On the Structure of Analyst Research Portfolios and Forecast Accuracy

Journal of Accounting Research (Impact Factor: 2.38). 09/2009; 47(4):867-909. DOI: 10.1111/j.1475-679X.2009.00338.x
Source: RePEc


ABSTRACT This study provides insights into the forces and constraints that shape analyst research coverage along country and sector dimensions and the impact of the structure of an analyst's portfolio on forecast accuracy. We find that analyst specialization by country and sector is sensitive to the extent to which firms "within" a country or sector and firms "across" country-sectors are exposed to common economic forces, the potential for revenue generation, and broker culture. Our tests indicate that existing research on the relation between analyst portfolio structure and forecast accuracy may suffer from an endogeneity bias. We use our analysis of analyst specialization to develop controls for this bias. Once we employ these controls, we find that country diversification is associated with superior forecast accuracy. However, the relation between sector diversification and forecast accuracy is context-specific. Specifically, sector diversification enhances forecast accuracy in an international context, while it detracts from forecast accuracy in a domestic U.S. context. Copyright (c), University of Chicago on behalf of the Accounting Research Center, 2009.

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Available from: Omesh Kini
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    • "Palepu (1985) and Rumelt (1982) utilize complete data to investigate the same issue and reach a conclusion similar to that presented by Gort. In terms of literature on product diversification of a firm and earnings forecast accuracy, Kini et al. (2009) indicate that the relation between sector diversification and forecast accuracy is context‐ specific. In an international context such as European Zone, forecast accuracy may increase with sector diversification, whereas in the U.S., analyst may generate higher accuracy when focus on a specific industry. "

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    • "F-tests on the equality of the coefficients on CHAIN_ANALYST and IND indicate that the difference is statistically significant (p < 0.01) in all regression specifications, consistent with analysts following supply chain specialization generating significantly more accurate and less optimistically biased forecasts for the supplier firms than industry specialists following the same supplier firms (H3). The signs and significance levels for the effect of other analyst and firm characteristics on forecast performance are generally consistent with those reported in prior research (e.g., Mikhail et al. 1997; Clement 1999; Jacob et al. 1999; Kini et al. 2009; Sonney 2009), except for the unexpectedly positive but insignificant coefficient on DM_logNFIRM in the ACCURACY regression. [Insert TABLE 4 about here] In terms of the economic significance of these results, the coefficient of 0.0517 in the ACCURACY regression (column (1) of Table 4), for example, suggests that holding various firm, analyst, and forecast characteristics constant, supply chain analysts are 0.05% more accurate than NONE = 1 analysts, which represents 34.5% (0.0517%/0.15%=34.5%) of the mean forecast accuracy of NONE =1 analysts for the supplier firms. "
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    ABSTRACT: This study examines the antecedents and consequences of analysts choosing to become supply chain analysts (i.e., analysts following both a supplier and its major customer). We find that information complementarities between firms in the same supply chain, between a supplier firm and its industry peer firms, and between the supplier’s major customer and other firms in analysts’ portfolio affect their supply chain specialization decision. The potential revenues supplier firms generate for analysts’ brokerage houses also significantly affect this decision. While supply chain analysts achieve superior forecast performance compared to non-supply chain analysts for supplier firms, they provide lower quality forecasts for other firms in their portfolios. These findings suggest that analysts allocate resources strategically. Our results are robust to techniques designed to address the potential endogeneity of analysts’ supply chain portfolio choices.
    Full-text · Article · Sep 2015 · The Accounting Review
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    • "Insert Figure 1 Approximately Here Both averages of common and individual coverage forecast correlations increase with the number of analysts with common coverage. This is consistent with the evidence in Kini et al. (2009) "
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    ABSTRACT: We examine whether sell-side analyst research generates comovement in stock returns. Each year, we form pairs of stocks and show that analysts who cover both stocks in a pair expect their future earnings to be more highly correlated than do analysts who cover only one stock in the pair. These correlation expectations have pricing consequences. The price reactions of a pair of stocks to a forecast or recommendation are closer when the issuing analyst covers both stocks than when the analyst covers only one. Moreover, the daily stock return correlation between stocks in a pair increases with the fraction of analysts covering both stocks and the fraction of forecasts issued by analysts covering both stocks. Collectively, the evidence is consistent with stronger information spillovers and return comovement between stocks that share coverage from the same analysts.
    Preview · Article · Mar 2012 · Journal of Accounting Research
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