Time-varying herding behavior within the Eurozone stock markets during crisis periods

Abstract

Purpose Motivated by the ongoing debate on the existence and magnitude of herding in financial markets, the purpose of this paper is to examine Eurozone stock markets for herding behavior. In the context of the present study, the authors seek for herding behavior of stock markets as a whole as opposed to previous studies that examine herding on stock level. Design/methodology/approach To this end, the authors employ data on benchmark stock market indices for a long sample starting from 2000 through 2016. The testing procedure entails the standard Capital Asset Pricing Model-based procedure along with an advanced econometric method allowing the coefficients of the model to vary over time. Findings Results provide evidence in favor of negative herding behavior (anti-herding) for the Eurozone as a whole with noteworthy transitions. Further analysis reveals that stock markets of the periphery exhibit scarce evidence of herding, whereas continental countries are mainly characterized by negative herding behavior. Originality/value The present study’s main contribution is twofold. First, herding is examined not in sector or stock level as previous studies but at market level. Second, the testing methodology entails a pure time-varying regression model with stochastic volatility proposed by Nakajima (2011) that has not been previously employed in stock market herding. The results entail significant implications for investors seeking for diversification across Eurozone stock markets.

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“…Moreover, the fractal dimension d increases between the first sub-period (before the outbreak) and the second (after the outbreak), implying that herding behaviour decreases between the two periods. These empirical findings are also in line with previous works (Stavroyiannis & Babalos, 2019). Therefore, the risk of bubbles weakens and inefficiency is minimised.…”

Anomalous diffusion and long-range memory in the scaled voter model

“…The assumption that herding behavior is time-dependent is quite common in the literature [18][19][20][21]. Yet often it is assumed to be a stochastic process.…”

“…The assumption that the intensity of herding behavior is time-dependent is quite common in the literature [18][19][20][21]. Yet often it is assumed to be a stochastic process, while here we assume that herding behavior follows a deterministic power-law function.…”

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“…Particularly, our hourly CSAD static model results agree with those of Sibande et al (2021) , who observe anti-herding behaviour in the currency market with their CSAD static measure. One might argue that herding behaviour is very likely to be time-varying ( Babalos et al, 2015 , Gębka and Wohar, 2013 , Stavroyiannis and Babalos, 2017 , Stavroyiannis and Babalos, 2020 , Yarovaya et al, 2021 ). To depict its potentially vigorous and fluctuating nature, we implement Nakajima (2011) ’s TVP model with stochastic volatility.…”