Abstract
AbstractThis study examines the time‐varying performance of investment strategies following analyst recommendation revisions in the UK stock market, with specific emphasis on the impact of changing market conditions. We find a negative relationship between the recommendation performance and market conditions as measured in terms of past market return and market volatility. In particular, the upgrade (downgrade) portfolio generates significantly positive (negative) net abnormal returns in bad market conditions (e.g., the dot‐com bubble burst in 2000 and the credit crisis in 2007), but not in other periods of time. Moreover, our non‐temporal threshold regression analysis shows that the reported negative relationship disappears when market conditions become better, i.e., when the past market return (market volatility) is higher (lower) than a certain level, indicating the importance of taking non‐linearity into account in the long sample period as examined in this study. Our time‐series bootstrap simulations further confirm that the superior recommendation performance in bad market conditions is not due to random chance; analysts have certain skills in making valuable up/downward revisions in bad markets.
Highlights
There are numerous studies on the information role of financial analysts, while the existing literature mostly ignores the question of whether the performance of their stock recommendations is related to the state of the economy (Chang & Choi, 2017; Loh & Stulz, 2018). Loh and Stulz (2018) provide empirical evidence showing that analysts’ advice is more valuable in bad market conditions
In Subsection 4.2, we formally test the impact of changing market conditions on the performance of analyst recommendation revisions, confirming the existence of a significantly negative relationship between the recommendation performance and market conditions, measured as in terms of past market return and/or market volatility
In the final part of our empirical analyses, we employ the non-temporal threshold testing procedure, originally proposed by Hansen (2000), to test whether the dynamic recommendation performance is sensitive to different market conditions, in terms of past market return or market volatility
Summary
There are numerous studies on the information role of financial analysts, while the existing literature mostly ignores the question of whether the performance of their stock recommendations is related to the state of the economy (Chang & Choi, 2017; Loh & Stulz, 2018). Loh and Stulz (2018) provide empirical evidence showing that analysts’ advice (e.g., stock recommendations and earnings forecasts) is more valuable in bad market conditions. The upgrade (downgrade) portfolio generates significantly positive (negative) net abnormal returns in two periods of bad market conditions, i.e., the dot-com bubble burst in 2000 and the credit crisis in 2007, but not in the rest of the sample period, in line with Loh and Stulz (2018). To the best of our knowledge, this is the first study to examine the relationship between market conditions and the recommendation performance in the UK stock market using various alternative methodological approaches, in particular, the non-temporal threshold regression model that has not been employed in prior analyst research.
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