Please use this identifier to cite or link to this item:
Title: Dispersion in Options Investors’ Versus Analysts’ Expectations: Predictive Inference for Stock Returns
Authors: Andreou, Panayiotis 
Kagkadis, Anastasios 
Maio, Paulo 
Philip, Dennis 
Major Field of Science: Social Sciences
Field Category: Economics and Business
Keywords: Short Selling;Short-sale Constraints;Options Markets
Issue Date: 1-Apr-2021
Source: Critical Finance Review, 2021, vol. 10, no. 1, pp. 65 - 81
Volume: 10
Issue: 1
Start page: 65
End page: 81
Journal: Critical Finance Review 
Abstract: We create a market-wide measure of dispersion in options investors' expectations by aggregating across all stocks the dispersion in trading volume across moneynesses (DISP). DISP exhibits strong negative predictive power for future market returns and its information content is not subsumed by several alternative equity premium predictors. Consistent with the implications of theoretical models that link dispersion to overpricing, the predictive power of DISP is particularly pronounced in relatively optimistic periods. Although an aggregate analysts' forecasts dispersion (AFD) measure also performs well in optimistic periods, it delivers insignificant overall predictability. This is because in the aftermath of the 2008 financial crisis, AFD was heavily driven by pessimistic forecasts and hence its increase did not reflect a true overpricing. As a result, AFD does not appear to be a robust equity premium predictor in recent years.
ISSN: 2164-5760
DOI: 10.1561/104.00000091
Rights: © Panayiotis C. Andreou, Anastasios Kagkadis, Paulo Maio and Dennis Philip
Attribution-NonCommercial-NoDerivatives 4.0 International
Type: Article
Affiliation : Cyprus University of Technology 
Durham University Business School 
Lancaster University 
Hanken School of Economics 
Appears in Collections:Άρθρα/Articles

CORE Recommender
Show full item record

Page view(s)

Last Week
Last month
checked on Sep 17, 2021

Google ScholarTM



This item is licensed under a Creative Commons License Creative Commons