The effect of bond rating changes on stock returns: Evidence from the China & Hong Kong stock market

Efficient Market Hypothesis has always been a hot topic for empirical study in Finance. In this paper, we examine the efficiencies of Mainland China and Hong Kong markets by analyzing the different reactions of stock price and volatility to credit rating changes. The study of impact of credit rating change also fills a gap of no empirical analysis of credit rating change effect in these two markets.

In a semi-strong efficient market, investors cannot make profit based on public information. In this study, we select Chinese cross-listed A-H share companies as our sample and compare the effects of bond rating changes on A-share stock price and H-share stock price. The differences in the stock return and volatility reactions signify the differences in market efficiency. The results from an event study indicate that neither market is semi-strong efficient and Hong Kong market is more efficient in digesting credit rating change information. Both Mainland China and Hong Kong markets show statistically significant and negative abnormal returns after the announcement of credit rating downgrades and only Mainland China market shows statistically significant abnormal returns before the announcement. Hong Kong market shows statistically significant and positive abnormal returns around the announcement of credit rating upgrades and Mainland China market shows no statistically significant abnormal returns around the announcement. Concerning volatility, credit rating downgrades can cause significant positive abnormal volatility around the announcement date in both Mainland China and Hong Kong markets, while there is no significant abnormal volatility around the announcement of credit rating upgrades.

In the cross-sectional analysis of return reactions to credit rating changes, pre-announcement abnormal returns and whether credit ratings moved to speculative grade have an impact on the abnormal returns during the announcement.