Modeling and forecasting abnormal stock returns using the nonlinear Grey Bernoulli model

Bahar Doryab and Mahdi Salehi
Additional contact information
Bahar Doryab: Ferdowsi University of Mashhad
Mahdi Salehi: Ferdowsi University of Mashhad

Journal of Economics, Finance and Administrative Science, 2018, vol. 23, issue 44, 95-112

Abstract: Purpose – This study aims to use gray models to predict abnormal stock returns. Design/methodology/approach – Data are collected from listed companies in the Tehran Stock Exchange during 2005-2015. The analyses portray three models, namely, the gray model, the nonlinear gray Bernoulli model and the Nash nonlinear gray Bernoulli model. Findings – Results show that the Nash nonlinear gray Bernoulli model can predict abnormal stock returns that are defined by conditions other than gray models which predict increases, and then after checking regression models, the Bernoulli regression model is defined, which gives higher accuracy and fewer errors than the other two models. Originality/value – The stock market is one of the most important markets, which is influenced by several factors. Thus, accurate and reliable techniques are necessary to help investors and consumers find detailed and exact ways to predict the stock market.

Keywords: Abnormal returns; Gray theory; Nash nonlinear gray Bernoulli model; Nonlinear gray Bernoulli model (search for similar items in EconPapers)
JEL-codes: D53 (search for similar items in EconPapers)
Date: 2018
References: Add references at CitEc
Citations:

Downloads: (external link)
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3207818 Full text (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ris:joefas:0121

Access Statistics for this article

Journal of Economics, Finance and Administrative Science is currently edited by Nestor U. Salcedo

More articles in Journal of Economics, Finance and Administrative Science from Universidad ESAN 1652 Alonso de Molina, Santiago de Surco 15023, Lima, Peru. Contact information at EDIRC.
Bibliographic data for series maintained by ESAN Ediciones ().