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

Jian Yang, Juan Cabrerab and Tao Wang
European Journal of Operational Research, Vol. 200 Issue 2,  pp. 498-507

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.