ANALISIS INVESTOR HERDING BEHAVIOR DENGAN MULTINOMIAL LOGIT REGRESSION PADA BEI (Studi Kasus pada Saham LQ-45 Periode 2009-2014)

FITYANI, Izza and ARFINTO, Erman Denny (2015) ANALISIS INVESTOR HERDING BEHAVIOR DENGAN MULTINOMIAL LOGIT REGRESSION PADA BEI (Studi Kasus pada Saham LQ-45 Periode 2009-2014). Undergraduate thesis, Fakultas Ekonomika dan Bisnis.

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Abstract

Herding Behavior is the tendency of institutional or individual investors to behave similar. This behavior is irrational because investors do not depend their investment decisions on information available but follow the crowd. Distinguishing the causes of herding behavior is crucial for discovering whether herding leads to market inefficiency and financial bubbles. Herding may destabilize stock prices and thus impair the proper functioning of financial market. This study is analyzing the effect of size, trading volume activity, return and volatility to herding behavior in 2009 to 2014 period. Herding behavior will be measured based on the types of investors in Indonesian capital market. Then analysis of the effect of size, trading volume activity, return and volatility to herding behavior will be conducted using multinomial logistic regression method. The result of this study shows that size gives positive effect to all types of investors in herding behavior. TVA gives positif effect on four types of investors while eight other types investors have negatife effects for herding behavior. Return does not give effect to all types of investors while volatility give positive effect on all types investor except domestic investors institution and foreign institution investor for herding behavior. Size and volatility have the most impact for investor in herding.

Item Type:Thesis (Undergraduate)
Additional Information:herding behavior, investor-owned shares, LQ-45 index, multinomial logistic regression
Uncontrolled Keywords:herding behavior, investor-owned shares, LQ-45 index, multinomial logistic regression
Subjects:H Social Sciences > H Social Sciences (General)
Divisions:Faculty of Economics and Business > Department of Management
ID Code:46106
Deposited By:INVALID USER
Deposited On:11 Aug 2015 09:45
Last Modified:11 Aug 2015 09:45

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