Signaling to partially informed investors in the newsvendor model

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Schmidt, William, Vishal Gaur, ...
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Last edited by MARC Bot
January 4, 2023 | History

Signaling to partially informed investors in the newsvendor model

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We investigate a phenomenon in which firms may attempt to influence their market valuation by choosing an inventory stocking quantity which does not optimize expected profits. We employ the newsvendor model within a signaling game to examine a relatively common scenario in which the firm's equity holder has incomplete information concerning the demand for the firm's product. We apply a perfect Bayesian equilibrium solution and identify ranges of model parameters where the firm's stocking quantity decision does not maximize expected profits. This includes instances in which a firm facing high demand chooses a lower stocking quantity than that which would optimize expected profits and a firm facing low demand chooses a higher stocking quantity than that which would optimize expected profits. This result contrasts with prior research, which has shown that when equity holders have incomplete information about the quality of the firm's opportunities, high quality firms will consistently overinvest and low quality firms will invest to optimize expected profits. We show an extreme example of this behavior in which a high demand firm chooses that stocking quantity which would have been optimal under complete information for a low demand firm.

Publish Date
Language
English
Pages
40

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Edition Availability
Cover of: Signaling to partially informed investors in the newsvendor model
Signaling to partially informed investors in the newsvendor model
2011, Harvard Business School
in English - Rev.

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Book Details


Edition Notes

"April 2011, revised March 2012" -- Publisher's website.

"February 6, 2012" -- added t.p.

Includes bibliographical references.

Published in
[Boston]
Series
Working paper / Harvard Business School -- 11-105, Working paper (Harvard Business School) -- 11-105.

The Physical Object

Pagination
40 p.
Number of pages
40

ID Numbers

Open Library
OL43866852M
OCLC/WorldCat
781554933, 723493810

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January 4, 2023 Edited by MARC Bot import existing book
December 12, 2022 Created by MARC Bot Imported from harvard_bibliographic_metadata record