Artikel

Attitudes towards ambiguous information and stock returns

This study examines whether investors' attitudes toward ambiguity can explain cross-sectional stock returns by investigating the relationship between future stock returns and option-implied volatilities as well as implied third moments. We find that investors' attitudes toward different levels of ambiguous stocks help explain cross-sectional variations of stock returns during the 1996-2010 period in the U.S. stock market. In this study, investors' attitudes toward ambiguity are measured by stocks' option-implied third moments. Negative-skewed quintiles represent ambiguity aversion and vice versa. Different levels of ambiguity for stocks are distinguished by stocks' option-implied volatility. High volatility quintiles represent stocks with high information ambiguity. Independent two-dimension sorting results show that ambiguity averters are compensated for holding stocks with higher ambiguity. Meanwhile, ambiguity-loving investors are willing to give up some returns to hold stocks with lower levels of ambiguity. The results show that both types of ambiguity attitudes increase the factor model's explanatory power. The estimated monthly premiums for ambiguity-aversion and ambiguity-loving factors are 0.38% and 1.28%, respectively.

Sprache
Englisch

Erschienen in
Journal: Cogent Economics & Finance ; ISSN: 2332-2039 ; Volume: 7 ; Year: 2019 ; Issue: 1 ; Pages: 1-33

Klassifikation
Wirtschaft
Asset Pricing; Trading Volume; Bond Interest Rates
Thema
uncertainty
ambiguity-aversion premium
ambiguity-loving premium
stock returns
factor model

Ereignis
Geistige Schöpfung
(wer)
Zhang, Ziyun
Ereignis
Veröffentlichung
(wer)
Taylor & Francis
(wo)
Abingdon
(wann)
2019

DOI
doi:10.1080/23322039.2019.1693678
Handle
Letzte Aktualisierung
10.03.2025, 11:44 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Artikel

Beteiligte

  • Zhang, Ziyun
  • Taylor & Francis

Entstanden

  • 2019

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