Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/109739
Title: Common analyst coverage and information transfers within analyst portfolios
Authors: Ji, Mingming
Degree: Ph.D.
Issue Date: 2022
Abstract: This paper examines the role of information transfers within an analyst’s portfolio in improving analyst forecast accuracy. Given that firms co-covered by the same analyst are economically linked, such linkages captured by common analyst coverage make information on one firm collected and processed by an analyst valuable for the analyst to analyze other firms within the same portfolio. I take management earnings forecasts as the sources of information, and focus on the information transfers from large firms to small firms within analysts’ portfolios. Considering the top (bottom) quartile firms in terms of market capitalization in an analyst’s portfolio as large (small) firms, I find that there exist information transfers from large firms to small firms. Specifically, I show a positive intra-analyst information spillover effect, that is, the management earnings forecasts issued by large firms can reduce analysts forecast errors on the small firms within the same analyst portfolio. In addition, I find greater spillover effects if the portfolio firm linkages are stronger (captured by common industry and peer analyst coverage), if analysts are more experienced (captured by general and industry-specific experience), and if small firms face greater uncertainty (captured by firm age and analyst dispersion). I also show that the spillover effect is through the information environment mechanism as information asymmetry of small firms is significantly reduced thanks to information spillovers. Finally, I document that the information spillover effect is asymmetric (i.e., there is only large-to-small but no small-to-large information spillovers), and the market reacts positively to analyst forecast revisions with information spillover.
Subjects: Investment analysis
Business forecasting
Hong Kong Polytechnic University -- Dissertations
Pages: 57 pages : illustrations
Appears in Collections:Thesis

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