Economics at your fingertips  

Testing Market Efficiency with Nonlinear Methods: Evidence from Borsa Istanbul

Fuzuli Aliyev ()
Additional contact information
Fuzuli Aliyev: Finance Department, Baku Engineering University, Baku AZ0101, Azerbaijan

International Journal of Financial Studies, 2019, vol. 7, issue 2, 1-11

Abstract: Market efficiency has been analyzed through many studies using different linear methods. However, studies on financial econometrics reveal that financial time series exhibit nonlinear patterns because of various reasons. This paper examines market efficiency at Borsa Istanbul using a smooth transition autoregressive (STAR) type nonlinear model. I develop nonlinear ARCH and STAR models, a linear AR model and random walk model for 10 years’ weekly data and then out-of-sample forecast next 12 weeks’ return. Comparing forecast performance powers, I find that the STAR model outperforms random walk, that is Borsa Istanbul returns are predictable at the given period. The results show that the shareholders may earn abnormal return and identify the direction of the return change for the next week with at least 66% accuracy. Contrary to the linear level studies, these findings show that the Borsa Istanbul is not weak form efficient at nonlinear level within the studied period.

Keywords: market efficiency; nonlinear models; STAR; return prediction (search for similar items in EconPapers)
JEL-codes: G1 G2 G3 F2 F3 F41 F42 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed

Downloads: (external link) (application/pdf) (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:

Access Statistics for this article

International Journal of Financial Studies is currently edited by Prof. Dr. Nicholas Apergis

More articles in International Journal of Financial Studies from MDPI, Open Access Journal
Bibliographic data for series maintained by XML Conversion Team ().

Page updated 2019-06-22
Handle: RePEc:gam:jijfss:v:7:y:2019:i:2:p:27-:d:237146