Nonlinearity, data-snooping, and stock index ETF return predictability

Jian Yang, Juan Cabrera and Tao Wang

European Journal of Operational Research, 2010, vol. 200, issue 2, pages 498-507

Abstract: This paper examines daily return predictability for eighteen international stock index ETFs. The out-of-sample tests are conducted, based on linear and various popular nonlinear models and both statistical and economic criteria for model comparison. The main results show evidence of predictability for six of eighteen ETFs. A simple linear autoregression model, and a nonlinear-in-variance GARCH model, but not several popular nonlinear-in-mean models help outperform the martingale model. The allowance of data-snooping bias using White's Reality Check also substantially weakens otherwise apparently strong predictability.

Keywords: Ishares; Random; walk; Nonlinear; models; Forecasting; evaluation; Reality; check (search for similar items in EconPapers)
Date: 2010

Downloads: (external link)
http://www.sciencedirect.com/science/article/B6VCT ... bde6fc16a381e6b07b99
Full text for ScienceDirect subscribers only

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: http://EconPapers.repec.org/RePEc:eee:ejores:v:200:y:2010:i:2:p:498-507

Access Statistics for this article

European Journal of Operational Research is edited by Roman Slowinski, Jesus Artalejo, Jean-Charles. Billaut, Robert Dyson and Lorenzo Peccati

More articles in European Journal of Operational Research from Elsevier
Series data maintained by Heidi Boesdal ().