Date: 2016
Type: Article
A non-linear approach for predicting stock returns and volatility with the use of investor sentiment indices
Applied economics, 2016, Vol. 48, No. 31, pp. 2895-2898
BEKIROS, Stelios D., GUPTA, Rangan, KYEI, Clement, A non-linear approach for predicting stock returns and volatility with the use of investor sentiment indices, Applied economics, 2016, Vol. 48, No. 31, pp. 2895-2898
- https://hdl.handle.net/1814/44651
Retrieved from Cadmus, EUI Research Repository
The popular sentiment-based investor index SBW introduced by Baker and Wurgler (2006, 2007) is shown to have no predictive ability for stock returns. However, Huang et al. (2015) developed a new investor sentiment index, SPLS, which can predict monthly stock returns based on a linear framework. However, the linear model may lead to misspecification and lack of robustness. We provide statistical evidence that the relationship between stock returns, SBW and SPLS is characterized by structural instability and inherent nonlinearity. Given this, using a nonparametric causality approach, we show that neither SBW nor SPLS predicts stock market returns or even its volatility, as opposed to previous empirical evidence.
Additional information:
Published online: 05 Jan 2016
Cadmus permanent link: https://hdl.handle.net/1814/44651
Full-text via DOI: 10.1080/00036846.2015.1130793
ISSN: 0003-6846
Publisher: Routledge
Keyword(s): Investor sentiment stock markets non-linear dependence C22 C32 C53 G10 G11
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