No abstract

Purpose The purpose of the study is to examine whether analyst coverage responds to changes in investor information demand for a firm and to test whether certain investor or firm characteristics moderate this association. Design/methodology/approach The authors model analyst activeness (AA) as a function of institutional investors' information demand, proxied by news readership on Bloomberg terminals and retail investors' information demand, proxied by the Google Search Volume Index (GSVI). Additionally, the authors take several steps to mitigate concerns about reverse causality that may confound the findings. Findings Results suggest that analysts respond to information demand shocks, but partially revert their coverage after the demand shock subsides. Furthermore, the results suggest that analysts cater their coverage more towards institutional investors than to retail investors. Evidence also suggests that analysts are more responsive to investors interested in firms with tech stock characteristics. Finally, the authors find evidence that specialist analysts respond more to institutional investors while generalist analysts respond more to retail investors. Originality/value The authors are the first to empirically examine the extent to which analysts cater to investor information demand. This is a vital topic to study because analysts are one of the primary sources of information for market participants. Understanding an analyst's motivation for providing information will help to facilitate market efficiency.

PurposeMany prior tests of market efficiency, which occurred decades ago, were limited by data and did not employ methodology to correct for leptokurtosis in the stock return distribution. Furthermore, these studies did not test many aspects of conditional market efficiency. One aspect of a potential conditional violation of market efficiency is whether stock markets are efficient conditional on the level of stock return.Design/methodology/approachThis paper uses quantile regressions to control for leptokurtosis in the stock return distribution and simultaneous quantile regressions to test whether markets are efficient conditional on the level of the market return. This paper uses market-level stock return data to bias against finding significant results in the efficiency tests. Furthermore, the author uses data from 1926 through 2018, providing the longest time period to date under which market efficiency is tested.FindingsThis paper presents evidence that the autoregressive coefficient decreases across return levels in stock market indices. The autoregressive coefficient is positive around highly negative returns and negative or insignificant around highly positive returns, which suggests that when stock returns are low they are more likely to continue lower, and when stock returns are high they are more likely to reverse. Results additionally suggest that market efficiency is not time-invariant and that stock markets have become more efficient over the sample period.Originality/valueThis paper extends the literature by finding evidence of a violation of weak-form market efficiency conditional on the level of stock returns. It further extends the literature by finding evidence that the stock market has become more efficient between 1926 and 2018.

We use an international sample to test theories predicting an association between operating and financial leverage with stock returns and the value premium. We find evidence that operating and financial leverage are related to stock returns and the value premium across the sampled countries. Results hold after considering the trade‐off between financial and operating leverage and are stronger in North American and European subsamples. Consistent with theory, we find that a country's labor share is positively associated with the value premium. Overall, we present evidence suggesting the value premium reflects compensation for exposure to systematic operating and financing risk.