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Abstract

Investor herding behavior is a primary source of speculative bubbles since it implies that investors make identical trading decisions, which can lead to stock prices deviating from their underlying worth. The goal of this study is to detect herding behavior in the Indonesian stock market between 2016 and 2021. The relationship between return and trading volume, known as Cross Sectional Absolute Deviation, is used to assess herding behavior (CSAD). Time-series regression and quantile regression analysis will be employed as data analytic techniques in this study to investigate herding behavior under various market scenarios. Herding behavior is evident in the Indonesian stock market with low trading volume, high market return, and low market return in quantile 0,95. Herd behavior has both beneficial and harmful consequences during certain investing seasons. The best method to reduce the impact is to strengthen the investor’s trading strategy and trading platform

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