An Analysis of Herding in the Korean Stock Market Using Network Theory

Using network theory, we investigate if investors follow movements of closely ‘connected stocks’ regardless of their fundamentals or industries when investment decision is driven by panic under stress. We find strong evidence of herding in the Korean market for the period from January 2005 to December 2015 as in previous studies in herding. However, herding arises at positive extreme market movements during bear states. We interpret the results as follows: during bear states when the expected market return is high, overconfident investors over-respond to good signals because the signals are consistent with their priors of the high expected market return (self-attribution bias). Herding does not necessarily arise by panic under stress.