A non-linear approach for predicting stock returns and volatility with the use of investor sentiment indices

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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.

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Keywords

Investor sentiment, Stock markets, Nonlinear dependence

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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.