Earnings Extrapolation and Predictable Stock Market Returns / Hongye Guo.

Format:

Book

Thesis/Dissertation

Author/Creator:

Guo, Hongye, author.

Contributor:

University of Pennsylvania. Finance, degree granting institution.

Language:

English

Subjects (All):

Finance.

Finance--Penn dissertations.

Penn dissertations--Finance.

Local Subjects:

Finance.

Finance--Penn dissertations.

Penn dissertations--Finance.

Physical Description:

1 online resource (102 pages)

Distribution:

Ann Arbor : ProQuest Dissertations & Theses, 2022

Contained In:

Dissertations Abstracts International 84-03A.

Place of Publication:

[Philadelphia, Pennsylvania] : University of Pennsylvania, 2022.

Language Note:

English

Summary:

The U.S. stock market's return during the first month of a quarter correlates strongly with returns in future months, but the correlation is negative if the future month is the first month of a quarter, and positive if it is not. These effects offset, leaving the market return with its weak unconditional predictive ability known to the literature. The pattern accords with a model in which investors extrapolate announced earnings to predict future earnings, not recognizing that earnings in the first month of a quarter are inherently less predictable than in other months. Survey data support this model, as does out-of-sample return predictability across industries and international markets. These results challenge the Efficient Market Hypothesis and advance a novel mechanism of expectation formation.

Notes:

Source: Dissertations Abstracts International, Volume: 84-03, Section: A.

Advisors: Stambaugh, Robert; Committee members: Dou, Winston; Roussanov, Nikolai; Wachter, Jessica.

Department: Finance.

Ph.D. University of Pennsylvania 2022.

Local Notes:

School code: 0175

ISBN:

9798351434155

Access Restriction:

Restricted for use by site license.