A cognitive model of stock market reactions to multi-firm alliance announcements

Author:

Ozcan Serden1,Overby Mikkel Lucas2

Affiliation:

1. Copenhagen Business School, Denmark,

2. Serious Games Interactive, Denmark,

Abstract

Previous studies of stock market reactions to alliance announcements assume that investors accurately detect and encode these public statements, evaluate them with stable, well-established preferences, and that the signalling value of an announcement is independent of the context in which it is conveyed.This article draws on behavioural decision theory to advance a cognitive model of stock market reactions to the announcement of complex, multi-firm alliances. The model predicts a U-shaped relationship between the diversity of partners comprising the alliance and abnormal stock market returns. An empirical analysis of multi-firm alliances announced in the US between 2000 and 2004 corroborates the model's prediction. Moreover, the study shows that a firm's size and analyst coverage moderate the relationship between its alliance partners' diversity and its abnormal returns.These findings suggest that attentional selection and subsequent encoding processes produce cognitive biases in the interpretation of announcements and the market moves towards greater efficiency for large or high-coverage firms. Managers should thus take the effect of the `process of processing' into account when disclosing information to the investor community.

Publisher

SAGE Publications

Subject

Strategy and Management,Industrial relations,Education,Business and International Management

Cited by 29 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3