A non-linear approach for predicting stock returns and volatility with the use of investor sentiment indices
Title: A non-linear approach for predicting stock returns and volatility with the use of investor sentiment indices
Citation: Applied economics, 2016, Vol. 48, No. 31, pp. 2895-2898
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.
Subject: Investor sentiment; stock markets; non-linear dependence; C22; C32; C53; G10; G11
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