigate the differences of both rational and irrational herding behavior. The purpose of this study is to propose some methodologies to measure rational herding. Initially, we use the “S statistic” proposed by Bernhardt, et al. (2006) which was originally used to estimate the probability of analysts’ herding and apply it to the stock market. Second, we use the condition of following return to identify order imbalance as rational herding. Then, the residuals form the regression of that unexplained by rational herding. Finally, we research the interaction between rational and irrational herding and market volatility, efficiency, and noise using the Vector Autoregression Model.
The findings of this paper are: (1) Rational herding can decrease volatility and noise, but has no significant impact on efficiency in high market value situations. (2) Rational herding can also decrease noise but increase volatility, however there is also no significant impact on efficiency in low market value situations. (3) Irrational herding can increase volatility and noise but has no significant impact on efficiency in either high or low market value situations. (4) Volatility and noise can decrease rational herding in high market value situations, but the volatility increases rational herding and noise still decreases rational herding in low market value situations. (5) Volatility and noise can increase irrational herding in both high and low market values situations. (6) Market efficiency has no impact on rational or irrational herding in either high or low market value situations.

誌謝 ii
摘要 iii
ABSTRACT iv
I. INTRODUCTION 1
1.1 Background information and motivation 1
1.2 Purposes 5
1.3 Research structure 6
1.4 Research contributions 7
II. LITERATURE REVIEW 8
2.1 Herding behavior 8
2.2 Herding measurement 12
2.3 Herding and volatility, efficiency, noise 14
III. METHODOLOGY 18
3.1 Data description 18
3.2 Rational herding and irrational herding 18
3.2.1 Total herding 19
3.2.2 Rational herding 20
3.2.3 Irrational herding 25
3.3 Empirical model 27
3.3.1 Market quality 27
3.3.2 Vector Autoreggression (VAR) Model 30
IV. EMPIRICAL RESULTS 34
4.1 Summary statistics for rational, irrational herding and market quality 34
4.1.1 Rational herding 34
4.1.2 Irrational herding 36
4.2 Vector Autoregression Model 39
4.2.1 Herding and volatility 39
4.2.2 Herding and efficiency 44
4.2.3 Herding and noise 48
4.3 Robustness Check 53
V. CONCLUSION 56
5.1 Conclusion 56
5.2 Suggestions for future research 60
REPERENCES 61
Appendix: 64

英文部分
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中文部分
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