Do rating agencies exhibit herding behaviour? Evidence from sovereign ratings

Abstract

We assess the presence of herding by considering the lead-lag relationship of sovereign ratings assigned by the three main rating agencies at the individual country level. Given that different rating agencies may have different levels of expertise (reputation) for different countries it is not obvious that such homogeneity holds. We therefore conduct poolability tests within this context to assess this assumption and find evidence of heterogeneity. This leads us to conduct country-by-country time-series tests to assess the lead-lag relationship among agencies. To our knowledge we are the first to do this and thereby extend the literature on herding among rating agencies' sovereign assignments. We also consider changes in the lead-lag relationship through time by splitting the sample into pre-crisis and crisis periods to assess the extent to which any herding is intentional and our results indicate some degree of heterogeneity through time. To the extent that there is herding we find that it is generally towards Standard and Poor's ratings confirming our expectations given that this agency is regarded as possessing the greatest reputational capital. However, our results do not support the expectation that Fitch is a follower for more (a leader for less) countries than Moody's.

From COVID-19 herd immunity to investor herding in international stock markets: The role of government and regulatory restrictions

“…Second, unlike previous studies on herding behaviour in international stock markets (e.g., Chen et al, 2019 , Chiang and Zheng, 2010a , Gebka and Wohar, 2013 , Lin, 2018 , Yarovaya et al, 2020 ), this study exploits the possibility that government response to the coronavirus pandemic can mitigate herding behaviour. For instance, fiscal stimulus packages that incentivise companies to temporarily furlough employees with a public subsidy (UK), and contribute to information sets of international investors, can potentially trigger no herding or anti-herding effects.…”

First‐mover disadvantage: the sovereign ratings mousetrap

“…In contrast with these studies, Chen et al. (2019) assume herding amongst CRAs to be heterogenous across sovereigns. Using 35 separate country regressions, the authors find that herding differs across countries and CRAs.…”

“…“Hiding in the herd” might prevent them from being penalised for making a “wrong” decision (Scharfstein and Stein, 1990). Secondly, individuals might observe positive externality from imitating the behaviour of others, for example when they believe their peers have an information advantage (Chen et al., 2019; Graham, 2003). Finally, imitating behaviour of others might bring an increased pay‐off with a rising number of agents behaving the same way (see Devenow and Welch, 1996).…”

“…Our important findings lie in the test of the commercial ‘mousetrap hypothesis’, as we focus on the commercial consequences for the first mover CRA rather than its followers (e.g., Chen et al., 2019; Lugo et al., 2015). Specifically, we investigate the impact of sovereign downgrades by S&P (the downgrade leader CRA in our data) on their future sovereign rating coverage and their probability of ratings contracts being withdrawn.…”

Exploring Probabilistic Network‐Based Modeling of Multidimensional Factors Associated with Country Risk

“…Forecasters assign and replicate country risk ratings to facilitate policy‐makers involved in establishing national policies. However, these ratings may provide biased opinions due to the focus of rating strategies on backward looking analyses rather than forward looking (Chen, Stewart, & Webb, 2019). Rating agencies are also critiqued for using opaque methodologies and overestimating (underestimating) ratings in good (bad) times (Chen, Stewart, & Webb, 2019).…”