The Determinants of Beta Herding : Panel Data Evidence from 16 European Countries

This paper investigates the determinants of time-varying herd behaviour and their interaction effect with asymmetric market conditions. The sample used covers the stocks listed in Europe from December 1992 to December 2020. We expand the state-space model of Hwang and Salmon (2004) to capture herding towards the market, size/growth (SMB), value (HML), operating profitability (RMW), investment (CMA) and momentum (WML) factors. We use a fixed-effects model with Driscoll and Kraay’s (1998) standard errors to analyse the impact of market return, volatility, liquidity and sentiment on herd behaviour. Our main conclusions are that herding increases with volatility and decreases with liquidity and sentiment, while market returns do not explain herding. We estimate that controlling for past herding and macroeconomic conditions, an increase of 10% in volatility and liquidity leads to an increase of 0.0059 and a decrease of 0.0032 points in herding, respectively. Conditioning herding by asymmetric states of return, volatility, liquidity and sentiment further reveals that uncertainty and low sentiment enhance herd behaviour. These results support herding to be risk- and lack-of-information-driven