Summary
The paper titled "The Seasonality in Sell-Side Analysts’ Recommendations" investigates whether there is seasonality in investment recommendations issued by star analysts and non-star analysts. The study finds that both star and non-star analysts tend to issue more optimistic recommendations in May, contradicting the well-known market adage, "Sell in May and go away."
Non-star analysts were found to be more optimistic in their price targets compared to star analysts. Moreover, the study reveals that the cyclicality in analysts' optimism is more closely linked to corporate earnings announcement schedules rather than overall market trends. Additionally, analysts do not explicitly account for known seasonal effects when setting their recommendations and price targets.
Using I/B/E/S data from 2003 to 2014, the researchers analyzed how seasonality influences analysts' optimism cycles and how earnings announcements impact target price forecasts. The study emphasizes that investors should be aware that analysts are most optimistic in May, which could influence investment decisions.
Methodology
Data Collection
➤ Analyst recommendation and price target data were collected from the I/B/E/S database (2003-2014).
➤ Star analysts were identified using Institutional Investor, StarMine, and The Wall Street Journal rankings.
➤ Compustat data was used to track corporate earnings announcement dates.
Market Seasonality Analysis
➤ CRSP index data was analyzed to examine seasonal patterns in daily and monthly market returns from 2003 to 2014.
Target Price Seasonality Analysis
➤ The mean target price expected return (TPER) was calculated separately for star and non-star analysts.
➤ Seasonal differences were examined between the summer (May–October) and winter (November–April) periods.
➤ The study also assessed how buy, hold, and sell recommendations varied across seasons.
Regression Analysis
➤ OLS regression was used to analyze factors influencing target price forecasts, with independent variables including:
➤ Seasonal dummy variables
➤ Past and future market returns
➤ Earnings announcement frequency
Earnings Announcements & Optimism Cycles
➤ Analysts’ average target prices over the year were compared against corporate earnings release schedules to determine the relationship between analyst optimism and earnings cycles.
Key Findings
No Strong Market Seasonality
➤ Unlike prior studies, this research did not find a clear seasonal pattern in market returns from 2003 to 2014.
➤ The researchers suggest this may be due to the short sample period or increased market awareness of seasonality effects.
Target Price Seasonality
➤ Both star and non-star analysts issued more optimistic price targets during the summer months, contradicting the "Sell in May" theory.
➤ Non-star analysts were consistently more optimistic than star analysts, particularly in buy and hold recommendations.
Earnings Announcements & Optimism Cycles
➤ Analysts’ optimism was more strongly correlated with earnings announcement schedules than with market returns.
➤ As the number of quarterly earnings reports increased, analysts issued more optimistic price targets.
➤ However, analyst optimism tended to decline in the month before peak earnings release periods, suggesting that uncertainty leads to excessive optimism during periods of limited information.
Star vs. Non-Star Analyst Differences
➤ Non-star analysts were significantly more optimistic than star analysts in buy and hold recommendations.
➤ In contrast, star analysts were more cautious and less likely to issue overly optimistic forecasts.
➤ This implies that star analysts exhibit a more conservative approach compared to non-star analysts.
Conclusion
This study provides valuable insights into the seasonal patterns of analysts’ recommendations, challenging the "Sell in May" theory by showing that analysts tend to be most optimistic during the summer months.
Additionally, the research highlights that analyst optimism is more influenced by corporate earnings cycles rather than general market trends, suggesting that investors should consider earnings announcement schedules when interpreting analysts' recommendations.
Moreover, the study demonstrates clear differences between star and non-star analysts, with star analysts being generally more conservative in their recommendations. This suggests that investors should carefully evaluate analyst reputation and track record when considering investment advice.
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