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Analyst Pessimism And Forecast Timing, Orie E. Barron, Donal Byard, Lihong Liang
Analyst Pessimism And Forecast Timing, Orie E. Barron, Donal Byard, Lihong Liang
Lihong Liang
In this study, we show that on average relatively pessimistic analysts tend to reveal their earnings forecasts later than other analysts. Further, we find this forecast timing effect explains a substantial proportion of the well-known decrease in consensus analyst forecast optimism over the forecast period prior to earnings announcements, which helps explain why analysts’ longer term earnings forecasts are more optimistically biased than their shorter term forecasts. We extend McNichols and O’Brien’s (1997) and Hayes’ (1998) theory concerning analyst self-selection to argue that analysts with a relatively pessimistic view - compared to other analysts - are more reluctant to issue …
The Determinants Of Analyst-Firm Pairings, Lihong Liang, Edward J. Riedl, Ramgopal Venkataraman
The Determinants Of Analyst-Firm Pairings, Lihong Liang, Edward J. Riedl, Ramgopal Venkataraman
Lihong Liang
This paper explores the determinants of observed analyst-firm pairings. We adopt an analyst/brokerage house perspective that allows us to examine not only firm-level characteristics as in prior research, but also attributes of the analyst and the analyst’s brokerage house that may drive these pairings. Our empirical analyses provide two primary insights. First, analyst characteristics such as industry expertise and relative experience, and brokerage house characteristics such as continuity of coverage, are associated with the decision to follow a firm. Second, there is substantial variation in the association between firm, analyst, and brokerage house characteristics and the decision to follow a …
Post-Earnings Announcement Drift And Market Participants' Information Processing Biases, Lihong Liang
Post-Earnings Announcement Drift And Market Participants' Information Processing Biases, Lihong Liang
Lihong Liang
Prior research has been unable to explain the phenomenon known as post-earnings announcement drift, raising questions concerning the semi-strong form efficiency of the market typically assumed in capital market research. This study contributes to our understanding of this anomaly by examining drift in the context of theories that consider investors' non-Bayesian behaviors. The empirical evidence reveals that investors' overconfidence about their private information and the reliability of the earnings information are two important factors that explain drift. Finally, this study also provides insight into the puzzling relationship between dispersion and drift discussed in prior research.