A non-linear approach for predicting stock returns and volatility with the use of investor sentiment indices
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Date
Authors
Bekiros, Stelios
Gupta, Rangan
Kyei, Clement Kweku
Journal Title
Journal ISSN
Volume Title
Publisher
Routledge
Abstract
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.
Description
Keywords
Investor sentiment, Stock markets, Nonlinear dependence
Sustainable Development Goals
Citation
Stelios Bekiros, Rangan Gupta & Clement Kyei (2016) A non-linear approach for predicting stock returns and volatility with the use of investor sentiment indices, Applied Economics, 48:31, 2895-2898, DOI: 10.1080/00036846.2015.1130793.
