Abstract
This paper investigates the consequences of herding on systematic and idiosyncratic risk for stocks traded on S&P 500. Herding behavior is measured through a state-space model. Using monthly data from 1999 to 2017, different periods of herding and adverse herding are present. Evidence shows that the state space model identifies the significant herding effects on both risk measures for specific portfolios. Our findings validate the expected implications of herding on betas but not of adverse herding. In addition, the low-beta anomaly is not confirmed on our beta-based portfolios. On the other hand, we confirm the risk-return relationship. We attribute this evidence to overpriced values of high beta assets as well as to the effects of adverse herding on the systematic and idiosyncratic risk. Finally, we also show that the herding level could serve as a systematic driver of returns improving the portfolio performance of traditional ‘anomaly’ based strategies.
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