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Aggregate analyst characteristics and forecasting performance
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DOI：10.1111/acfi.13262.png)
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摘要
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This paper examines the advantages of aggregate measures of analyst characteristics to researchers and investors interested in explaining differences in analysts' forecasting performance. We show while single-characteristic and factor-based measures reflecting attributes such as forecasting experience, access to resources and portfolio complexity vary significantly in the extent to which each explains analyst forecasting performance, equal-weighted composite measures based on single characteristics or on factors extracted from those characteristics are consistently associated with forecasting bias arising from a range of indicators of reduced earnings quality. These aggregate measures of analyst characteristics require no additional data beyond traditional archival sources and offer a useful method of testing the impact of analyst characteristics on their forecasting performance.
Keyword:
analyst characteristics
analyst expertise
analyst forecasts
analyst optimism
earnings quality
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2.6
论文数:
1.8K
被引数:
4.5K
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