A Nonlinear Approach for Predicting Stock Returns and Volatility with the Use of Investor Sentiment Indices
Rangan Gupta () and
No 201536, Working Papers from University of Pretoria, Department of Economics
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, and Huang et al. (2015) developed a new investor sentiment index, SPLS, which they show 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 or SPLS predicts stock market returns or even its volatility, as opposed to previous empirical evidence.
Keywords: Investor sentiment; stock markets; nonlinear dependence (search for similar items in EconPapers)
JEL-codes: C22 C32 C53 G10 G11 (search for similar items in EconPapers)
Pages: 7 pages
New Economics Papers: this item is included in nep-cfn and nep-ore
References: Add references at CitEc
Citations: Track citations by RSS feed
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
Journal Article: A non-linear approach for predicting stock returns and volatility with the use of investor sentiment indices (2016)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:pre:wpaper:201536
Access Statistics for this paper
More papers in Working Papers from University of Pretoria, Department of Economics Contact information at EDIRC.
Bibliographic data for series maintained by Rangan Gupta ().