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

被引:56
作者
Yang, Jian [1 ]
Cabrera, Juan [2 ]
Wang, Tao [3 ,4 ]
机构
[1] Univ Colorado Denver, Sch Business, Denver, CO 80217 USA
[2] CUNY, Grad Ctr, Dept Econ, New York, NY 10016 USA
[3] CUNY, Queens Coll, Dept Econ, Flushing, NY 11367 USA
[4] CUNY, Grad Ctr, Flushing, NY 11367 USA
关键词
Ishares; Random walk; Nonlinear models; Forecasting evaluation; Reality check; ARTIFICIAL NEURAL-NETWORKS; FINANCIAL RISK MANAGEMENT; MODEL-SELECTION APPROACH; TECHNICAL TRADING RULES; TIME-SERIES MODELS; MARKET-EFFICIENCY; LINEAR-MODELS; REALITY CHECK; PRICES; DYNAMICS;
D O I
10.1016/j.ejor.2009.01.009
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
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. (C) 2009 Elsevier B.V. All rights reserved.
引用
收藏
页码:498 / 507
页数:10
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