The purpose of this study is to examine how credit rating agencies’ decisions impact the stock market using a systematic and quantitative review of existing empirical studies. Specifically, we employ a meta‐regression analysis (MRA) to investigate the extent and nature of the effect of rating agencies’ decisions on the stock market. We survey 62 studies published between 1978 and 2015. Our first finding is that the cumulative average abnormal returns calculated from this empirical literature are affected by publication bias. After controlling for publication bias, the main findings of our meta‐analysis indicate that negative rating decisions cause statistically significant negative abnormal returns. This evidence suggests an informational effect. Our results also indicate that positive rating decisions do not have a significant effect. Finally, the MRA results reveal the importance of several factors related to primary study design, as well as to the nature of the data.

No abstract

Luc Neuberg is Managing Director of Fortis Investments Luxembourg and Risk Manager of Fortis Multi-Management.His research area concerns financial risks, asset allocation and agent-based modelling.Virginie Terraza is an assistant professor of finance at the University of Luxembourg and researcher in Luxembourg School of Finance (LSF). Her principal research centres relate to the analysis of the financial risks, portfolio management and financial econometrics. Practical applicationsNet asset value (NAV) of funds of funds (FoF) is based on the underlying funds NAVs. Due to the time of publication of the underlying funds NAVs as well as the underlying funds relating to different markets with different closing times, the NVA of FoF includes time lags and is therefore producing some noise. This noise makes it difficult to correctly estimate tracking error (TE). To minimise the impact of time lags, the authors suggest a measure to adjust the TE considering the problem of non-synchronous data. The paper constitutes an appropriate reading for risk managers as well as for investors needing to compare risk relevant factors using TE (ie information ratio) of funds of funds. AbstractThe purpose of this paper is to analyse the impact upon tracking errors (TEs) of time lags in the calculation of fund of funds (FoF) net asset value (NAV). We examine how microstructure effects produce noise in the NAV of FoF and therefore noise in the TE. For that, we use simulations to calculate FoF NAVs at different closing dates. We then compare series of TEs to analyse the impact of time lags and formalise a relation adjusting the TE including error terms in the ratio.

The purpose of this paper is to analyze the impact upon tracking errors of timing inconsistencies in the calculation of Funds of Funds (FoF) net asset value (NAV). We examine how these timing inconsistencies produce noise in the NAV of FoF and therefore noise in the tracking error. We construct Funds of Funds and calculate NAVs of these FoF using underlying NAVs at different dates. We then compare series of tracking errors to analyze the impact of the timing inconsistencies and formalize a relation adjusting the tracking error including the error term generated by these timing inconsistencies.