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Cited by 309

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Investor Sophistication and Market Earnings Expectations

Open access
Walther, Beverly R.·1997·Journal of Accounting Research

Abstract

This paper investigates whether sophisticated investors rely more on analyst forecasts than on time-series model forecasts in forming expected earnings. Specifically, I investigate if earnings-announcement-related returns are more closely associated with analyst (SRW) forecasts for firms for which the marginal investor is more (less) likely to be sophisticated. My proxies for investor sophistication are institutional ownership, analyst following, and firm size (Atiase [1985], Hand [1990]). I predict that market participants place more weight on the analyst forecast for firms with high institutional ownership, firms with high analyst following, and large firms. For a sample of 89,246 firm-quarter observations over 1980-1995, I find that the weight placed on the analyst (SRW) forecast is increasing (decreasing) in institutional ownership, analyst following, and firm size. Forecast availability (as captured by publication in The Wall Street Journal) or forecast accuracy cannot account for these findings. Overall, my results suggest that market earnings expectations do not consistently resemble either analyst or SRW forecasts. Rather, the cross-sectional variation in the relative weights placed on these two forecasts is related to proxies for the sophistication of the marginal investor.

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Metadata

Authors
Walther, B. R.
Venue
Journal of Accounting Research
Publisher
JSTOR
Published
1997
Volume
35
Issue
2
Pages
157
ISSN
0021-8456 (ISSN-L)
OpenAlex
W3126081180
Cited by
309
References
2
FWCI
11.30
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Investor Sophistication and Market Earnings Expectations. https://app.cochat.ai/papers/10.2307/2491358
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Walther, B. R. (1997). Investor Sophistication and Market Earnings Expectations. Journal of Accounting Research. https://doi.org/10.2307/2491358

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

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