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Essays on Earnings Forecasting Accuracy

Luo, Shuqing (2011) Essays on Earnings Forecasting Accuracy. Doctoral Dissertation, University of Pittsburgh. (Unpublished)

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Abstract

This dissertation comprises two essays on earnings forecasting accuracy. Chapter 2 focuses on how management forecasting accuracy is affected by managers' behavioral biases over time and Chapter 3 addresses how analyst portfolio design choices affect cross-sectional differences in analyst forecasting accuracy.In particular, Chapter 2 examines how CEOs' overconfidence and their exhibited self-serving attribution biases affect how they adjust their future earnings forecasts when they receive feedback concerning their prior forecasts. I find that overconfident CEOs respond to feedback by improving their future forecasting accuracy, but they do so more slowly than their less confident peers. I also find that overconfident CEOs learn to improve their future forecasting accuracy only when feedback is less ambiguous in the form of forecasting errors. In contrast, managers who are less confident respond to both less ambiguous forecasting errors and more ambiguous market feedback concerning their prior forecasts. Chapter 3 examines analysts' supply chain coverage portfolio design and their forecasting accuracy. I define the relation between a firm and one of the firm's major customer firms as a "supply chain relation". Further, I define an analyst who issues forecasts for both the firm and one or more of the firm's major customers in the same year as a "supply chain analyst". I classify all firms followed by the supply chain analyst into one of the three categories in a given year: "focal firms", i.e., firms for which the analyst also covers one or more of the firm's major customers, "major customers" of a focal firm for the analyst, and "other" firms which include all remaining firms in the analyst's portfolio. I find that analysts who follow both a focal firm and one or more of the firm's major customers issue significantly more accurate earnings forecasts for both the focal firm and the firm's major customers than the same analysts issue for "other" firms in the analyst portfolio. I also find that these analysts are more accurate in their forecasts for the focal firm and the firm's major customers than other non-supply chain analysts following the same firm, but not the firm's supply chain. I show that the superior forecasting accuracy for supply chain analysts for both the focal firm and the firm's major customers is achieved at the cost of reduced forecasting accuracy for "other" firms in the analyst portfolio. In explaining the relative importance of forecasting accuracy for the firms in the analyst portfolio, I find that focal firms and the firms' major customers are more likely to generate more profitable trading commissions and operate in an industry segment that has a greater number of other peer firms than "other" firms in the same analyst portfolio. This evidence is consistent with earlier studies and suggests when analysts have stronger incentives to generate trading commissions from the stock of a firm, the analysts are more likely to spend effort to acquire more precise information about the firm (Hayes, 1998). When covering the firm's supply chains helps analysts produce more precise information about the firm, analyst forecasting accuracy improves accordingly.


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Details

Item Type: University of Pittsburgh ETD
Status: Unpublished
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Luo, Shuqingshl37@pitt.eduSHL37
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee CoChairEvans, John Hjhe@katz.pitt.eduJHE
Committee CoChairNagarajan, Nandu Jnagaraja@katz.pitt.eduNAGARAJA
Committee MemberKim, Kyongheekimkyo@missouri.edu
Committee MemberFeng, Meimfeng@katz.pitt.eduMEF23
Committee MemberHoffman, Vicky Bvickyh@katz.pitt.eduHEIMAN
Date: 1 February 2011
Date Type: Completion
Defense Date: 26 October 2010
Approval Date: 1 February 2011
Submission Date: 16 October 2010
Access Restriction: 5 year -- Restrict access to University of Pittsburgh for a period of 5 years.
Institution: University of Pittsburgh
Schools and Programs: Joseph M. Katz Graduate School of Business > Business Administration
Degree: PhD - Doctor of Philosophy
Thesis Type: Doctoral Dissertation
Refereed: Yes
Uncontrolled Keywords: Analyst Forecast; CEO Overconfidence; Supply Chain; Supply Chain Analysts; Analyst Portfolio Design; Management Forecast
Other ID: http://etd.library.pitt.edu/ETD/available/etd-10162010-005802/, etd-10162010-005802
Date Deposited: 10 Nov 2011 20:03
Last Modified: 15 Nov 2016 13:50
URI: http://d-scholarship.pitt.edu/id/eprint/9480

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